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Electrochemical energy systems such as batteries and supercapacitors have played an important role in society for two centuries. The rise of the consumer electronics industry has been underpinned by innovations in battery technology, and batteries are subject to more public interest now than ever before due to the uptake of electric vehicles and the demand for grid-scale batteries to stabilise an intermittent renewable energy supply. Most electrochemical energy systems are complex. A multitude of processes over different length- and time-scales drive their realised performance. One source of complexity arises from the enigmatic mechanism by which inter-particle interactions at the atomistic scale give rise to critical macroscopic behaviours. Examples of this can be found in liquid electrolytes, for which electrostatic screening lengths and ion conductivity are both observed to deviate significantly from predictions of classical theories at high concentrations. A second source of complexity is that each system is operated in a different way in practice, and the way a system is used strongly influences both short- and long- term performance, with each system following a unique degradation trajectory. This thesis will demonstrate that both of these challenges can be tackled through the combination of data, physical intuition and machine learning. Machine learning models can learn from orders of magnitude more data than humans can, and we will see that such models can be trained to make more accurate predictions about how electrochemical systems will perform under different operating conditions. In addition, machine learning can act as a "computational microscope", offering new ways of understanding the molecular origin of macroscopic properties. I begin by addressing the enigmatic under-screening effect observed in concentrated electrolytes, and explore whether discrepancies between classical theory and experiment can be explained using the concept of ion pairing, by identifying the number of statistically distinct environments inhabited by ions. The results bring into question the validity of the ion pair hypothesis for concentrated systems, but more importantly they suggest that static properties of electrolytes, such as screening length, can be explained by studying statistical differences between local ionic environments rather than just the mean local environment as captured by the radial distribution function. Extending this, I then posit that global dynamic properties such as ion conductivity can also be decomposed into atomistic contributions that are functions of local static structure. The idea is to learn the mapping from local structural motif to a local contribution to conductivity, which effectively generalises ideas first put forward in the ion-pair hypothesis or "cluster Nernst-Einstein" theory. By studying the distributions of local conductivities across electrolytic systems we can decipher what structural motifs are correlated with enhanced or degraded conductivity. I then turn to address the system level challenge of forecasting how electrochemical systems will respond to different operating conditions. In the growing lithium-ion battery industry, this is a major challenge, since batteries of the same chemistry will respond differently to the same use conditions due to differences in internal state caused by manufacturing heterogeneity and different extents of degradation. We develop a general framework that combines electrochemical impedance spectroscopy with machine learning to predict how a battery will respond to a given use condition, which has relevance for the design of improved battery management systems. The findings of this thesis help to further our understanding of the fundamental mechanism by which inter-ion interactions give rise to screening and conduction within liquid electrolytes. More broadly, these findings can help to guide the design of novel electrolytes for next generation systems, to develop optimal fast-charging protocols that do not sacrifice battery life, and to triage batteries towards second-life applications.

The work presented in this thesis focusses on developing a high-energy all-organic membrane-free redox flow battery. Redox flow batteries are promising energy storage devices due to the decoupling of energy capacity and power. Low energy densities owing to using aqueous electrolytes, alongside costly inorganic redox materials and ion-exchange membranes hinder their mass commercialisation. Organic redox active materials and non-aqueous electrolytes are promising pathways to realising high energy density redox flow batteries at an affordable price. Additionally, manipulation of the liquid/liquid interface that forms between high concentration water-in-salt electrolytes and non-aqueous electrolytes presents a method of removing the expensive, and lifetime limiting membranes. The main body of this work concentrates on a novel redox active molecule for the negative half-cell, octafluoro-9,10-anthraquinone. Octafluoro-9,10-anthraquinone shows promising redox properties, with a highly negative redox potential, rapid mass transfer, and rapid kinetics. Instability of the highly reactive charged states when in high concentrations leads to rapid decomposition and passivates the electrode. Typical stabilisation techniques, such as hydrogen bonding, protonation, and more strongly supporting electrolytes did not stabilise the reduced states. The instability of the charged states of novel redox materials is a constant challenge in this field, as capacity loss is present in every non-aqueous organic redox material to date. Low concentrations of the quinone show promising battery performance in a membrane-free device. The membrane-free devices separate the half-cells by a liquid/liquid interface that forms from the spontaneous partitioning of high concentration water-in-salt electrolytes and acetonitrile. Through studying a selection of inorganic and organic catholyte materials, this study demonstrates a novel organic membrane-free water-in-salt based static battery. However, incomplete separation and subsequent reactions of the organic materials limits the system to only static function. Flowing the membrane-free device perturbs the interface and propagates self-discharge reactions, which destroys the promising performance seen in the static systems. The second focus of this work involves a separate study covering organic redox active, high concentration deep eutectic solvent-based electrolytes. The study discovers a redox active novel benzophenone/(2,2,6,6-tetramethylpiperidin-1-yl)oxyl deep eutectic solvent with a lower viscosity and density than previously reported systems. The work highlights the challenges of using highly concentrated electrolyte solutions for redox flow battery applications.

Estimating the state of health of battery energy storage systems is key to their operational safety and reliability, both of which affect lifetime cost. However, accurate estimation of state of health remains challenging, as measurement techniques used in laboratory environments are not available in real-world operating environments. In this work, a framework is developed that combines the relative strengths of commonly applied model- and data-driven approaches to state of health estimation. Gaussian process regression, a flexible Bayesian method of learning arbitrary functions from input-output data, is applied to estimate the parameters of low-order battery models as functions of internal states, operating conditions and lifetime. The approach is first motivated by the difficulty of parameter identification for physics-based battery models from real-world data. Then it is shown how electrical equivalent circuit models can be extended to include parameter dependencies on operating conditions and lifetime in a data-driven manner. The framework is then applied to two different usage scenarios. First, internal resistance is estimated for a fleet of solar-connected lead-acid batteries located in sub-Saharan Africa, where the resulting health metric is shown to provide an early indication of end-of-life failure. Second, a first-order RC circuit, coupled with a one-state thermal model, is parameterised in a joint process that also simultaneously estimates battery states, using data from a Li-ion cell under laboratory conditions. The only prerequisite was the cell-level open-circuit voltage versus charge curve and, in the case of the Li-ion cell model, a single thermal parameter. Given this, the method is agnostic to chemistry and battery construction. Enabling robust and fast state of health estimation for large fleets of batteries has the potential to `close the loop' in terms of battery energy storage system design. Instead of performing laboratory-based ageing experiments, field data can be used directly to determine factors that affect battery life. By incorporating this information into fault diagnosis and health-aware battery management systems, safety and reliability will be improved. Furthermore, with deeper understanding of degradation in the real world, better design of energy storage systems will ultimately lead to better cost efficiency through reduced over-engineering.

Mesoporous carbons (MCs) have been used for a wide range of applications such as energy storage and soft-templating synthesis proves to be an effective method to generate highly ordered MCs. This thesis systematically explores the feasibility of applying amphiphilic ILs as recyclable template to fabricate ordered MCs for supercapacitors by a combination of computational and experimental techniques. The thesis begins with a comprehensive review of the literature, which covers the most important aspects of the research and identifies the critical research gaps. This sets up the objectives of the work in a clear way with a templating synthesis route proposed that comprises four major steps: 1) the self-assembly process, 2) the cross-linking of carbon precursors, 3) extraction of IL templates, and 4) calcination. Chapter 2 compares three different computational modelling approaches on their ability to describe the self-assembly of ILs in binary aqueous solutions as benchmark work. This leads on to Chapter 3, where coarse-grained molecular dynamics simulation is applied to gain understanding into the self-assembly of ternary systems that include carbon precursors, and results from modelling are complemented by experiments. Chapter 4 focuses on the next step of the synthesis - cross-linking of the carbon precursor, which reveals the role of cross-linking in the pore architecture, surface functionality, and electrochemical performance of the resulting MCs. Finally, under the guidance of earlier chapters, Chapter 5 focuses on the main aim of the thesis - synthesis of mesoporous carbons using ILs as templates for supercapacitor applications. The thesis ends with a conclusion and reflection chapter. Moving forward from the templating mechanism to practical preparation, this work provides a solid foundation on IL-templated synthesis of ordered MCs.

This thesis addresses the question: Can we characterize requirements for flexibility over different timescales in electricity systems dominated by solar and wind power? Storage and flexibility play an increasingly important role, but there is great uncertainty about amounts of flexibility needed and how they depend on generation mix and demand, including electrification of heating and transportation. Furthermore, to inform investment and planning, it is valuable to characterize the timescales over which flexibility will be needed, as different resources can be used to shift energy over different time horizons. To address this problem, the analysis uses the novel application of three methods to disaggregate overall flexibility requirements into short-, medium-, and long-term requirements, without relying on assumptions about technology parameters or costs. These methods are illustrated using the case of Great Britain and results are used to draw insights into GB flexibility needs under future scenarios. Flexibility is required over multiple timescales, from less than hourly to interseasonal or longer. Overcapacity of renewables provides value in terms of avoided storage costs, particularly displacing requirements for the longest duration storage, though generation capacity beyond 120% of demand yields diminishing marginal returns. Heating electrification has a larger impact than EVs, though flexible heating can partially offset additional power capacity needs. In all cases, the capacity required to shift energy by up to a day was on the order of 1 TWh; this could account for over half of all energy shifted depending on flexible resource operation. Electricity systems with at least 80% of energy from solar and wind require 3-150 TWh to shift energy by weeks or longer. The required capacity to shift energy by more than one year could potentially be avoided using renewables overcapacity, dispatchable generation, or interconnectors.

The work in this thesis focuses on the metallic anode in two of the divalent battery systems: aqueous zinc batteries and calcium-ion batteries. By performing systematic studies, we aim to provide a deep understanding of their anode degradation mechanisms: In Chapter 3, I looked at the ageing-induced degradation in ZnSO4-based aqueous zinc batteries. It was found that ageing can lead to significant anode capacity loss, in some cases over 70% efficiency loss after only 24 hours. We assessed such loss with respect to various factors: ageing time, anode loading, cycling rates etc. and investigated the root causes of such ageing-induced capacity loss using in-situ Computed X-Ray Tomography. A paper based on this chapter, 'Decoupling and Quantifying Aging-Induced Zn Anode Degradation Processes in Aqueous Zinc Batteries' has been submitted to 'Joule' and is now under review. In Chapter 4, I explored a possible strategy to mitigate the dendrite problem in the ZnSO4-based aqueous zinc batteries. By using a single-crystal (002) Zn as an ideal model anode, I promoted planar Zn deposition and defect suppression, which largely resolved the dendrite problem and allowed excellent cell performance at high-rate and long-cycle conditions. A paper based on this chapter, 'Achieving Ultra‐High Rate Planar and Dendrite‐Free Zinc Electroplating for Aqueous Zinc Battery Anodes' has been published in 'Advanced Materials'. In Chapter 5, I systematically studied and visualized the plating and stripping process in the Ca(BH4)2-based calcium-ion battery electrolyte using in-situ TEM. I revealed that despite calcium deposition being mostly globular, calcium dendrite formation can still occur as a result of high current density. In addition, the inhomogeneous CaH2 layer formation can also lead to the formation of localized 'hot spots', which can induce unexpected dendrite formation at lower current densities. Two papers based on this chapter, 'Liquid cell transmission electron microscopy and its applications' and 'Current-density-dependent electroplating in Ca electrolytes: From globules to dendrites', has been published in 'Royal Society open science' and 'ACS Energy Letters'.

