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Solar energy is one type of clean energy resource, and currently the IMO, EU and UK are targeting net zero carbon emissions by 2050. This paper delves into the integration of photovoltaic (PV) systems into hybrid vessels in order to meet their strategies and targets. The technical challenges that come with designing such systems as well as their economic and environmental impacts are examined. By optimizing the usage of harnessed solar energy, we discover the operational strategy that provides maximal benefits through day-to-day savings as well as over the 25 year lifespan of solar panels. It demonstrates impressive economic viability, with cost savings of up to GBP 4.55 per day and a payoff period as short as 9 years. It also displays a modest emission reduction of up to 8.002 kg of CO2, which serves as proof for a pathway to greener practices in the maritime industry. This report highlights the operational flexibility that a hybrid vessel possesses once paired with a PV system through the ability to withstand regulatory and market changes. Also, when looking ahead, further adoption of PV technology creates opportunities for innovation in adopting renewable energy solutions in maritime transportation. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

The UK net‐zero target requires the integration of significant renewable energy resources into the electrical grid. This, together with the projected growth in electricity demand imposes practical challenges on the power transfer capability of existing transmission feeders. For environmental and planning reasons, construction of new overhead lines is problematic, and where possible upgrading of existing substations and lines is preferred. This paper investigates the feasibility of transforming an existing three‐phase (3Φ) double‐circuit 400 kV line into a six‐phase (6Φ) feeder for a simulated future GB scenario. Results indicate a 6Φ feeder, operating at a 'phase‐adjacent phase' voltage of 400 kV can effectively solve the constraints of boundaries in transmission networks. When considering the various operating contingencies, associated with an important UK network boundary and its expected near‐future winter‐peak power transfer requirements, the thermal overload issues are mitigated by transforming a feeder from 3Φ to 6Φ. The paper demonstrates upgrading to 6Φ technology is a potential solution to certain future boundary constraints and in these cases avoids the need to build new underground or overhead AC/DC lines. [ABSTRACT FROM AUTHOR]

Hydrogen is gaining prominence as a sustainable energy source in the UK, aligning with the country's commitment to advancing sustainable development across diverse sectors. However, a rigorous examination of the interplay between the hydrogen economy and the Sustainable Development Goals (SDGs) is imperative. This study addresses this imperative by comprehensively assessing the risks associated with hydrogen production, storage, transportation, and utilization. The overarching aim is to establish a robust framework that ensures the secure deployment and operation of hydrogen-based technologies within the UK's sustainable development trajectory. Considering the unique characteristics of the UK's energy landscape, infrastructure, and policy framework, this paper presents practical and viable recommendations to facilitate the safe and effective integration of hydrogen energy into the UK's SDGs. To facilitate sophisticated decision making, it proposes using an advanced Decision-Making Trial and Evaluation Laboratory (DEMATEL) tool, incorporating regret theory and a 2-tuple spherical linguistic environment. This tool enables a nuanced decision-making process, yielding actionable insights. The analysis reveals that Incident Reporting and Learning, Robust Regulatory Framework, Safety Standards, and Codes are pivotal safety factors. At the same time, Clean Energy Access, Climate Action, and Industry, Innovation, and Infrastructure are identified as the most influential SDGs. This information provides valuable guidance for policymakers, industry stakeholders, and regulators. It empowers them to make well-informed strategic decisions and prioritize actions that bolster safety and sustainable development as the UK transitions towards a hydrogen-based energy system. Moreover, the findings underscore the varying degrees of prominence among different SDGs. Notably, SDG 13 (Climate Action) exhibits relatively lower overall distinction at 0.0066 and a Relation value of 0.0512, albeit with a substantial impact. In contrast, SDG 7 (Clean Energy Access) and SDG 9 (Industry, Innovation, and Infrastructure) demonstrate moderate prominence levels (0.0559 and 0.0498, respectively), each with its unique influence, emphasizing their critical roles in the UK's pursuit of a sustainable hydrogen-based energy future. [ABSTRACT FROM AUTHOR]

Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that efficiently matches available power supply and demand. The core of improvement of the proposed smart battery scheduling algorithm is exploiting future knowledge, which can be realized by current state-of-the-art forecasting techniques, to effectively store and trade energy. The performance of the developed heuristic battery scheduling algorithm using forecast data of demands, generation, and energy prices is compared to a heuristic baseline algorithm, where decisions are made solely on the current state of the battery, demand, and generation. The battery scheduling algorithms are tested using real data from two large-scale smart energy trials in the UK, in addition to various types and levels of simulated uncertainty in forecasts. The results show that when using a battery to store generated energy, on average, the newly proposed algorithm outperforms the baseline algorithm, obtaining up to 20–60% more profit for the prosumer from their energy assets, in cases where the battery is optimally sized and high-quality forecasts are available. Crucially, the proposed algorithm generates greater profit than the baseline method even with large uncertainty on the forecast, showing the robustness of the proposed solution. On average, only 2–12% of profit is lost on generation and demand uncertainty compared to perfect forecasts. Furthermore, the performance of the proposed algorithm increases as the uncertainty decreases, showing great promise for the algorithm as the quality of forecasting keeps improving. [ABSTRACT FROM AUTHOR]

This paper provides a high-accuracy assessment of domestic demand-side management (DSM) approach in the context of distributed renewable energy sources (RES). To determine the potential of domestic DSM for households, a microgrid model of a typical UK residential estate was developed to simulate the impact of RES. The microgrid model comprises 15 UK households with appropriate allocation of washing machines, tumble dryers and dishwashers in accordance with the statistical data. In order to obtain a high-accuracy result, the power consumption of the microgrid model utilises real historical high-resolution data of household energy consumption and RES generation. Thereafter, 40% of distributed wind and solar energy is implemented in the model to produce two individual scenarios. The operation of the white appliances in the model is controlled using a domestic DSM based on a load shifting algorithm. The primary criterion of the DSM considered in this paper is the reduction in energy feedback to the grid in order to decrease the utilisation of the grid and to reduce the transmission losses. The results obtained from the model simulation are compared to the baseline model and discussed with respect to the possible benefits of implementation of domestic DSM under the impact of RES. It has been shown that the self-consumption ratio of the microgrid operating under the DSM is increased by 3% for both scenarios. The model analysis provides highly realistic results which can be used for efficiency assessment of various load shifting methods. [ABSTRACT FROM AUTHOR]

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon a total or partial system failure. However, with the continuous shutdown of large-centralised generators, which traditionally provided the black start support together with the variability of RES, the restoration process becomes much more complex. Primarily, the RES should have enough capacity to energise the load at the time of the restoration. Nonetheless, due to significant advantages, there is an increasing trend to use RES to meet the local energy demand by large industrial customers. The flexibility of shifting loads together with the surplus of RE generation could support the system operator during the system energisation process after a blackout. This paper mainly focuses on identifying the capabilities and factors that should be accounted for to participate in the system restoration process by large industrial consumers. The case study conducted on a large-scale steel factory in the UK reveals the possibility of supporting the restoration process under the bottom-up approach. [ABSTRACT FROM AUTHOR]

The reduced inertia levels in low-carbon power grids necessitate explicit constraints to limit frequency’s nadir and rate of change during scheduling. This can result in significant curtailment of renewable energy due to the minimum generation of thermal plants that are needed to provide frequency response (FR) and inertia. Additional consideration of fast FR, a dynamically reduced largest loss and under frequency load shedding (UFLS) allows frequency security to be achieved more cost effectively. This paper derives a novel constraint from the swing equation to contain the frequency nadir using all of these services. The expected cost of UFLS is found probabilistically to facilitate its comparison to the other frequency services. We demonstrate that this constraint can be accurately and conservatively approximated for moderate UFLS levels with a second order cone (SOC), resulting in highly tractable convex problems. Case studies performed on a Great Britain 2030 system demonstrate that UFLS as an option to contain single plant outages can reduce annual operational costs by up to $\pounds $ 559 m, 52% of frequency security costs. The sensitivity of this value to wind penetration, abundance of alternative frequency services, UFLS amount and cost is explored. [ABSTRACT FROM AUTHOR]