Among the technologies being researched for grid-scale electricity storage, pumped thermal energy storage consists of storing electricity as thermal energy, with the conversions being done by a reversible heat pump/heat engine system. Advantages include the use of abundant and cheap materials, conventional components from the power industry, as well as full flexibility in siting. Various thermodynamic cycles can be used for the energy conversion, including the Joule-Brayton, transcritical, and glide (also known as Kalina) cycles. The latter has not been extensively studied yet for PTES and is the focus of the present work. Akin to a Rankine cycle, it differs by employing a zeotropic mixture for the working fluid. As a result, evaporation and condensation occur non-isothermally over a temperature "glide", making this cycle a good match for sensible heat storage. The mixture used for the working fluid must be chosen carefully. Its effective heat capacity during phase change (a well defined property due to the temperature glide) can exhibit extremely high variability, which would incur substantial pinch-point problems and thus inefficiency in the heat transfer processes integral to PTES. In the present work, an alkane mixture is therefore optimised to achieve near-constant heat capacity. This alkane mixture is then used as the working fluid in a model of a low temperature glide cycle that uses water for both the hot and cold stores. Despite the low temperatures involved, the computed cycle round-trip efficiency reaches roughly 55% under realistic assumptions for isentropic efficiency and heat exchanger effectiveness. This is largely due to the efficient heat transfer enabled by optimising the working fluid. Energy density is relatively low at 2.2 kWh.m⁻³ compared to other PTES cycles, though still several times higher than for pumped hydro storage. Capital cost is estimated at 15-45 $/kWhe for the specific energy cost and 1300-2900 $/kW for the specific power cost, making this competitive with batteries for long duration storage even under conservative assumptions. Capital cost is then investigated further in order to analyse the physical drivers of cost in PTES systems in general, both in terms of power and energy. The nature of the working fluid influences the specific power cost via the turbomachinery as well as the heat exchangers. Operating conditions like pressure and temperature also have a major effect; in particular, increasing temperature lowers the heat-to-work ratio of the cycle and therefore lowers heat exchanger cost, although beyond a certain point material limits force a switch to more expensive materials and cause a discrete jump in cost. In order to improve efficiency, energy density, and potentially reduce cost, a higher temperature glide cycle is then modelled, after the optimisation of a new working fluid mixture. To that end, many fluids are examined according to several criteria, before deciding on a final mixture that is also based on alkanes. Pressurised water is used for the hot store at up to 180 °C while unpressurised water is again used for the cold store. Performance is characterised by parametric studies which suggest round-trip efficiency can reach 60%, with an energy density of around 5 kWh.m⁻³. The specific power cost is (conservatively) estimated at 1600 $/kW, an improvement on the low-temperature cycle thanks to the lower heat-to-work ratio. However, the specific energy cost is higher at around 120 $/kWhe, due to the expense of the pressure vessel for the hot store. Consequently, the PTES plant's storage duration determines which of the low and high temperature glide is most cost-effective.

Lithium-oxygen batteries (LOBs) have attracted immense research interest as they have the highest theoretical energy density among the advanced battery systems. Achieving such high energy densities can substantially reduce the need for fossil fuels, enable greater use of renewable energy, and revolutionise the transportation sector. However, due to the complexity of oxygen reduction and evolution reaction chemistries and reactivity of reduced oxygen species, LOBs still need significant improvement in their fundamental understanding to overcome the electrolyte and cathode stability issues. In the Thesis, firstly, the redox mediated charging process was studied to understand the mechanism to enable fast charging with low overpotentials and side reactions. It is demonstrated that the redox mediated oxidation follows Marcus theory of electron transfer and the rate limiting step is the first 1-electron oxidation, Li₂O₂ → Li-O₂. The kinetically dominant step is the Li-O₂ disproportionation. It is also shown that the singlet oxygen (¹O₂) yield does not correlate with the amount of degradation. This casts doubt on whether ¹O₂ is the main cause of degradation in LOBs. Secondly, due to the discrepancy in ¹O₂ and electrolyte degradation amounts, the stability of the common LOB salts and solvents towards ¹O₂ were tested. It is shown that tetraglyme-LiTFSI, one of the most widely used electrolytes, is stable towards ¹O₂ under chemical conditions. In the LOB literature, ¹O₂ is mainly detected and quantified using DMA, a ¹O₂ trap. Here, it is revealed that DMA can react with superoxide depending on the salt-solvent combination and DMAO₂, the reaction product of ¹O₂ with DMA, can degrade into by-products depending on the solvent environment. Finally, the stability of the electrolyte and the cathode towards ¹O₂ under electrochemical conditions and the real cause of faradaic efficiency loss are investigated. It is demonstrated that ¹O₂ is not the main source of degradation and fresh Li₂O₂ surfaces is the culprit. This finding should redirect the focus of LOB research from avoiding ¹O₂ to developing electrolytes inert towards peroxide and peroxide-derived side products for an electro/chemically stable cell.

Disastrous events, especially under extreme weather conditions, have severe impact on the resilience of electrical power systems. A power system should be reliable under normal circumstances and resilient to extreme events. To improve the resilience of a power system, infrastructural strategies ought to be devised to boost robustness, and operational strategies upgraded to improve the system's flexibility. The battery energy storage system (BESS) is one potential operational strategy to boost the resilience of a power system. This project aims to assess the contribution of BESS to the resilience of power systems under extreme weather events, especially via modelling of BESS utilization. In order to apply BESS analysis, a BESS modelling framework is proposed, taking reliability of battery cells and capacity fading of BESS into consideration. Case studies based on the modelling are performed to identify how BESS can improve reliability and resilience of a power system. Increasing numbers of BESS are planned to be installed in power systems around the world. Therefore, the locations to install BESS has become a prominent challenge to BESS utilization, given that an appropriate location of BESS installation will enable it to support not only the installation site, but surrounding network nodes. This project also develops assessments on location selection of BESS, as based on case studies. The performance of BESS to boost the resilience of a power system appears to vary with its installation locations. Therefore, in order to determine the appropriate locations to install BESS into a network, a 3-step dispatching procedure using an ELECTRE based multi-criteria decision analysis (MCDA) is proposed to effectively identify locations and amount of BESS to be installed into a network. This prediction is based on the capacity of the BESS in question and the features (topology, demand and fragility) of the network. Moreover, optimization of BESS utilization is taken into consideration. A better discharging profile improves the performance of BESS. Thus, this project develops case studies to analyse the optimization of BESS discharging, aiming to improve the resilience of a power system. Then, particle swarm optimization and Q-learning are tested for optimization of BESS control. A specific Q-learning algorithm is proposed to control BESS discharge. The proposed Q-learning optimization procedure is helpful with regards to reliability and resilience improvement of different power systems for BESS control. The final proposed 3-step BESS location selection procedure expands state-of-the-art research by introducing a new BESS dispatching method that provides an ELECTRE MCDA with an objective entropy weighting method. Conditional value at risk of energy not supplied (ENS) is also taken into consideration which enable the system operator to dispatch the BESS into a power system while considering both the amount of BESS and the power loss under extreme situation based on different confident level settings. The proposed Q-learning procedure is proved to be time efficient and able to improve the resilience of different power systems.

Chile has set ambitious targets to reach 100% renewable generation in the electric system and supply 80% of its heating with sustainable sources by 2050. The fulfilment of these goals brings new challenges for balancing supply and demand and creates the need for providing the energy networks with operational flexibility from new sources. Thermal energy storage arises as an option that can provide part of this flexibility, decoupling supply and demand by time-shifting power delivery at a competitive cost and with fewer geographical limitations compared to other storage technologies. Although Chilean energy policy has recently turned its attention on these issues, there is still a lack of technical input for assessing the potential of thermal energy storage to support the deployment of renewables in the electric grid and for cleaning heating supply. This thesis aims to bridge that gap and focuses on assessing how different thermal energy storage technologies can help to increase the share of intermittent renewables in the Chilean electric grid and in its residential heating sector. This is performed through techno-economic optimisation of the design and operation of specific thermal energy storage systems configurations. In the case of the electric grid, a linear optimisation model of the Chilean network is developed. The long-term impact of pumped thermal energy storage on the total system's cost is assessed. Among the main findings, it is concluded that the integration of on-grid 8h capacity storage increases the solar photovoltaic fraction, which leads to reductions in operation and investment costs by 2050. For the residential heating sector, a solar district heating network supported by borehole seasonal thermal storage is proposed as a clean alternative for heating in southern Chile. A simulation-based multi-objective optimisation of the system's design is performed, focusing on minimising cost and emissions. The results show that this system can be cost-competitive with some conventional heating technologies under specific circumstances. The presence of seasonal thermal storage helps drive down the total emissions by reducing the use of the auxiliary gas heater in winter. Finally, the solar district heating network is combined with a heat pump, and the effect of the power-to-heat scheme supported by short and long-term storage is assessed. It is found that despite the positive impact on cost and emission of the heat pump integration under the proposed configuration, fast charging thermal storage technologies may be better suited to integrate the heat supplied by the heat pump than the slower charging borehole storage. Additionally, by combining the previously developed models, it is established that the flexibility of the electric demand of a heat pump collocated with thermal storage decreases the strain on the electricity system expansion compared with inflexible demand. The findings reported in this thesis set the ground for further research, potentially using more detailed models and assessing other thermal storage technologies to highlight their value and encourage the use of thermal energy storage to assist the Chilean energy transition. Furthermore, these tools and analyses could be applied to other countries and areas following similar energy transition pathways.

Redox flow batteries (RFBs) with their decoupled power and capacity scaling are a promising energy storage technology. However, low energy density and high capital costs stymy such systems. For this reason, novel electrolytes are under active development. Previous electrolytes have involved a variety of metal-containing and organic systems. Organic systems can offer fast kinetics, high tunability and low cost. In this thesis, novel quinone derivatives were synthesised and investigated as potential electrolytes for organic aqueous RFBs. The first research chapter presents an investigation of quinones functionalised with aryl amines. 2,5-bis(4-carboxyanilino)-benzo-1,4-quinone was found to be the most promising example, retaining its electrochemical activity after reacting with hydroxide ions, the resultant molecule showing greater stability and reacting at a lower potential. Using NMR and EPR spectroscopy, insights into the charge delocalisation and chemical reactions of the molecule under battery operation were gained. The important conclusion from this study is that conjugate addition is not always detrimental. The next chapter involved screening several vanillin-derived quinones for potential viability for RFB use. Several candidates were synthesised and characterised and a flow battery based on 2,5-bis((methyl)aminoethanol)-benzo-1,4-quinone was constructed. These electrolytes were shown to be promising and chemically versatile, but solubility is still a major problem that will limit their application. The final research chapter explored several heteroaromatic quinones derived from tetra-amino-benzoquinone. Aqueous electrochemical characterisation was carried out and the most promising candidate, bis-triazolo-benzoquinone, was used as an anolyte in basic aqueous media. In situ spectroscopy was used to gain insight into the behaviour of the molecule under battery operation. Fused quinone systems of this type may be promising electrolytes but problems associated with solubility and long-term cycling are yet to be overcome. Overall, the thesis has (i) developed new protocols for the synthesis and derivatisation of important families of novel electrolytes for RFBs (based on simple chemical routes), (ii) introduced new methodologies for benchmarking electrolyte electrochemical performance, and (iii) exposed the compromise between solubilising and electrochemical functionality as a primary future challenge for organic RFB electrolyte development.

Suitably cost-effective energy storage will aid in the migration to a low carbon global energy economy. In an attempt to access such technology, recent years have seen a great deal of research into enabling a step change in the performance of lithium-ion batteries. One perceived route to achieving this is an all-solid-state battery, in which the flammable liquid electrolyte used in commercial battery technologies is replaced with a solid that has a high lithium-ion conductivity. Such batteries may have improved energy density and reliability as compared to the current state-of-the-art. Optimising the properties of these solid-electrolytes for successful incorporation into a battery cell has proved challenging, and a commercially viable all-solid cell has yet to be produced. Within this thesis, we argue for a full understanding of point defect chemistry to learn more about the performance and properties of crystalline solid electrolytes. In doing so we discuss these solid-state ionic materials through the lens of semiconductor defect chemistry, highlighting the importance of considering the coupling between defect populations via the electronic chemical potential, or rather the Fermi energy. We show how perturbations to the Fermi energy (facilitated by aliovalent doping) affect the concentrations of all charged defects in the system, questioning the validity of the commonly held assumption that the charge imbalance introduced by aliovalent dopants is compensated by changing concentrations of mobile-ion defects. This leads to potential difficulties in assigning a simple composition-property relationships. This approach reveals that the lithium-ion conductor Li3OCl is, from a defect chemistry perspective, a somewhat poor candidate solid electrolyte and that the garnet ion conductor Li7La3Zr2O12 (LLZO) has a more complex than previously considered doping response. We then build on this model to examine electronic carrier populations in LLZO, discussing possible non-negligible electronic conductivity, which has been linked to battery failure owing to a bulk lithium reduction process. Finally, we explicitly consider dopant-driven changes in defect–host-framework interactions which result in modulations to the potential energy surface for lithium ion transport in the superionic conductor Li10GeP2 S12. To close, we briefly discuss the practical and theoretical challenges posed by modelling the point defect chemistry of solid electrolytes more fully. It is hoped that this work will inspire more considerations of the equivalence between a picture of defect chemistry in functional materials that invokes charge-neutral defect reactions and one which considers a system where the concentrations of all charged defects are coupled.