• A net-zero DN model composed of solely non-dispatchable DGs and BESSs has been considered to tackle severe windstorms. • The proposed framework is particularly effective in DNs with high shares of converter-based DGs. • The proposed three-stage resilience assessment can provide up to 25 percent load shedding reduction. • A detailed spatiotemporal representation of the DN was implemented to accurately estimate the status of the grid. Increasing incidences of extreme weather events pose significant challenges to the electrical grids in terms of the ability to withstand those high-impact eventualities. This paper proposes a resilience assessment framework for net-zero active distribution networks (ADNs) to tackle the impacts of extreme windstorms where only renewable energy resources (RESs) and battery energy storage systems (BESSs) are considered. To accurately capture the influence of windstorms on the grid, a detailed spatiotemporal representation of grid system assets and their exposure to the wind has been implemented. The suggested day-ahead resilience assessment is based on a three-stage approach. The first stage computes the probabilities of failure of each line and determines the most vulnerable ones. The second stage obtains the optimal grid configuration based on the outcomes of the first stage given the available non-dispatchable RESs and commits the available resources in each island to minimize the loss of load during the windstorm. If such a value is still larger than zero after the second stage, a novel voltage regulation scheme is applied in the third stage, taking advantage of the RESs and BESSs in each island. The proposed resilience assessment has been evaluated using the IEEE 33-bus test system with the meteorological data retrieved from an actual windstorm event occurred in the UK on the 20th of February. The outcomes of this paper underscore that a significant reduction in load shedding during such extreme events can be achieved, thus having a notable enhancement to the overall resilience of the system. Finally, the performance of this approach is compared with other resilience-oriented methods for windstorms, where the benefits of using the scheme reported in this paper are highlighted and quantified. [ABSTRACT FROM AUTHOR]

In the context of Great Britain, onshore wind provides the most cost-effective method of renewable electricity generation. However, projects often face opposition to development based on social issues, and there are concerns that existing geospatial modelling approaches fail to fully integrate these effects into their assessment. Building upon previous statistical analysis, this paper presents a geospatial multi-criteria decision analysis that integrates the technological, legislative and social constraints to determine suitable sites for onshore wind turbine development in Great Britain. The findings suggest that the capacity estimates for wind are less than 5% of what was previously estimated, yet opportunities remain for further exploitation of this resource. [ABSTRACT FROM AUTHOR]

Electric heat pumps (HPs), hybrid heating technology and district heating networks (DHN) are the main low-carbon heating technologies that can deliver the ambitious carbon reduction target in the UK. The optimal design of the heating system on a national scale to maximize the economic benefits regarding both investment cost and operation cost while satisfying the carbon target remains an open question. This paper aims to compare the economic advantages as well as the associated impacts on the electricity system under the full deployments of ASHP (air source HP), hybrid HP-Bs (ASHP and gas boilers) and DHNs. To do so, a novel whole-system approach is applied with the explicit consideration of the coordinated operation between heat and electricity system. The optimized strategy for heat sector decarbonisation is also demonstrated, providing an outline of the optimal deployment for different heating technologies in terms of their penetrations and deployed areas. The UK case study suggests the significant economic advantage of the hybrid HP-B over the other two heating technologies, while DHN may play an important role in urban areas under the optimized heat decarbonisation strategy. The results also clearly demonstrate the changes on the electricity side driven by the different decarbonisation strategies in the heating system. [ABSTRACT FROM AUTHOR]