Flexible and stretchable energy storage devices have attracted significant attention of industry and academia. These devices show great potential for applications in wearable electronics or soft robotics. However, the fabrication of flexible and stretchable electronic devices such as supercapacitors is challenging and requires expensive and time-demanding processes. Additive manufacturing has become one of the most attractive techniques for building bespoke devices. In this regard, 3D-printing has emerged as an extrusion-based method for an accurate rapid prototyping. Here, we propose a combined method of 3D-printing and laser-scribing to fabricate flexible and stretchable supercapacitors. The developed technique consists of the synthesis of the required materials, as well as the manufacturing processes of each part of a flexible supercapacitor. The components of the supercapacitor such as the conductive current collectors, electroactive material, gel electrolyte, as well as the housing encasement were successfully attained. The integration of the parts to obtain a complete flexible energy storage device was successfully achieved by investigating the interactions of the developed materials in contact. The obtained flexible energy storage device presents an areal capacitance of 2.3 F cm-2, excellent cycling stability (97% retention after 10.000 cycles). Also the developed supercapacitor prototype can deliver a high energy density of 0.21 mWh cm-2 and a maximum power density of 39 mW cm-2 making it competitive compared with similar micro-supercapacitors reported to date. In addition, the manufactured devices kept its remarkable capacitance properties while being bent and stretched. It is envisaged that these precisely controlled software processes could be easily integrated in a production line with determined manufacturing times and keeping the resulting devices with their remarkable electrochemical performance. All the rapid protoytping manufacturing processes were accomplished by affordable commercial 3D printers and laser scribers. The attained integration results pave the way towards automated fabrication processes of flexible energy storage devices with industrial and academic applications.

The energy industry is quickly changing, with more renewable energy technologies emerging and sustainable sources growing in their capacities, which is slowly reducing the need for fossil fuel sourced energy supply. But with it come challenges, with energy storage becoming increasingly more important to help balance the gap between the energy supply and demand. The interest in hydrogen has accelerated in recent years as it can be used for several end uses, for example power-to-power, power-to-gas and power-to-fuel. It could therefore potentially decarbonise several industries, not just the energy sector. For hydrogen produced by renewables through water electrolysis to become competitive, the issues of low roundtrip efficiencies, high costs and the need of scaling up a new infrastructure needs to be addressed. This research project is a collaboration between University of Edinburgh and Bright Green Hydrogen (BGH). BGH is a non-for-profit company that created and launched the Levenmouth Community Energy Project (LCEP) in 2014 (operational from 2017) to explore electrolytic hydrogen's ability to decarbonise energy supplies. The LCEP consists of: 750 kW wind turbine, 48 kW roof PV, 112 kW ground PV, 250 kW PEM electrolyser, 100 kW PEM fuel cell, two 60 kW hydrogen refuellers and a total of 17 hydrogen vehicles of three different models. This project used the data, information and observations from the LCEP to build an energy system model that included hydrogen with real-world aspects. The model was used to explore different ways that the economics and self-reliance for energy of small-scale hydrogen systems can be improved by conducting a techno-economic analysis on a number of alterations. The electrolyser control system was improved to help the electrolyser behave more energy efficiently, components were changed in sizing and a Lithium-ion battery was added into the model to help optimising the main electrolyser's performance. The first novelty of this work was a new electrolyser model that was developed specifically to account for energy consumption and hydrogen production at low load, which appeared frequent and significant in this type of system. The model was found to represent the plant data better than existing ones. One general conclusion from this work was the impact of operation at low load, which is difficult to avoid at all times and yet should be minimised for good technical and economic performance. The second contribution to knowledge in this work is the methods and findings of the technoeconomic assessment. Several possible improvements were explored to find a balance in techno-economic performance of the small-scale hydrogen production facility. It was found that a control system that made adequate use of forecast weather and energy supply data was critical for effective and efficient use of the electrolyser, without excessive shutdown time and parasitic loss at times of low energy supply. In addition, changes in the respective capacities of the components (electrolyser, storage, solar energy supply) for the same demand could result in significant improvements in economic performance, and so could the incorporation of batteries within the system in support of the electrolyser. Batteries helped both electrolyser standby load (to help with grid independence) and hydrogen production (to improve electrolyser's output). However, there is a balance between battery storage size and system benefits. In the particular case of the LCEP as built, the system struggled to perform well while it had two end uses (energy storage for buildings and fuel for vehicles) without more energy and hydrogen supply. Also, the main electrolyser was oversized for its needs, resulting in poor capacity utilization and high parasitic load. But a significantly smaller electrolyser with sufficient storage had a notable technical benefit to the system. Finally, there were several adjustments that could lead to a technically well-performing smallscale hydrogen system, but none that made it economically feasible. Capital costs, operating costs, maintenance costs, major replacement costs and durability of components are still major factors that need to be addressed for hydrogen at this scale to be feasible. However, this work clearly identified required areas of progress to achieve economic viability without subsidies, in particular, improving the longevity of the electrolyser and fuel cell stacks would alone enable a positive Net Present Value. In addition, recent and ambitious policy decisions and more widely deployed demonstration projects can stimulate volumes of productions of these components, and the significant cost reductions that these would allow.

Electrical power is essential to modern society, and is necessary for innumerable applications from lighting, heating, household appliances, to large-scale machinery, communication and transportation. Ensuring a reliable, efficient and sustainable electrical power system is therefore crucial. At present, the generation, transmission and distribution of electrical power is being rapidly transformed by advances in technology and sustainability initiatives. Some of the most important new trends include: an increasing amount of distributed generation; widespread use of power electronic converters for generation, energy storage, and loads; and increasing use of DC transmission, forming hybrid AC/DC networks. This raises new challenges and opportunities for the power system, particularly in terms of its control and optimization. In this thesis, we will consider some of these challenges for the control and optimization of contemporary and future power systems, focussing especially on hybrid AC/DC networks and converter-based microgrids. Hybrid AC/DC networks are an effective solution for future power systems, due to the increasing number of converter-based loads and distributed energy resources. The hybrid AC/DC network allows the advantages of both AC and DC networks to be combined. By using high-efficiency converters to connect the AC and DC grids, the overall efficiency of the network can be improved. However, the interconnection of AC and DC networks via interlinking converters (ILCs) to form a hybrid network brings new technological challenges, one key area being the control of such a network. The network, and especially the interlinking converter, must be controlled to ensure that the DC and AC subsystems coordinate to stabilize the network and allocate power appropriately. This is an area which has attracted considerable recent interest due to the non-triviality of the control design. In this thesis, we discuss two main contributions to the literature on hybrid AC/DC networks: the first is to present primary and distributed secondary control schemes for hybrid AC/DC networks. Using a simple model for the interlinking converter, valid for slower timescales, we prove stability and optimality. We demonstrate our proposed controllers with realistic simulations, and show improved transient performance and more accurate power allocation compared to the traditional dual-droop approach. The second part of our work considers dynamic models of the ILCs for slightly faster timescales, and proposes a passivity framework for hybrid AC/DC grids. The use of passivity allows the derivation of decentralized conditions through which the stability of the network can be guaranteed. We discuss how an appropriate ILC control design can facilitate an appropriate power allocation in the network and demonstrate the proposed design with advanced simulations. The second major area of interest is converter-based AC microgrids. Distributed generation and battery storage are being integrated into the power network at an increasing rate, and these are connected to the network via power converters. To enhance efficiency and reliability, it is envisioned that distributed generation, storage and loads will form microgrids which are able to operate autonomously if necessary. Autonomous operation poses challenges in terms of frequency and voltage regulation, requiring grid-forming inverters to coordinate the regulation of the frequency and voltage. A further challenge is to achieve an appropriate steady-state power allocation between multiple sources in the network. This thesis presents several contributions in this area. Firstly, we present a passivity framework to obtain decentralized conditions for assuring stability, and consider its applicability to grid-forming inverter control schemes in the literature. Taking existing control schemes, we assess their passivity properties numerically and discuss how these can be improved. We then design a state feedback controller which: satisfies the passivity condition for stability; allows disturbances and load changes to be regulated by contributions from multiple inverters; and allows a wide range of performance specifications to be achieved. Again, realistic simulations are used to demonstrate the proposed control approach. We also demonstrate that the passivity framework is applicable for general resistive-inductive-capacitive models of the transmission lines with an arbitrary number of states and length-varying parameters. We then present work on optimizing low voltage distribution networks with controllable battery energy storage. This is a highly relevant problem as distribution networks around the world are experiencing an uptake of energy storage systems. The proposed formulation in this chapter allows the incorporation of various important features that have not been addressed in the literature. Previous literature on convexified optimal power flow had not investigated the case of unbalanced distribution networks, especially regarding unbalance constraints, power loss in the neutral wire, and meshed network configurations. These effects are practically important in many distribution networks but existing methods were not able to incorporate this into a convex formulation. The proposed method is then used to demonstrate optimized dispatch of energy storage systems in a suitable four-wire unbalanced distribution test network. All our analytical results are network independent and have been verified with realistic case studies in MATLAB/Simulink.

To ensure lithium-ion batteries are reliable in terms of lifetime and performance, a detailed understanding of their ageing behaviour is essential. Models that predict battery lifetime require knowledge of the causes of degradation and operating conditions that accelerate it. Batteries experience two ageing modes: calendar ageing at rest and cyclic ageing during the passage of current. Existing empirical ageing models treat these as independent, but degradation may be sensitive to their order and periodicity - a phenomenon known as "path dependence". This empirical study investigates whether interactions between ageing modes can impact the rate of degradation. Eight groups of graphite/NCA 18650 lithium-ion cells were exposed to load profiles consisting of the same ratio of calendar and cyclic ageing applied in various orders. The profiles incorporate different C-rates, cycling methods and calendar ageing conditions, to gain insight into the conditions that encourage path dependent ageing. The data collected indicates that under certain conditions cells exposed to the same amount of calendar/cyclic ageing, but in different orders, can lead to a difference in degradation trends. The divergence in degradation rates is more pronounced when constant current cycling at higher C-rates and is limited when constant voltage steps are incorporated during cycling. Comparing the rate of degradation experienced by cells exposed to combined load profiles versus the degradation predicted using the cumulative empirical model indicates that the cumulative model underestimates the cell lifetime. These findings suggest that including the possible coupling between calendar and cyclic ageing modes can improve the accuracy of lifetime predictions.

Supercapacitors have seen significant study as an additional electrochemical energy storage technology. Due in large part to their high specific power, they have seen growing application for rapid energy storage, or for the delivery of large bursts of power in a short amount of time. However, there is still a desire to enhance their specific energy without sacrificing that specific power. In this work, the synthesis and novel use of activated carbon spheres between 300 and 400 nm with an exceptionally high specific surface area of 2972 m2/g were used as electrode materials for supercapacitors. When this material was used in an aqueous symmetric device, specific energies of up to 10.59 Wh/kg were obtained at a high specific power of 5.15 kW/kg. This performance was achieved with less than 1% capacitance loss over 10,000 galvanostatic charge-discharge cycles. Finally, a novel and facile electrodeposition of manganese oxide using potassium permanganate solution was described. The technique was found to have a high degree of uniformity in deposition, and the ability to tune the thickness of the deposition layer. The manganese oxide deposited was characterised using a range of techniques and found to behave closely to that of birnessite-type manganese oxide. When deposited onto electrodes with activated carbon spheres, the manganese oxide layer conformed to the spherical surface well. These activated carbon sphere-manganese oxide core-shell electrodes were used in asymmetric two-electrode pseudocapacitors where a specific energy of 5.24 Wh/kg at a specific power of 819 W/kg was achieved.

To avoid driving climate change on a dangerous path, a substantial reduction in greenhouse gases emissions is required. Hence, a high penetration of renewable energy technologies is essential, but most renewables are either affordable or dispatchable but not both. Energy storage systems integrated into concentrating solar power (CSP) plants can enhance dispatchability and solar-to-electricity efficiency. Besides, the combination of dispatchable CSP plants with lower cost photovoltaic (PV) plants exploits synergies between the reliability of CSP with energy storage and cost of PV. However, this integration leads to complex interactions between the different technologies and requires sophisticated design guidelines to achieve low costs and high dispatchability simultaneously. In this thesis, a two-stage multi-objective optimisation framework for the design and operation of hybrid CSP-PV plants with energy storage is developed. The two-stage optimisation simultaneously optimises the design and operation of a hybrid solar power plant with respect to competing technical and financial performances. The multi-objective operational optimisation stage finds the best operational strategy of a hybrid power plant with energy storage systems. The model, written in Python, uses a typical meteorological year to optimise one-year hourly operation. The results demonstrate that the integration of an energy storage system in a concentrating solar power plant provides dispatchability and, when hybridised with photovoltaic, enhances its competitiveness with current electricity prices. The low mismatch between supply and demand, even when a fixed commitment is required throughout the year, together with high overall efficiency, indicates that the integration of energy storage in hybrid solar power plants is an opportunity to increase the penetration of solar energy in the power sector. The design of reliable and cost-competitive hybrid solar power plants requires the careful balancing of trade-offs between financial and technical performance. Hence, the design optimisation stage optimises the capacities of the main components of the hybrid power plant and handles financial and technical objectives. Different configurations are analysed as case studies throughout the thesis to analyse the impacts, interactions, and synergies of technology integration. Three locations are investigated, which present different solar resource profiles: Seville (Spain), Tonopah (USA), and the Atacama Desert (Chile). The optimisation results are used to develop some guidelines for the optimal design of dispatchable hybrid solar power plants with energy storage based on the given solar resource and required dispatchability. These guidelines provide an initial design for affordable and dispatchable hybrid solar power plants and can enable their widespread deployment. The model developed can be applied to other locations under different input parameters and demand profiles. Besides, the flexibility of the model allows it to be extended in order to evaluate different energy conversion and storage technologies to design hybrid power plants with energy storage under different configurations and requirements. Thus, the optimisation framework can provide valuable information for the integration of different technologies to support the affordable and sustainable transition to a clean energy system.

Currently, fossil fuels make up a significant proportion of global energy demand and cause many concerns, such as increasing greenhouse gas emission. Therefore, there is a considerable need for cost-effective, facile and efficient processing of environmental-friendly energy harvesting and storage systems. Solar energy is one of the most promising energy sources that meet the energy demand. The silicon-based solar cells exhibit competitive power conversion efficiency and dominate the solar cell market in recent years. In contrast, organic solar cells (OSCs) have emerged as promising third-generation photovoltaic devices owing to their outstanding properties such as the potential of low-cost mass manufacturing, lightweight, mechanical flexibility and easy processability. Therefore, OSCs have received growing attention from the research community. For solar cell technologies, a smectic liquid crystal C8-BTBT was selected in Chapter 3 due to its unique thermal dynamic and crystal properties. A range of ternary OSCs with and without C8-BTBT loading at gradient weight fractions were thermally treated and fabricated. In addition, the assessment of fabricated OSCs on the photovoltaic characteristics reveals the evolution of various cell parameters with annealing temperature and C8-BTBT weight fractions. The cell with 5 wt% C8-BTBT loading exhibited the best performance after thermal annealing treatment at 120 oC. Furthermore, flexible hydrogel substrates were fabricated for flexible OSCs in Chapter 4. The PHEMA hydrogel films were optimised via adjusting photopolymerisation duration under UV light. Based on the fabricated PHEMA substrates, flexible OSCs were subsequently made, whose extracted device parameters showed comparable characteristics with those in Chapter 3. Moreover, PHEMA-based OSCs can be dissolved in different types of polar solvents, which is promising for realising sustainable and recyclable solar cells. For the development of energy storage devices, asymmetric carbon nanohorns were proposed as an active material to fabricate flexible solid‐state carbon wire (CW)‐based electrochemical supercapacitors (ss‐CWECs) which exhibited high power density and ultra‐low cutoff frequency. Based on microscopy and electrochemical characterisation, the fundamental reaction mechanism in polyvinyl‐based electrolyte system was elucidated in Chapter 5, as being associated with deprotonation reaction under the acid, base, and elevated temperature conditions. In Chapter 6, by using activated carbon, multi‐walled carbon nanotubes, and single‐wall carbon nanohorns as hybrid electrode materials (5:1:1), remarkable specific length capacitance of 48.76 mF cm−1 and charge-discharge stability (over 2000 times cycles) of ss‐CWECs were demonstrated, which are the highest reported to date. Furthermore, a high‐pass filter for eliminating ultra‐low electronic noise was demonstrated, enabling an optical Morse Code communication system to be operated. vThe collective works in this thesis demonstrate novel energy conversion and storage applications with the liquid crystal in OSCs and carbon nanoparticles in supercapacitors. These results provide a step forwards in the development of energy conversion and storage devices for a more efficient energy system.

More energy dense lithium ion batteries are essential for the production of long-range electric vehicles and all-electric aircraft. These next generation batteries will require high capacity cath- ode materials that move beyond the lithium intercalation chemistry of current electrodes. On paper, transition metal fluorides are among the most promising cathode materials, combining high electrode potentials (2.6 V to 3.5 V vs. Li+/Li) with three to six times the theoretical capacity of conventional cathode materials. However, their commercial application has been hindered by their inability to cycle in a truly energy dense format (i.e. at high active material concentra- tion) and ultimately the inadequate understanding of their electrochemical capabilities and limitations. Both of these issues have been largely resolved as a result of this DPhil project. First I design a materials system that is practically ideal for reversible high-capacity cycling as well as detailed mechanistic study. This is achieved through the development of a new colloidal synthesis method for single-crystalline, monodisperse transition metal fluoride (FeF2, CoF2) nanorods. Size and shape control are demonstrated, and a chemical reaction pathway and nu- cleation and growth mechanism are proposed. Next I present an ionic liquid electrolyte (1 molal lithium bis(fluorosulfonyl)imide in N-methyl-N-propylpyrrolidinium bis(fluorosulfonyl)imide) that forms a stable solid electrolyte interphase, prevents the fusing of particles, and consequently precludes the major failure mechanisms associated with transition metal fluoride cathodes. The use of this electrolyte with the iron(II) fluoride (FeF2) nanorod system results in near theoretical capacity (570 mA h g−1) on discharge and charge, with extraordinarily stable cycling (>90% ca- pacity retention after 100 cycles). This stability is maintained for over 200 cycles at relatively high cycling rates (C/2) and temperatures (50 ◦C). By combining the unique vantage point afforded by this novel materials system with the morphology preserving qualities of our new electrolyte, I am further able to characterize the discharge/charge mechanism with an unprecedented level of detail. High-resolution analytical transmission electron microscopy reveals intricate morphological features, lattice orientation relationships, and oxidation state changes that that provide a new and comprehensive understanding of the discharge/charge (conversion) reaction mechanism. This new mechanistic understanding defines the structural and chemical origins of reversible cycling and cell failure in transition metal fluorides and unearths new concepts such as an inherently high discharge rate capability in FeF2.

Multi-material, multi-technology (MMMT) manufacturing systems combine or hybridize the benefits of individual fabrication and characterization techniques into a single manufacturing platform. In particular MMMT systems based on additive manufacturing (AM) technologies offer new opportunities for increased design freedom and additional functionality. However, the realization of the potential of AM-based MMMT systems is held back by the lack of accessible, affordable and reconfigurable hybrid-AM systems. In this thesis, a novel, extendable hybrid-AM framework/concept is introduced. A corresponding, modular machine has been designed and built from the bottom-up. Detailed insights into the design considerations, operating principles, associated digital workflows and potential applications are discussed. The machine provided design freedom and in-line functionality previously unachievable. These aspects are then demonstrated through the: (1) AM of functional, form-factor free energy storage devices (supercapacitors, EDLC’s) in a single, automated multi-material operation; and (2) measurement of a material property distribution (the local dielectric permittivity (εr) in 3D) within printed parts as they are being formed. Careful consideration was given to the underlying materials- and AM processing-science. The supercapacitor behaviour was assessed through a range of electro-chemical and other characterization techniques, and provided encouraging energy storage behaviour. A ring-shaped supercapacitor was fabricated in a single manufacturing operation, unachievable by conventional manufacturing. Non-destructive, in-line permittivity data was reconstructed into three dimensional (3D) dielectric “images” of a printed object, and techniques to understand and improve the spatial resolution are presented. The research aimed to accelerate the integration of functional devices in product manufacture (in particular for applications with irregular volume/shape and mass-customization requirements), accelerate the design-make-test cycle for functional devices through insight in device conformance to intended design (in-line quality control), and provide a versatile hybrid-AM environment for further research.

Decarbonisation of the electrical grid, necessitated by international targets to limit further global warming, will require a steadily increasing penetration of non-dispatchable intermittent renewable electricity generation sources. Energy storage has the potential to substantially increase the grid's ability to accept greater quantities of renewables while maintaining stability. Pumped-Heat Energy Storage (PHES) is a form of electrical energy storage targeted to provide storage on the order of days or weeks, as opposed to short durations of storage currently available through battery technologies. PHES systems could be utilised at substations across the country to help the grid endure diurnal load fluctuations and periods of low wind and solar resource. This system is based upon the Joule-Brayton cycle, which operates in the reverse direction to store exergy and the forward direction to generate electricity. An inert gas is the cycle working fluid, and a liquid is used to transfer heat to and from thermal exergy stores. Exergy is stored as temperature differences from ambient in balanced hot and cold stores. PHES development at the University of Edinburgh has iteratively explored different system architectures, and focused on increasing confidence in components within these architectures where there is uncertainty with regard to performance. Early work concentrated on gas-liquid mixing within the cylinder of a compressor/expander machine, while current work has eliminated such mixing and instead proposes the use of large scale, direct-contact heat exchangers. Such exchangers suffer from significant uncertainty for this application owing to the lack of existing experimental correlations with which to predict their behaviour at the proposed operating pressure and temperature. As a result, gas liquid surface interactions and heat-transfer between gas and liquid streams are largely unknown, hindering system development. Two experimental campaigns were conducted to verify components in both the early and current system iterations. The first demonstrated a novel in-cylinder gasliquid mixing device and quantified device behaviour against the no-mix condition. The second campaign demonstrated operation of a scaled pilot packed-column direct contact heat exchanger, where gas and liquid comingled to exchange heat. Existing experimental correlations for high pressure packed column flooding were verified against experimental results, and the overall heat exchange coefficient was calculated. Results were used to validate a finite volume heat transfer model based upon previous correlations. Successful gas-liquid heat exchange in the temperature and pressure range of interest was demonstrated, advancing PHES development and informing future iterations of the system.

Global warming is endangering the Earth's ecosystem. It is imperative for humanity to limit greenhouse gas emissions in order to combat rising global average temperatures. Demand-side management (DSM) schemes have widely been analysed in the context of the future smart grid. Often they are based on game-theoretic approaches to schedule the electricity consumption of its participants such that it results in small peak-to-average ratios (PAR) of the aggregated load. In order to guarantee high comfort levels for the consumer, we investigate DSM schemes on the basis of individually owned energy storage systems. The scheduling of these batteries is incentivised by a specific pricing function offered to the users. Within this thesis we cover various aspects for these type of management schemes. Firstly, we design a simple game-theoretic scheduling mechanism and analyse how the battery model, more specifically the round-trip efficiency, affects the outcome. From the simulations we find the importance of highly efficient energy storage systems for the engagement of participants. Secondly, the simple scheduling mechanism is replaced with a more advanced dynamic game, that models fine-grained control over the battery. For this novel game, we derive an analytical solution for the best response of a user, considerably speeding up the solution algorithm for the game. Furthermore, a comparison between the two games also shows the improvements in reducing the PAR of the aggregated load. Based on the augmented game, we investigate the resilience of the equilibrium solution with respect to inevitable real-world forecasting errors. One of the main findings of this thesis is reflected in the results showing the robustness of the schedules for a large number of simulated scenarios and even in the worst-case. Thirdly, we explicitly deal with the finite horizon effect that occurs due to the fixed time frame of the game mechanism. This eventually leads to a DSM system which results in a mean PAR of the aggregated load close to the optimum. Further studies show that these outcomes can be achieved due to the interaction of the households. Individual scheduling of batteries reduces the potential reduction of PAR and is especially detrimental for the robustness against forecasting errors. Fourthly, the developed model is analysed with respect to cyber-physical attacks. We develop a novel type of data-injection attack on the forecasted data and show their impact. After suggesting suitable monitoring strategies to the utility company, a game-theoretic model is employed to understand their decision making process. Finally, we investigate which battery size is optimal for such a DSM scheme. The respective experiments give insight into the different factors that determine the sizing of the battery. From the results we can infer that certain types of users only require a small scale battery system to achieve considerable gains. Overall, this thesis provides an in-depth analysis of a demand-side management scheme that can be employed by prosumers all around the world in the nearest future. Furthermore, the experiments give insights to utility companies to focus on community approaches and how they can mitigate potential cyber attacks.

The environmental imperative to achieve net-zero emissions quickly to minimise the rise in average global temperature rise due to global warming is clear. To achieve this, variable renewable energy (VRE) needs to substitute existing energy sources in the polluting sectors: electricity, heat, transport and industry. The integration of VRE sources to high levels of penetration however, is difficult: unlike most commodities, supply and demand must be in equilibrium at each moment in time, from the sub-second to inter-annual. This study quantifies the flexibility required by a power network to integrate additional VRE sources as a function of the magnitude and duration of the electrical energy storage required. The original energy storage requirement modelling tool (ESRMT) calculates: 1) the storage magnitude index (SMI), 2) the storage duration index (SDI) and 3) the storage size required. This quantifies the impact of VRE penetration, the mix of VRE sources and the application of other flexibility methods on the storage requirements. The ESRMT is used to consider locations in Japan, the UK, Canada and Australia and shows that, while requirements do increase with VRE penetration, the magnitude and type is location specific and highly dependent on the mix of VRE sources. Medium and long-term storage required at high VRE penetration are difficult to mitigate. The chemical storage of electrical energy, using ammonia, is a promising solution due to its favourable chemical and technical properties. The decarbonisation of the ammonia production is itself an environmental imperative as it accounts for 1.3% of global carbon dioxide emissions and supports over 48% of the global population through nitrogen based fertilisers. The developed islanded ammonia production modelling tool (IAPMT) optimises the mix of VRE sources, plant design and operation to minimise the levelised cost of ammonia (LCOA) at any given location. The IAPMT is used to consider ammonia production at 534 locations in 70 countries. It shows that at the best location a LCOA of $473/tonne is currently achievable, but this will decrease to $310/tonne by 2030. Decarbonised production will be highly competitive with conventional production by 2030. Assuming its use for seasonal storage, these LCOA estimates mean that the levelised cost of electricity (LCOE) of power-toammonia-to-power of $252/MWh by 2030.