This paper presents the methodological approach and findings of a simulation study of advanced energy conservation, generation and management technologies applied to two case study dwellings in the UK, so as to achieve net zero energy (NZE) target that includes a reduction of net regulated energy (HVAC) to 0 kWh/m 2 per year and energy generation of at least 50 kWh/m 2 per year. The performance of the dwellings are also tested for a change in energy use and risk of summertime overheating in future climates in the short (2030s), medium (2050s) and long term (2080s). The findings indicate that to meet the NZE targets, regulated loads need to reduce by about half (over current Building Regulations) with community (rather than building-level) renewables playing a major role. It is also found that the NZE targets, given current regulations, are not particularly difficult to achieve in design with regard to energy efficiency but are highly expectant with regard to renewable energy. Further, summertime overheating is projected to be a risk for net zero energy dwellings by the 2050s. Despite this the regulated energy use of both dwellings is projected to reduce by 11 kWh/m 2 /yr, accompanied by a small increase in renewable generation (2 kWh/m 2 /yr). [ABSTRACT FROM AUTHOR]

This paper articulates the potential implications of Brexit on energy policy and security in the United Kingdom (UK). Given the uncertainties associated with the decision to leave the European Union (EU), the need to consider its potential effects on the UK's energy sector becomes even more pertinent. Through the lens of a few widely reviewed trade regimes in the light of Brexit, it can be observed that while UK energy policies are unlikely to change drastically, Brexit nevertheless threatens the UK's capacity to safeguard its energy supply. The uncertainties following Brexit could arguably starve the UK's upstream petroleum, electricity, and renewable energy sectors of their required investments. Both short and long-term impacts could result in UK residents paying more per unit of energy consumed in a "hard Brexit" scenario, where the UK exits the Internal Energy Market (IEM) and must trade with the EU underWorld Trade Organisation rules. While a hard Brexit could aid the growth of the nascent shale gas industry, a negotiated withdrawal that includes some form of access to the IEM (a "soft Brexit") would be more beneficial for the future of energy security in the UK. [ABSTRACT FROM AUTHOR]

Abstract: This paper demonstrates how Linear Programming (LP) can be applied to assist in the choice of renewable energy technologies for use in buildings to meet CO2 emissions reduction targets. Since there are many possibilities for combining different renewable technologies, the capital costs associated with the installation of one or more renewables can vary widely. In terms of capital investment the preferred solution will be the one at least cost, and LP provides an effective way to find this minimum through the so-called “objective function”. This project has used “lp_solve”, a free-source Mixed Integer Linear Programming solver that has been embedded in a Microsoft Excel application called Carbon emissions And Renewables for Building OPtimisation Toolkit (CARB-OPT) developed by RES Ltd in collaboration with London South Bank University (Renewable Environmental Services Ltd. (RES) is the environmental consultancy of Long and Partners Engineering Group. RES is currently involved in a Knowledge Transfer Partnerships (KTP) project in conjunction with the Faculty of Engineering, Science and the Building Environment (ESBE) at London South Bank University). This paper reports the application of this LP optimisation process for an office building case study with four alternative combinations of renewables. The process showed the technology mix that would lead to the smallest investment needed to comply with UK Building Regulations requirements and regional planning targets. In addition, the process offers a robust methodology to test the impact that the key assumptions may have upon the optimum solution. [Copyright &y& Elsevier]

Abstract: In the past decade or so, the British government policy support for renewable energy (RE) has been at the core of the rapid growth of bioenergy in the UK rather than genuine market forces. Policy support has been through various instruments which are discussed in this paper, with particular attention given to co-firing and transport fuels. The UK energy sector remains dominated by large fossil fuels power plants and this does not facilitate the introduction of RE. One exception is co-firing which in 2005 generated 2.5TWh. Another area of considerable potential and interest is the use of biofuels (biodiesel and bioethanol) for transport, although current contribution remains still very small (0.18% of total fuel sales in 2005). In 2005, the UK used 1.4 million tonnes of biomass in co-firing, mostly imported, while considerable potential exists for further expansion should policy incentives continue. It is also generally accepted that the UK will have to rely largely on imports if it is to fulfil its 5% minimum biofuel blends agreed for 2010 and 10% in 2015. Both sectors present excellent opportunities for international bioenergy trade, despite the domestic production potential, as demonstrated in this paper. In addition, the forthcoming introduction of carbon and sustainability reporting should incentivise greater reporting along the supply chain, encouraging trade in the most sustainable biofuels. [Copyright &y& Elsevier]