Enhanced frequency inertial response has become an essential requirement requested by many grid transmission system operators around the world to support the frequency stability of power systems after sudden severe disturbance. With current regulations mandate to deploy more renewable generation resources, this prerequisite has become a necessity toward building new decarbonised power systems. Energy storage systems (such as a grid-scale battery energy system) have the advantage of storing energy and providing high power at a rapid rate, which is expected to meet this need. The research presented in this thesis demonstrates that the battery energy system can improve the dynamic response of the entire large grid. Therefore, it supports the integration of more renewable energy resources to meet the future energy scenarios that set by the British National Grid. The research develops and validates a model of a battery energy storage system for the use at a grid transmission level to support the frequency inertial response. This involves a comprehensive analysis and design of all the electro-mechanical-chemical models of such a system and analysing their impact on the power system overall frequency dynamics. The models were studied through preliminary tests by connecting the proposed developed system to large-scale power grid prototypes. An optimisation method was developed to search for best-required design variables that can improve the grid system frequency response to set points. Hence, the main contribution is the creation of optimisation methodology to calculate the correct optimised design variables for grid-scale battery energy storage to enhance the rate of change of frequency, provide frequency support and improve the overall power system dynamics. The key outcomes are: (i) design and test a preliminary model of grid-scale battery energy storage system with a set of controllers including inertia response controller that sup-port the frequency response; and (ii) develop an optimisation methodology to search for the optimal size and location of grid-scale energy storage system under different scenarios of operating conditions. Both outcomes have been verified and validated through several simulation cases.

There is a clear and urgent need for rechargeable batteries of higher energy density. Alkali-ion batteries based on Li-ions are the state-of-the-art, although Na-ion may offer a cheaper alternative. In both cases the cathode imposes the biggest limitation on overall energy density. Alkali-rich cathode materials can store alkali-ions and electrons densely by invoking redox chemistry of both the transition metal (TM) and oxide ions in the lattice. However, O-redox is accompanied by voltage hysteresis, irreversible O-loss and complex structural changes. In this thesis, model Na-ion materials have been investigated to isolate and examine these phenomena. Firstly, Na0.67[Mg0.28Mn0.72]O2, with Mg2+ ions occupying the TM layer rather than alkali-ions, is studied and shown to exhibit O-redox. This reveals that ionic interactions between the TM layer substituent and O are the necessary precondition for O-redox. Secondly, by comparing the O-loss behaviours of Na0.67[Mg0.28Mn0.72]O2 and Na0.75[Li0.25Mn0.75]O2, the critical role of the TM layer substituent is revealed; when removed from the structure, the co-ordination number around O can drop below three and O-loss is triggered. Unlike Li+, Mg2+ is retained within the structure preventing O-loss. Thirdly, O-redox materials Na0.75[Li0.25Mn0.75]O2 and Na0.6[Li0.2Mn0.8]O2 are studied in parallel to understand why the former exhibits voltage hysteresis and the latter not. The preservation of the TM layer ordering scheme is shown to prevent hysteresis maintaining stable electron holes on O2- in Na0.6[Li0.2Mn0.8]O2. For Na0.75[Li0.25Mn0.75]O2, severe in-plane TM migration destroys the ordering scheme, triggered by formation of molecular O2 gas which is directly evidenced for the first time in the bulk. Reduction of O2 occurs on discharge at low voltage giving rise to hysteresis. Finally, a new Li-rich oxyfluoride, Li2MnO2F, with a stable disordered rocksalt structure is presented. Li2MnO2F stores charge utilising both Mn and O-redox with negligible O-loss demonstrating the potential of disordered rocksalts to deliver high energy densities.

Pumped thermal energy storage (PTES) and liquid air energy storage (LAES) are two technologies that use mechanically-driven thermodynamic cycles to store electricity in the form of high-grade thermal energy, employing abundant materials that are kept in large insulated tanks. Both technologies are free from geographic constraints, providing a significant advantage over competing methods such as pumped hydro or compressed air energy storage. The focus of this thesis is on the analysis, modelling and development of these technologies. A number of PTES systems have been proposed based on different thermodynamic cycles. A variant based on the Joule-Brayton cycle employing liquid storage media is studied here. An analytical study is presented that reveals how the performance of the cycle varies along a range of operating conditions. Generally, the same strategies that minimise compression/expansion losses also maximise heat exchanger losses, which results in optimal points at certain operating conditions. A numerical model is developed to find these optima while accounting for real fluid properties. Employing a regenerative heat exchanger is found useful to adapt the cycle to the operating temperature ranges of the storage liquids and to increase the performance of the cycle. A new combined cycle that integrates PTES and LAES is presented. The fundamental advantage is that the cold thermal reservoirs that would be required by the separate cycles are replaced by a single heat exchanger that acts between them, thereby saving significant amounts of storage media per unit of energy stored. Several configurations are possible and these are studied and optimised. The most advanced configuration reaches a round-trip efficiency of 71 % under nominal conditions, compared to 65 % for stand-alone PTES and 61 % for LAES. A further adaptation of the combined cycle is presented which only employs water and liquid air as storage media, dramatically reducing the cost of energy capacity. The performance of the heat exchangers is found to have a significant impact on the overall performance of the various cycles. For this reason, an optimisation procedure is developed to obtain heat exchanger designs that minimise entropy generation for a given amount of material. These designs are used when estimating the costs of energy capacity and power capacity of each cycle. Results indicate that the best cycle configurations would be competitive with reported costs for pumped hydro and compressed air energy storage.

Electrical Energy Storage (EES) can decouple energy production from its consumption and is urgently needed by both conventional energy system for load leveling and renewable energy system for intermittency smoothing. Currently, Pumped Hydro Energy Storage (PHES) and Compressed Air Energy Storage (CAES) are the main technologies employed, but they both suffer from high capital cost, geographical constraints and environmental issues. Therefore, many innovative concepts of EES technologies have been proposed recently, including the Adiabatic Compressed Air Energy Storage (A-CAES), Pumped Thermal Energy Storage (PTES), Isothermal Compressed Air Energy Storage (I-CAES) and Liquid Air Energy Storage (LAES). All of these EES store electricity in the forms of thermal or mechanical energy, and are most suitable for large-scale energy storage. As a result, they have received intensive treatment from both the industry and academia, but a comparative study and optimization of these large-scale thermo-mechanical energy storage systems from a thermo-economic perspective has so far been lacking, which forms the major part of this thesis. In this thesis, a complete set of system models have been developed for each EES technology, incorporating both thermodynamic and economic factors with due consideration for the constraints and variation ranges of each parameter. Then parametric studies are carried out for each system to analyze the impact of each parameter on the system performance (e.g., efficiency and unit cost). Loss and cost distributions are given for the representative cases, and the detailed explanation and potential improvement are also provided. After that, thermoeconomic optimizations are carried out for each individual system, and the trade-off between efficiency and unit cost as well as the main factors controlling this trade-off are revealed. Finally, these optimized systems are compared with each other, and new EES systems that combined the merits of existing ones are proposed as well. The results show that A-CAES and I-CAES tend to have higher system efficiency and lower unit cost than PTES and LAES, but the PTES and LAES enjoys higher energy density and more siting freedom. More information about the component efficiency and cost is required for an accurate comparison between A-CAES and I-CAES, and between PTES and LAES.

Graphene is a promising material for supercapacitor electrodes, both in electric double layer capacitors and as a conductive support for incorporating materials with large pseudocapacitance, yet further development is still needed. Aerogels represent an attractive way to fabricate 3D grapehene structures with large and accessible surface areas and therefore useful for supercapacitor electrodes. Among the different methods available for aerogel production, freeze casting is a versatile technique, allowing good control of morphology. Freeze casting has therefore been applied to graphene-based materials, however most examples reported so far focus on using graphene oxide (GO) as the precursor material dispersed in water, which carries some inherent disadvantages in terms crystalline quality and processing conditions available. Using non-aqueous solvents which are solid at room temperature but can be easily melted upon heating enables sublimation under ambient conditions, making the process simpler and potentially more scalable. They also enable the use of other forms of graphene-based materials, e.g. pristine graphene sheets, which are difficult to disperse in water and reduce the need for further processing after solvent sublimation. This thesis therefore explores the fabrication of graphene-based aerogels using non-aqueous solvents and room temperature sublimation. Formation of aerogels utilising camphene as solvent and using different sources of graphene-related materials is presented, including six different commercial products and in-house produced GO. Aerogels utilising commercial graphene nanoplatelets, XG C750, as the graphene source achieved the highest specific capacitance, thanks to the source material's high starting surface area and ability to be effectively dispersed in the solvent. Successful fabrication of graphene-based aerogels is also demonstrated in five different solvent systems: camphene, menthol and phenol as single solvents, as well as mixtures of camphor with camphene and naphthalene. Menthol-based aerogels achieved the best overall performance in terms of surface area and capacitance, presenting a promising route for further exploration thanks to menthol's low toxicity and cost.

Proton Exchange Membrane Fuel Cell (PEM-FC) is a technology that is associated with three main challenges that can be summarised as cost, reliability and lifetime. Current global research in PEM-FC focuses on reducing the use of expensive precious materials to reduce costs. Research is also improving the way fuel cells internal subsystems (water management, thermal management, power conditioning unit, gas supply management) are being controlled, managed and operated to enhance reliability and lifetime. This thesis takes the FC research to a different level of abstraction to reduce FC internal degradation. The proposed work does not focus on current FC global research trends. Instead, it addresses the different fuel cell challenges by proposing new solutions to the external factors (dynamic of the load, battery size, etc.) affecting a FC during operation. The formulated thesis hypothesis is therefore: “ Reduce the FC internal degradation and address the above three FC challenges by looking at the overall FC system (FC, battery, DC/DC converter, load) and ignoring the FC internal subsystems and subcomponents (water, thermal management, power conditioning, gas supply management). This research differs from previous work as it does consider a FC as a black box and only work on how to better control external components that have a negative impact on the fuel cell durability. ” This research work proposed three main interrelated “antidotes” to address the PEM-FC premature failure, thereby reducing cost, reliability and lifetime issues: a) Development of an optimisation technique to size the intermediate battery buffer component within a fuel cell system. b) Devise a method to optimise the fuel cell electrical power output using the proposed double PID control system. c) Devise a method to optimise the fuel cells operation and reduce battery stresses using advanced predictive Artificial Intelligence (AI) technology. The outcome from this research work demonstrates how it is possible to reduce the fuel cell and battery degradation while feeding load requirements.

To achieve ambitious future environmental targets for aircraft set out by organisations such as NASA and the European Union, turboelectric distributed propulsion (TeDP) has been proposed as a novel concept that has the potential to achieve these targets by significantly improving integrated propulsion-airframe performance. Realising TeDP as a technology option brings into play a number of design and development challenges due to the highly integrated natured of TeDP-airframe configurations, low technology-readiness-levels of key enabling technologies and new modes of operation opened up by shift to a more electric architecture. In tackling these challenges a multidisciplinary and integrated method to assess the benefits and challenges of turboelectric and hybrid-electric propulsion system configurations by considering the effect of aircraft size, mission specifications, airframe, electrical system, energy storage, propulsor architecture and gas turbine architecture was created. The method created was used in the assessment of turboelectric and hybrid electric performance for a regional transport aircraft and a medium haul transport aircraft. For the regional role the employment of a DC hybrid superconducting turboelectric architecture managed to achieve 16.7% block fuel saving and 3.23% total energy consumption saving over a baseline turboprop aircraft at 600 n.mi range. Driving performance benefits was increased duration of mission time batteries spend discharging at relatively high battery power rating which overcomes weight penalties from installation of electric machinery. For medium haul role the employment of a geared hybrid electric architecture managed to achieve a 3.07% block fuel saving over a baseline turbofan aircraft at 900 n.mi range. Driving performance benefit for the mission was increased battery-operative-cruise time at relatively high battery power rating overcoming aircraft weight penalty and electric machinery installation weight penalty. Despite fuel burn reduction, hybrid electric aircraft consumes more energy than a baseline configuration primarily due to utilisation of additional energy from battery pack.