In order to pursue the low-carbon development around the world, a large scale of renewable generation will be connected to the power systems. Take the Great Britain (GB) as an example, the GB power system has a large wind energy integration potential. The intermittency of wind generation will have great impact on the system frequency stability. Electric vehicles (EVs) have a crucial role in decarbonizing the transport sector. To increase the utilization of wind energy, EVs are suggested to provide frequency response service to the power system due to their quick power reaction characteristic. This paper proposes a general dynamic EV frequency control strategy considering the travelling behavior of the EV users. A droop control method is used to regulate the EV charging/discharging power according to the frequency signal. A Forced-Charge Boundary (FCB) and a Forced-Charge Area (FCA) are proposed to guarantee sufficient energy in the EV battery for user’s travel at the plug-out time. A dynamic Virtual Energy Storage System (VESS) is developed to evaluate the frequency response capacity of the EV clusters. In the case study, the model of the GB power system is used to investigate the frequency control effect of the control strategy. The simulation results show that the proposed strategy provides effective EV frequency response to the power system and thus is able to facilitate the integration of wind energy. [ABSTRACT FROM AUTHOR]

• Social acceptance research should be critical, systematic, and holistic. • Domestic hydrogen acceptance is shaped by the interplay of five distinct dimensions. • Hydrogen acceptance hinges on cognitive, sociopolitical, and sociocultural legitimacy. • Hydrogen acceptance is composed of a rich matrix of potential consumer responses. • Overcoming attitudinal and behavioral barriers is critical to the hydrogen transition. The 'deep' decarbonization of the residential sector is a priority for meeting national climate change targets, especially in countries such as the UK where natural gas has been the dominant fuel source for over half a century. Hydrogen blending and repurposing the national grid to supply low-carbon hydrogen gas may offer respective short- and long-term solutions to achieving emissions reduction across parts of the housing sector. Despite this imperative, the social acceptance of domestic hydrogen energy technologies remains underexplored by sustainability scholars, with limited insights regarding consumer perceptions and expectations of the transition. A knowledge deficit of this magnitude is likely to hinder effective policymaking and may result in sub-optimal rollout strategies that derail the trajectory of the net zero agenda. Addressing this knowledge gap, this study develops a conceptual framework for examining the consumer-facing side of the hydrogen transition. The paper affirms that the spatiotemporal patterns of renewable energy adoption are shaped by a range of interacting scales, dimensions, and factors. The UK's emerging hydrogen landscape and its actor-network is characterized as a heterogenous system, composed of dynamic relationships and interdependencies. Future studies should engage with domestic hydrogen acceptance as a co-evolving, multi-scalar phenomenon rooted in the interplay of five distinct dimensions: attitudinal, sociopolitical, community, market, and behavioral acceptance. If arrived to, behavioral acceptance helps realize the domestication of hydrogen heating and cooking, established on grounds on cognitive, sociopolitical, and sociocultural legitimacy. The research community should internalize the complexity and richness of consumer attitudes and responses, through a more critical and reflexive approach to the study of social acceptance. [ABSTRACT FROM AUTHOR]