Structured electrodes with tailored nanoscale morphology and chemistry are highly desirable for a range of applications. In particular, emerging energy storage applications such as thick Lithium-ion battery (LIB) electrodes and photoanodes for watersplitting require new electrode structures that simultaneously optimise electron, ion, and thermal transport. In this PhD thesis, advanced structured electrodes are fabricated by creating 3D carbon-inorganic hybrid architectures. In this process, patterned vertically aligned carbon nanotubes (CNT) were used as the structural scaffolds to shape the electrodes while inheriting the excellent thermal and electrical properties of CNTs. First, UV and colloidal lithographic patterning processes were developed to create micro- and nanopores respectively within the CNT structures. Those structures provide high surface area and conductive backbone for the synthesis of hybrid CNT-inorganic structures. Specifically, the parameter space to create honeycomb shaped CNT structures with pores ranging from 300~nm to 30~$\mu$m has been established. Next, the micro-pore CNT structures have been chemically modified with iron oxide using microwave-assisted, hydrothermal synthesis for fabricating high areal loading LIB anodes. The areal loading was increased by 120\% compared to a standard battery film while at the same time retaining a high capacity (900 mAhg$^{-1}$ at 0.2 C). Then thick electrodes with optimised diffusion pathways were created by coating the nanopatterned CNTs with silicon using physical vapour deposition. These electrode structures are up to 50\% thicker than previously reported structures and still retain a stable capacity (650 mAhg$^{-1}$) and a good high-rate performance. Finally, the honeycomb shaped CNT structures have been coated with bismuth vanadate using a hotcasting process and the electrode architecture has been optimized for good conductivity by the addition of a Pd/Au layer between the CNTs and the BiVO$_{4}$. The photoelectrode performance was measured and shows a clear increase in current density when exposed to light. Each of these novel electrodes illustrate how patterning vertically aligned carbon nanotube structures combined with inorganic surface modification enables the creation of advanced electrodes with new formfactors and improved performance in comparison to literature and to classic drop-casted battery films of the same materials.

Lithium-ion batteries have transformed energy storage and technological applications. They stand poised to convert transportation from combustion to electric engines. The discharge/charge rate is a key parameter that determines battery power output and recharge time; typically, operation is on the timescale of hours but reducing this would improve existing applications and open up new possibilities. Conventionally, the rate at which a battery can operate has been improved by synthetic strategies to decrease the solid-state diffusion length of lithium ions by decreasing particle sizes down to the nanoscale. In this work, a different approach is taken toward next-generation high-power and fast charging lithium-ion battery electrode materials. The phenomenon of high-rate charge storage without nanostructuring is discovered in niobium oxide and the mechanism is explained in the context of the structure–property relationships of Nb2O5. Three polymorphs, T-Nb2O5, B-Nb2O5, and H-Nb2O5, take bronze-like, rutile-like, and crystallographic shear structures, respectively. The bronze and crystallographic shear compounds, with unique electrochemical properties, can be described as ordered, anion-deficient nonstoichiometric defect structures derived from ReO3. The lessons learned in niobia serve as a platform to identify other compounds with related structural motifs that apparently facilitate high-rate lithium insertion and extraction. This leads to the synthesis, characterisation, and electrochemical evaluation of the even more complicated composition–structure–property relationships in ternary TiO2–Nb2O5 and Nb2O5–WO3 phases. Advanced structural characterisation including multinuclear solid-state nuclear magnetic resonance spectroscopy, density functional theory, X-ray absorption spectroscopy, operando high-rate X-ray diffraction, and neutron diffraction is conducted throughout to understand the evolution of local and long-range atomic structure and changes in electronic states.

Since the late 1980s, the energy sector in Great Britain has undergone some core changes in its functionality; beginning with the early 1990s privatisation, followed by an increased green ambition, and commencing a transition towards a low-carbon economy. As the British energy sector prepares itself for another major overhaul, it also puts itself at risk for not being sufficiently prepared for the consequences this transition will have on the existing generating capacity, security of supply, and the national electricity market. Upon meeting existing targets, the government of the United Kingdom risks becoming complacent, putting energy regulation to the backseat and focusing on other regulatory tasks, while introducing cuts for thriving renewable and other low-carbon energy generating technologies. The government has implemented a variety of directives, initiatives, and policies that have sometimes been criticised due to their lack of clarity and potential overlap between energy and climate change directives. The government has introduced policies that aim to provide stable short-term solutions. However, a concrete way of resolving the energy trilemma and some of the long-term objectives and more importantly ways of achieving them are yet to be developed. This work builds on analysing each low-carbon technology individually by assessing its past and current state in the British energy mix. By accounting for the changes and progress the technology underwent in its journey towards becoming a part of the energy capacity in Great Britain, its impact on the future wholesale electricity prices is studied. Research covered in this thesis presents an assessment of the existing and incoming low-carbon technologies in Great Britain and their individual and combined impact on the future of British energy economics by studying their implications for the electricity market. The methodological framework presented here uses a cost-minimisation merit order model to provide useful insights for novel methods of electricity production and conventional thermal energy generation to aid with the aftermath of potential inadequate operational and fiscal flexibility. The thesis covers a variety of scenarios differing in renewable and thermal penetration and examines the impact of interconnection, energy storage, and demand side management on the British wholesale electricity prices. The implications of increasing low-carbon capacity in the British energy mix are examined and compared to similar developments across Europe. The analysis highlights that if the optimistic scenarios in terms of green energy installation are followed, there is sufficient energy supply, which results in renewable resources helping to keep the wholesale price of electricity down. However, if the desired capacity targets are not met, the lack of available supply could result in wholesale prices going up, especially in the case of a natural gas price increase. Although initially costly, the modernisation of the British grid leads to a long-term decrease in wholesale electricity prices and provides a greater degree of security of supply and flexibility for all market participants.

Mesoporous titanium oxide with a pore size of 20-30 Å was impregnated with conducting polythiophene nanowires in order to improve conductivity to take advantage of the ca. 1000 m2/g surface areas for possible applications in charge storage in devices requiring fast Li+ insertion kinetics. Pristine mesoporous titanium oxide produced a peak capacity of 301 mAh/g at current densities of 0.2 mA.cm-2 and 187 mAh/g at 1 mA.cm-2. The conductivity of the composite improved from 3.56 x 10-2 mS.cm-1 to 5.79 mS.cm-1 but significantly reduced capacity. This was attributed to pore blocking and a significant increase in the weight of the sample preventing Li+ diffusion into the pores of the material. An investigation of variation in polymer loading level and pore size using polypyrrole nanowires was then undertaken in order to improve performance. The best synthesis conditions were achieved using 5% polymer loading and host materials with the largest pore size. Excessive polymer loading and smaller pore sizes lead to decreased performance due to inhibition of Li+ transport. The C18 templated TiO2 composite produced the best capacity retention at 58% retention, and the C12 composite produced the highest initial capacity of 170 mAh/g using a current density of 1 mA.cm-2. To improve the interface between the polymer and host materials a synthesis was adapted using a catalyst-free UV initiated polymerisation of vapour-loaded pyrrole monomer with mesoporous Ti and Ta oxides. The best materials showed improved conductivity for both the Ti and Ta oxides as well as improved Li+ capacity (190 mAh/g) relative to the pristine material (128 mAh/g) and superior capacity retention (49% as compared to 22%) for the Ti composites. The retention in surface area was 87% compared to 49% reported previously for analogous materials synthesised by catalyst-initiated method. This yielded Li+ capacities of 170 mAh/g further highlighting the superiority of this new photochemical approach. Since polymer doping seemed to improve conductivity while inhibiting Li+ transport an alternative approach using hexamethyldisilathiane (HMDST) to exchange Ti-O units with Ti-S at the surface of the mesopore channels to reduce the band gap between the valance band and the conduction band, increasing the conductivity while retaining the porosity and thermal stability. Lower temperatures generally yielded materials with superior properties and although conductivity was improved using higher loading levels of HMDST, this produced a significant drop in initial capacity (137 - 41 mAh/g), but superior retention on cycling. The best performing material was synthesised using large amounts of regent (3.5 mL) at lower heating temperatures (100 °C) to maximise the combination of surface area, initial capacity, conductivity, and capacity retention (76%). Finally a vanadium hydride gel was prepared by thermal treatment of tetraphenylvanadium(IV) followed by hydrogenation. This V(III)-based material is redox active and the hydride ligand very light relative to oxide and phosphate supporting ligands normally used in V(III)-based battery materials. For this reason it could potentially lead to greater Li+ insertion capacities, so electrochemical evaluation was warranted. The best material demonstrated a peak capacity of 131 mAh/g, at a discharge rate of 1 mA.cm-2. After repeated charge discharge cycling for 50 cycles, the material retained 36% of its capacity.

The thesis examines the design and implementation of a supervisory controller for the energy management of an AC stand-alone microgrid. The microgrid under study consists of a photovoltaic (PV), battery energy storage system (BESS) and auxiliary (micro gas turbine) units connected to a common AC bus and supplies a local load. The BESS unit has to maintain the AC bus voltage and frequency and needs to balance the difference between the intermittent PV power and that consumed by the load. However, the BESS has limited energy capacity and power rating and therefore it is important to implement a supervisory controller that can curtail the PV power to prevent the battery from being overcharged and also to operate the auxiliary unit to prevent the battery from being over discharged. A Fuzzy Logic Controller (FLC) that can be implemented inside the BESS unit is proposed. It monitors the battery power and State of Charge (SOC) and varies the bus frequency accordingly. The variation in the bus frequency serves as a communication means to the PV and auxiliary units. If the frequency is increased above the nominal value, the PV unit starts to curtail its power and if the frequency is decreased, the auxiliary unit starts to generate power. Power curtailment and supplement are proportional to the frequency variation. In order to avoid any need for communication links between the units, the DC/AC inverters of all the units adopt the well-known wireless droop technique. The droop control of the auxiliary unit is implemented in such a way that the unit is floating on the bus and thus it generates power only if the bus frequency is decreased below its nominal value. The main merits of the proposed controller are simplicity and easiness of implementation inside the BESS unit. The effectiveness of the controller in protecting the battery from over-charging/over-discharging has been verified by simulations including a real-time simulation and experimentally. Furthermore, the thesis investigates the effect of sudden shading of a PV and concentrated PV (CPV) on the bus frequency of an AC stand-alone microgrid. It is known that the CPV power can drop drastically, compared to traditional PV, when it is exposed to shading. A simulation model of the CPV in a microgrid has been built and the results are compared to those of the traditional PV. It is found that shading of the CPV has much more stronger effect on the bus frequency.

This research aims to develop synthesis protocols (based on a single route) to produce fullerenol with specified level of hydroxylation (n(оʜ)), and to demonstrate comparison of effects from different classes of fullerenol (i.e. different n(оʜ)) in an unexplored application (energy storage). The route of fullerene hydroxylation by NaOH in presence of phase-transfer catalyst TBAH was chosen as a basis for this research. Producton consistency in terms of achieved n(оʜ) was evaluated, and effects of selected three process parameters on n(оʜ) were investigated. Non-linear relationship between amount of TBAH used and n(оʜ) showed a maximum (n(оʜ) = 14 groups) for TBAH = 24 drops, and a minimum (n(оʜ) = 8 groups) for 3 drops. Relationship between volume of NaOH solution used and n(оʜ) resembles Freundlich Adsorption Isotherm for liquid-solid adsorption. 8.0 ml NaOH solution gave the same n(оʜ) = 16 groups as 4.0 ml solution, however an increase in production capacity was more obvious. Reaction time 10-30 minutes did not cause noticeable changes to n(оʜ). Three protocols for producing three classes of fullerenol (n(оʜ) < 10; n(оʜ) = 10-14; n(оʜ) = 15-20) within practical range based on TBAH-NaOH route have been developed. Adverse effects of CO₂ and O₃ on the route have been discovered. The research also established systematic mathematical calculations for determining empirical formula of fullerenol using TGA and EDX ('TGA-EDX method'). Minimum requirements of process design for fullerenol production are provided. Scale-up syntheses using the developed protocols were conducted and the products were used for investigation on the effect of n(оʜ) on performance of symmetric activated carbon supercapacitor containing fullerenol as electrode additives. Although lower in specific capacitance (and larger ESR), all fullerenol-containing supercapacitors offered higher maximum power, energy density and charge-transfer when compared to additive-free supercapacitor - suggesting potential and possibilities of fullerenol in energy applications.

Aqueous rechargeable lithium ion battery (ARLB) systems are potential alternative to existing rechargeable battery systems like Ni-Cd, Ni-MH, lead acid and lithium ion battery due to its advantages including rate capabilities, safety and environmental friendliness. Investigations of high energy/power, long cycle life and low-cost materials for aqueous rechargeable lithium ion batteries are of great interest especially for transportation applications such as electric (EVs) or hybrid-electric vehicles (HEVs), large-scale power storage grids and wearable electronics. ARLBs have higher power density but lower energy densities compared to lithium polymer batteries. ARLBs have much better rate capabilities (10-5000mAg-1 ) compared to lithium ion batteries (0.1-10mAg-1 ). This thesis focuses on the development and study of novel hexavanadate based anode and lithium manganese oxide based cathode materials for ARLBs with higher energy densities and better cycle life performances at higher rates. In this thesis, new set of hexavanadate based materials with high theoretical capacities like Li3V6O16, Na2V6O16, K2V6O16, CaV6O16 and SrV6O16 from the family of metal vanadium oxides (M2 ? ?+V6O16; x = valency of alkali metal ion) for aqueous rechargeable lithium ion battery were synthesized by both facile hydrothermal and sol-gel method using Vanadium Oxide (V2O5) and hydroxide salt of the alkali metal ion (LiOH, NaOH, KOH, Ca(OH)2 and Sr(OH)2. Similarly, different morphologies of high-voltage Spinel materials like LiMn2O4 were explored for its suitability to develop a better full cell ARLB. Electrochemical studies show higher lithium ion insertion into M2 ? ?+V6O16 but with irreversible capacity loss which is the research challenge this work has aimed to study and tried to address. As-prepared material were subjected to crystallographic X-ray diffraction (XRD analysis, mechanical properties, surface morphology {field emission scanning electron microscope (FE-SEM) and transmission electron microscopy (TEM)} characterization to evaluate the effect of crystal structure and morphology on its electrochemical performance. CaV6O16 doped with TiO2 as anode exhibits an initial capacity of 350mAhg-1 and retention of 200mAhg-1 over 100 charge/discharge cycles, at a current density of 500mAg-1 , which is much better than any aqueous lithium-ion battery reported. LiMn2O4 hollow microspheres as cathode displays an initial capacity of 145mAhg-1 and a capacity retention of more than 90% of its initial capacity for over 1000 cycles at a current density of 500mAhg-1 , which proves its potential for usage in commercial applications. Fundamental studies on the importance of different morphologies, mechanism of intercalation/de-intercalation of lithium ions in aqueous media into M2 ? ?+V6O16, dissolution of electrode material, effect of electrolyte's counter-ion on rate performance, influence of annealing temperature on crystallinity and electrochemical performance were conducted to help us optimize several parameters to achieve the best performance. Further, a full-cell ARLB is constructed in a pouch cell configuration using LiMn2O4 as cathode and Na2V6O16 and CaV6O16 as Anode and evaluated for its electrochemical performance. Additionally, different energy harvesting options are explored to power a combination of two or more energy storage systems coupled to a sensor-driven smart consumption system. Finally, we demonstrate the application of an intelligent power sourcing storage and consumption system (IPSSC) through two case-studies using an ontology developed with the knowledge obtained through proper classification of the available energy harvesting systems, energy requirement of devices and their components and ambient real-time source of energy. A kinetic energy harvesting based RMS simulation tool was used to calculate the number of data packets that could be transmitted in a wireless sensor network application from the above real-time energy sources.

The integration of variable renewable energy sources (VRE) is likely to cause fundamental and structural changes to the operation of future power systems. In the United Kingdom (UK), large amounts of price-insensitive and variable-output wind generation is expected to be deployed to contribute towards renewable energy and carbon dioxide (CO2) emission targets. Wind generation, with near-zero marginal costs, limited predictability, and a limited ability to provide upward dispatch, displaces price-setting thermal power plants, with higher marginal costs, changing flexibility and reserve requirements. New-build, commercial-scale, and low-carbon generation capacity, such as CO2 capture and storage (CCS) and nuclear, may impact power system flexibility and ramping capabilities. Low-carbon generation portfolios with price-sensitive thermal power plants and energy storage are therefore likely to be required to manage increased levels of variability and uncertainty at operational timescales. This work builds on a high-resolution wind reanalysis dataset of UK wind sites. The locations of existing and proposed wind farms are used to produce plausible and internally consistent wind deployment scenarios that represent the spatial distribution of future UK wind capacity. Temporally consistent electricity demand data is used to characterise and assess demand-wind variability and net demand ramp events. A unit commitment and economic dispatch (UCED) model is developed to evaluate the likely operating regimes of thermal power plants and CCS-equipped units across a range of future UK wind scenarios. Security constraints for reserve and power plant operating constraints, such as power output limits, ramp rates, minimum up/down times, and start-up times, ensure the operational feasibility of dispatch schedules. The load factors, time spent at different loads, and the ramping and start-up requirements of thermal power plants are assessed. CO2 duration curves are developed to assess the impacts of increasing wind capacity on the distribution of CO2 emissions. A sensitivity analysis investigates the impacts of part-load efficiency losses, ramp rates, minimum up/down times, and start-up/shut-down costs on power plant operating regimes and flexibility requirements. The interactions between a portfolio of energy storage units and flexible CO2 capture units are then explored. This multi-disciplinary research presents a temporally-explicit and detailed assessment of operational flexibility requirements at full 8760 hour resolution, highlighting the non-linear impacts of increasing wind capacity. The methodological framework presented here uses high spatial-and temporal-resolution wind data but is expected to provide useful insights for other VREbased power systems to mitigate the implications of inadequate flexibility.

There is a drive to transform the electricity industry in the UK from one based largely on fossil fuels to one based on low or zero carbon sources. The challenge of this transition, enabling a secure and sustainable electricity industry at an acceptable cost to consumers, has been dubbed the Energy Trilemma. Grid-connected electrical energy storage presents a potential solution to this challenge. However, the benefits of storage are split across different sectors of the electricity industry and there are a number of regulatory barriers preventing access to revenue streams. One accessible revenue stream is energy trading or price arbitrage. In current market conditions, arbitrage cannot provide sufficient revenue for electricity storage to cover its capital costs; however, some studies have suggested that with increased penetration of intermittent renewable power, electricity price volatility will increase enabling storage to become commercially viable through price arbitrage alone. This thesis examines the hypothesis that: Increased wind penetration leads to increased commercial opportunities for energy storage through price arbitrage. A linear programme is used to define the optimum operating strategy for a storage device, subject to the constraints of maximum storage capacity, charging and discharging rates, conversion efficiency and self-discharge. Initially, historic electricity prices from the British electricity market are used to investigate the value of storage with a low penetration of intermittent wind power. The results show that revenue is dependent on storage characteristics, with the performance of different technologies varying substantially. Furthermore, revenue is highly dependent on changes in market structure and fuel price variations from one year to the next. The thesis describes the development of a fundamental electricity price model based on the stacked merit order dispatch of thermal generation bidding to produce electricity in a competitive market centred around marginal generation costs. For peaking plant, an exponential uplift in price is applied to represent scarcity of supply. The implications of increasing wind power output are examined using projections of the location and capacity of future wind farms and spatially distributed hind cast wind speed data generated from a mesoscale atmospheric model. The analysis highlights that despite increased value being placed on storage in an energy system with a high penetration of wind power, opportunities for arbitrage are, in fact, reduced. This is a result of an oversupply of electricity on windy days suppressing peak electricity prices and reducing the daily price spread, which arbitrage exploits.

The UK’s decarbonisation strategy to increasingly electrify heating and transport will change the demand requirement on the electricity system. Additionally, under a climate change future, it is projected that the decarbonised grid will need to be able to operate under higher average temperatures in the UK, increasing the need for comfort cooling during summer and leading to additional electricity demand. These new demands will result in greater variation between minimum and peak demand as well as a significant increase in overall demand. Concurrently, supply-side decarbonisation programmes may lead to more intermittent renewables such as wind, PV, tidal and wave, elevating variability in electricity generation. Coupled with the anticipated higher variation in demand this brings on several challenges in operating the electricity grid. In order to characterise these challenges this research develops a bespoke electricity dispatch model which builds on hourly models of demand and generation. The hourly demand profiles are based on a high electrification of heating, transport and cooling coupled with future temperatures premised on the UKCP09 high emission scenario climate projections. The demand profiles show a significant increase in peak demand by 2050 reaching 194 GW, mainly due to summer cooling loads which contribute 70% of the demand. The cumulative CO2 emissions budgets of the GB power sector that are consistent with avoiding global climate change to 2°C are used to develop two low carbon generation scenarios distinguished by the amount of intermittent renewable generation technologies. The dispatch model tests the capability of generation scenarios with the use of hourly generation models in meeting future demand profiles out to 2050.The outputs from dispatch model indicate that there are shortages and excesses of generation relative to demand from 2030 onwards. The variability analysis outlines low and high generation periods from intermittent technologies along with the pace at which intermittent generation increases or decreases within an hour. The characterisation of variability analysis reveals the type of reserve capacity or smart solutions that are required to maintain the security of electricity supply. The solutions that could address the challenges quantified from the model outputs in operating a decarbonised GB electricity grid are explored using expert interviews. The analysis of the stakeholder interviews suggests smart grid solutions that include technologies as well as changes in operational procedures in order to enhance the operational resilience of the grid. Active Network Management through monitoring and control, demand management, storage systems and interconnectors are proposed to address challenges arising from varying demand and generation variability.

At present, one of the main issues in electric power networks is the reduction in conventional generation and its replacement by low inertia renewable energy generation. The balance between generation and demand has a direct impact on the system frequency and system inertia limits the frequency rate of change until compensation action can be undertaken. Traditionally generation managed frequency. In future, loads may be required to do more than just be able to be switched off during severe under frequency events. This thesis focuses on the development and practical implementation of the control structure of a smart adaptive load for network power-frequency support applications. The control structure developed makes use of advanced demand side management of fan loads (powered by AC drives) used in heating, ventilation, and air conditioning systems; where a change in power at rated load has little effect on their speed due to the cubic relationship between speed and power. The AC drive implemented in this thesis is based on an induction motor and a two level voltage source converter. To achieve the smart adaptive load functionality, first a power-frequency multi-slope droop control structure (feedforward control) is developed; relating the frequency limits imposed by the network supplier and the fan power-speed profile (Chapter 2, Fig 2.19). Secondly, this control structure is combined with the control developed, in Chapter 3, for the AC drive powering the fan load. The full development of the control structure of the AC drive, its tuning process and its practical implementation is given; an equation is developed to find suitable tuning parameters for the speed control of the nonlinear load (fan load), i.e. Eq. (3.59).The analysis and simulation results provided in Chapter 4 conclude that a fast control of the active power drawn by the AC drive is possible by controlling the electromagnetic torque (hence current) of the induction motor without disturbing the fan load overly. To achieve this, changes between closed loop speed control and open loop torque control (power control) are performed when needed. Two main issues were addressed before the hardware implementation of the smart adaptive load: the estimation of the network frequency under distorted voltage conditions, and the recovery period of the network frequency. In this thesis two slew rate limiters were implemented to deal with such situations. Other possible solutions are also outlined. Finally, experimental results in Chapter 5 support results given in Chapter 4. A full power-frequency response is achieved by the smart adaptive load within 3s.

This research investigates the energy, financial and environmental performance of an innovative integrated gasification fuel cell combined cycle fuelled by municipal solid waste that includes hydrogen storage and electrolysis. The suitability for fuel cells to run on synthesis gas coming from the gasification of waste is determined by the sensitivity of the fuel cell to run on contaminated fuel. Out of the available fuel cell technologies solid oxide fuel cells (SOFCs), because of their ceramic construction and high operating temperatures, are best suited for syngas operation. Their high operating temperature ( > 650°C) and the presence of nickel at the anode means that it is possible to reform hydrocarbons to provide further hydrogen. A major contaminant to be considered in gasification systems is tar which can foul pipework and cause substantial performance losses to the plant. Experimental research on the effects of tar on a SOFC at varying concentrations and operating conditions show; that some carbon deposition serves to improve the performance of the fuel cell by reducing the ohmic resistance, and there is a tendency for the tar to reform which improves overall performance. These improvements are seen at moderate tar concentrations but at higher concentrations carbon deposition causes substantial performance degradation. Numerical simulations representing all aspects of the proposed system have been developed to understand the energy performance of the system as a whole as well as the financial and environmental benefits. Taking into account variations in the waste composition, and the wholesale electricity price the proposed system, scaled to process 100,000 tonnes of waste per year (40,000 removed for recycling), has a simple payback period of 7.2 years whilst providing CO2 savings of 13%. Over the year the proposed system will provide enough electricity to supply more than 23,000 homes and enough heat for more than 5,800 homes (supplying 25% of the electrically supplied homes).

The power sector needs to be decarbonised by 2050 to meet the global target for greenhouse gas emission reduction and prevent climate change. With fossil fuels expected to play a vital role in the future energy portfolio and high efficiency penalties related to mature CO2 capture technologies, this research aimed at evaluating the efficiency improvements and alternate operating modes of the coal-fired power plants (CFPP) retrofitted with post-combustion CO2 capture. To meet this aim, process models of the CFPPs, chilled ammonia process (CAP) and calcium looping (CaL) were developed in Aspen Plus® and benchmarked against data available in the literature. Also, the process model of chemical solvent scrubbing using monoethanolamine (MEA) was adapted from previous studies. Base-load analysis of the 580 MWel CFPP retrofits revealed that if novel CAP retrofit configurations were employed, in which a new auxiliary steam turbine was coupled with the boiler feedwater pump for extracted steam pressure control, the net efficiency penalty was 8.7–8.8% points. This was close to the 9.5% points in the MEA retrofit scenario. Conversely, CaL retrofit resulted in a net efficiency penalty of 6.7–7.9% points, depending on the fuel used in the calciner. Importantly, when the optimised supercritical CO2 cycle was used instead of the steam cycle for heat recovery, this figure was reduced to 5.8% points. Considering part-load operation of the 660 MWel CFPP and uncertainty in the process model inputs, the most probable net efficiency penalties of the CaL and MEA retrofits were 9.5% and 11.5% points, respectively. Importantly, in the CaL retrofit scenarios, the net power output was found to be around 40% higher than that of the CFPP without CO2 capture and double than that for the MEA retrofit scenario. Such performance of the CaL retrofit scenario led to higher profit than that of the 660 MWel CFPP without CO2 capture, especially if its inherent energy storage capability was utilised. Hence, this study revealed that CaL has the potential to significantly reduce the efficiency and economic penalties associated with mature CO2 capture technologies.

The electricity network is undergoing significant changes in the transition to a low carbon system. The growth of renewable distributed generation (DG) creates a number of technical and economic challenges in the electricity network. While the development of the smart grid promises alternative ways to manage network constraints, their impact on the ability of the network to accommodate DG – the ‘hosting capacity’- is not fully understood. It is of significance for both DNOs and DGs developers to quantify the hosting capacity according to given technical or commercial objectives while subject to a set of predefined limits. The combinational nature of the hosting capacity problem, together with the intermittent nature of renewable generation and the complex actions of smart control systems, means evaluation of hosting capacity requires appropriate optimisation techniques. This thesis extends the knowledge of hosting capacity. Three specific but related areas are examined to fill the gaps identified in existing knowledge. New evaluation methods are developed that allow the study of hosting capacity (1) under different curtailment priority rules, (2) with harmonic distortion limits, and (3) alongside energy storage systems. These works together improve DG planning in two directions: demonstrating the benefit provided by a range of smart grid solutions; and evaluating extensive impacts to ensure compliance with all relevant planning standards and grid codes. As an outcome, the methods developed can help both DNOs and DG developers make sound and practical decisions, facilitating the integration of renewable DG in a more cost-effective way.

The Autonomic Power System (APS) grand challenge was a multi-disciplinary EPSRC-funded research project that examined novel techniques that would enable the transition between today's and 2050's highly uncertain and complex energy network. Being part of the APS, this thesis reports on the sub-project 'RR2: Avoiding High-Impact Low Probability events'. The goal of RR2 is to develop new algorithms for controlling risk exposure to high-impact low probability (Hi-Lo) events through the provision of appropriate risk-sensitive control strategies. Additionally, RR2 is concerned with new techniques for identifying and modelling risk in future energy networks, in particular, the risk of Hi-Lo events. In this context, this thesis investigates two distinct problems arising from energy risk management. On the one hand, we examine the problem of finding managerial strategies for exercising the operational flexibility of energy assets. We look at this problem from a risk perspective taking into account non-linear risk preferences of energy asset managers. Our main contribution is the development of a risk-sensitive approach to the class of optimal switching problems. By recasting the problem as an iterative optimal stopping problem, we are able to characterise the optimal risk-sensitive switching strategies. As byproduct, we obtain a multiplicative dynamic programming equation for the value function, upon which we propose a numerical algorithm based on least squares Monte Carlo regression. On the other hand, we develop tools to identify and model the risk factors faced by energy asset managers. For this, we consider a class of models consisting of superposition of Gaussian and non-Gaussian Ornstein-Uhlenbeck processes. Our main contribution is the development of a Bayesian methodology based on Markov chain Monte Carlo (MCMC) algorithms to make inference into this class of models. On extensive simulations, we demonstrate the robustness and efficiency of the algorithms to different data features. Furthermore, we construct a diagnostic tool based on Bayesian p-values to check goodness-of-fit of the models on a Bayesian framework. We apply this tool to MCMC results from fitting historical electricity and gas spot price data- sets corresponding to the UK and German energy markets. Our analysis demonstrates that the MCMC-estimated models are able to capture not only long- and short-lived positive price spikes, but also short-lived negative price spikes which are typical of UK gas prices and German electricity prices. Combining together the solutions to the two problems above, we strive to capture the interplay between risk, uncertainty, flexibility and performance in various applications to energy systems. In these applications, which include power stations, energy storage and district energy systems, we consistently show that our risk management methodology offers a tradeoff between maximising average performance and minimising risk, while accounting for the jump dynamics of energy prices. Moreover, the tradeoff is achieved in such way that the benefits in terms of risk reduction outweigh the loss in average performance.

Transition towards low-carbon energy systems requires an increase in the volume of renewable Distributed Generation (DG), particularly wind and photovoltaic, connected to distribution networks. To facilitate the connection of renewable DG without the need for expensive and time-consuming network reinforcements, distribution networks should move from passive to active methods of operation, whereby technical network constraints are actively managed in real time. This requires the deployment of control solutions that manage network constraints and, crucially, ensure adequate levels of energy curtailment from DG plants by using other controllable elements to solve network issues rather than resorting to generation curtailment only. This thesis proposes a deterministic distribution Network Management System (NMS) to facilitate the connections of renewable DG plants (specifically wind) by actively managing network voltages and congestion in real time through the optimal control of on-load tap changers (OLTCs), DG power factor and, then, generation curtailment as a last resort. The set points for the controllable elements are found using an AC Optimal Power Flow (OPF). The proposed NMS considers the realistic modelling of control by adopting one-minute resolution time-series data. To decrease the volumes of control actions from DG plants and OLTCs, the proposed approach departs from multi-second control cycles to multi-minute control cycles. To achieve this, the decision-making algorithm is further improved into a risk-based one to handle the uncertainties in wind power throughout the multi-minute control cycles. The performance of the deterministic and the risk-based NMS are compared using a 33 kV UK distribution network for different control cycles. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment. This thesis also proposes energy storage sizing framework to find the minimum power rating and energy capacity of multiple storage facilities to reduce curtailment from DG plants. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC OPF across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. The application of the proposed planning framework to a 33 kV UK distribution network demonstrates the importance of embedding real-time control aspects into the planning framework so as to accurately size storage facilities. By using reactive power capabilities of storage facilities it is possible to reduce storage sizes. The combined active management of OLTCs and power factor of DG plants resulted in the most significant benefits in terms of the required storage sizes.

Local electricity markets can be defined broadly as 'future electricity market designs involving domestic customers, demand-side response and energy storage'. Like current deregulated electricity markets, these localised derivations present specific stochastic optimisation problems in which the dynamic and random nature of the market is intertwined with the physical needs of its participants. Moreover, the types of contracts and constraints in this setting are such that 'games' naturally emerge between the agents. Advanced modelling techniques beyond classical mathematical finance are therefore key to their analysis. This thesis aims to study contracts in these local electricity markets using the mathematical theories of stochastic optimal control and games. Chapter 1 motivates the research, provides an overview of the electricity market in Great Britain, and summarises the content of this thesis. It introduces three problems which are studied later in the thesis: a simple control problem involving demand-side management for domestic customers, and two examples of games within local electricity markets, one of them involving energy storage. Chapter 2 then reviews the literature most relevant to the topics discussed in this work. Chapter 3 investigates how electric space heating loads can be made responsive to time varying prices in an electricity spot market. The problem is formulated mathematically within the framework of deterministic optimal control, and is analysed using methods such as Pontryagin's Maximum Principle and Dynamic Programming. Numerical simulations are provided to illustrate how the control strategies perform on real market data. The problem of Chapter 3 is reformulated in Chapter 4 as one of optimal switching in discrete-time. A martingale approach is used to establish the existence of an optimal strategy in a very general setup, and also provides an algorithm for computing the value function and the optimal strategy. The theory is exemplified by a numerical example for the motivating problem. Chapter 5 then continues the study of finite horizon optimal switching problems, but in continuous time. It also uses martingale methods to prove the existence of an optimal strategy in a fairly general model. Chapter 6 introduces a mathematical model for a game contingent claim between an electricity supplier and generator described in the introduction. A theory for using optimal switching to solve such games is developed and subsequently evidenced by a numerical example. An optimal switching formulation of the aforementioned game contingent claim is provided for an abstract Markovian model of the electricity market. The final chapter studies a balancing services contract between an electricity transmission system operator (SO) and the owner of an electric energy storage device (battery operator or BO). The objectives of the SO and BO are combined in a non-zero sum stochastic differential game where one player (BO) uses a classic control with continuous effects, whereas the other player (SO) uses an impulse control (discontinuous effects). A verification theorem proving the existence of Nash equilibria in this game is obtained by recursion on the solutions to Hamilton-Jacobi-Bellman variational PDEs associated with non-zero sum controller-stopper games.

The domestic sector will play an important role in the decarbonisation and decentralisation of the energy sector in the future. Installation numbers of building-integrated small-scale energy systems such as photovoltaics (PV), wind turbines and micro-combined heat and power (CHP) have significantly increased. However, the power output of PV and wind turbines is inherently linked to weather conditions; thus, the injected power into the public grid can be highly intermittent. With the increasing share of renewable energy at all voltage levels challenges arise in terms of power stability and quality. To overcome the volatility of such energy sources, storage technologies can be applied to temporarily decouple power generation from power consumption. Two emerging storage technologies which can be applied at residential level are hydrogen systems and vanadium-redox-flow-batteries (VRFB). In addition, the building-integrated energy sources and storage system can be combined to form a hybrid renewable energy system (HRES) to manage the energy flow more efficiently. The main focus of this thesis is to investigate the dynamic performance of two emerging energy storage technologies, a hydrogen loop composed of alkaline electrolyser, gas storage and proton exchange membrane (PEM) fuel cell, and a VRFB. In addition, the application of building-integrated HRES at customer level to increase the self-consumption of the onsite generated electricity and to lower the grid interaction of the building has been analysed. The first part deals with the development of a research test-bed known as the Hybrid Renewable Energy Park (HREP). The HREP is a residential-scale distributed energy system that comprises photovoltaic, wind turbine, CHP, lead acid batteries, PEM fuel cell, alkaline electrolyser and VRFB. In addition, it is equipped with programmable electronic loads to emulate different energy consumption patterns and a charging point for electric vehicles. Because of its modular structure different combinations of energy systems can be investigated and it can be easily extended. A unified communication channel based on the local operating network (LON) has been established to coordinate and control the HREP. Information from the energy systems is gathered with a temporal resolution of one second. Integration issues encountered during the integration process have been addressed. The second part presents an experimental methodology to assess the steady state and dynamic performance of the electrolyser, the fuel cell and the VRFB. Operational constrains such as minimum input/output power or start-up times were extracted from the experiments. The response of the energy systems to single and multiple dynamic events was analysed, too. The results show that there are temporal limits for each energy system, which affect its response to a sudden load change or the ability to follow a load profile. Obstacles arise in terms of temporal delays mainly caused by the distributed communication system and should be considered when operating or simulating a HRES at system level. The third part shows how improved system models of each component can be developed using the findings from the experiments. System models presented in the literature have the shortcoming that operational aspects are not adequately addressed. For example, it is commonly assumed that energy systems at system level can respond to load variations almost instantaneously. Thus, component models were developed in an integrated manner to combine theoretical and operational aspects. A generic model layout was defined containing several subsystems, which enables an easy implementation into an overall simulation model in MATLAB®/Simulink®. Experimental methods were explained to extract the new parameters of the semi-empirical models and discrete operational aspects were modelled using Stateflow®, a graphical tool to formulate statechart diagrams. All system models were validated using measured data from the experimental analysis. The results show a low mean-absolute-percentage-error (<3%). Furthermore, an advanced energy management strategy has been developed to coordinate and to control the energy systems by combining three mechanisms; statechart diagrams, double exponential smoothing and frequency decoupling. The last part deals with the evaluation, operation and control of HRES in the light of the improved system models and the energy management strategy. Various simulated case studies were defined to assess a building-integrated HRES on an annual basis. Results show that the overall performance of the hydrogen loop can be improved by limiting the operational window and by reducing the dynamic operation. The capability to capture the waste heat from the electrolyser to supply hot water to the residence as a means of increasing the overall system efficiency was also determined. Finally, the energy management strategy was demonstrated by real-time experiments with the HREP and the dynamic performance of the combined operation has been evaluated. The presented results of the detailed experimental study to characterise the hydrogen loop and the VRFB as well as the developed system models revealed valuable information about their dynamic operation at system level. These findings have relevance to the future application and for simulation studies of building-integrated HRES. There are still integration aspects which need to be addressed in the future to overcome the proprietary problem of the control systems. The innovations in the HREP provide an advanced platform for future investigations such as electric-vehicles as decentralised mobile storage and the development of more advanced control approaches.