The evolution towards Smart Grids (SGs) represents an important opportunity for modernization of the energy industry. It is characterized by a bidirectional flow of information and energy between consumers and suppliers. However, the rapid increase of energy demands in residential areas is becoming a challenging problem. In order to address this issue, Demand-Side Management (DSM) has proven to be an effective solution. In this paper, we propose LOSISH, a price-based Demand Response (DR) system for load scheduling in residential Smart Homes (SHs) that achieves a trade-off between electricity payments and consumer's discomfort. Our proposed system considers Renewable Energy Sources (RESs), Battery Energy Storage System (BESS) and Plug-in Electric Vehicle (PEV). We formulate our scheduling as a constrained optimization problem and we propose a new hybrid algorithm to solve it. The latter combines two well known heuristic algorithms: Particle Swarm Optimization (PSO) and Binary Particle Swarm Optimization (BPSO). Moreover, we propose a new clustering algorithm based on Machine Learning (ML) to extract consumer's preferences from a real dataset that contains the historical consumption patterns of his smart appliances. We test our approach on real data traces obtained from a SH and we set up an experiment to evaluate our algorithm on a Raspberry Pi and measure its energy consumption. To prove the effectiveness of our approach, we compare our results with another approach from the literature in terms of electricity bill, Peak-to-Average Ratio (PAR), energy consumption, and execution time. Numerical results show that LOSISH outperforms the other approach in terms of electricity bill (up to 52.92% cheaper), PAR (up to 44% decrease in peak demands), energy consumption (up to 69.44% less consumption), and execution time (up to 63.15% faster). • The load scheduling problem in residential smart homes is studied. • A constrained problem is formulated to make a trade-off between costs and comfort. • A hybrid heuristic algorithm and a Machine Learning clustering model are proposed. • Real data collected from a smart home in the UK was used to validate our approach. • Simulation and experimental results demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

The UK electricity grid is expected to supply a growing electricity demand and also to cope with electricity generation variability as the country pursues a low-carbon future. Molten Salt Reactors (MSRs) could offer a solution to meet this demand thanks to their estimated low capital costs, low operational risk, and promise of reliably dispatchable low-carbon electricity. In the published literature, there is little emphasis placed on estimating or modelling the future impact of MSRs on electricity grids. Previous modelling efforts were limited to quantifying the value of renewable energy sources, energy storage and carbon capture technologies. To date, no study has assessed or modelled MSRs as a competing power generation source for meeting decarbonization targets. Given this gap, the main objective of this paper is to explore the cost benefits for policy makers, consumers, and investors when MSRs are deployed between 2020 and 2050 for electricity generation in the UK. This paper presents results from electricity systems optimization (ESO) modelling of the costs associated with the deployment of 1350 MW e MSRs, from 2025 onwards to 2050, and compares this against a UK grid with no MSR deployment. Results illustrate a minimum economic benefit of £1.25 billion for every reactor installed over this time period. Additionally, an investment benefit occurs for a fleet of these reactors which have a combined net present value (NPV) of £22 billion in 2050 with a payback period of 23 years if electricity is sold competitively to consumers at a price of £60/MWh. [ABSTRACT FROM AUTHOR]

• Severe PV ramping at high penetration could cause voltage instability in presence of Induction motor loads. • Replacement of Induction motor by Variable Speed Drive (VSD) loads enhances voltage stability of distribution network. • Enhanced stability with VSD is studied theoretically with Q-V analysis and with time simulations. • Minimum IM replacement by VSD is determined for realistic distribution network at various PV penetration levels. The Photovoltaic (PV) sources have become the most popular renewable energy resources as it is modular and are deployed quickly. However, the distributed PVs are highly volatile and can have high ramping characteristics where the ramping can go up to 90% of its capacity in about 20 s due to events such as the passing of fast-moving clouds. This kind of PV ramps with high magnitudes can lead to voltage instability in distribution networks that are usually dominated by Induction motor (IM) loads. This paper explains the mechanism of such an instability analytically using Q-V analysis with distribution feeder and IM load characteristics. Highlighting the gradual replacement of IM loads by Variable Speed Drive (VSD) loads due to energy efficiency policies, the paper demonstrates the enhanced voltage stability under VSD loads by both time simulation and analytical approach. Furthermore, the analysis is extended to a realistic distribution network namely, United Kingdom General Distribution System (UKGDS) and extensive case studies are conducted to analyze the voltage stability during PV ramping events at various load compositions of IMs and VSDs. Moreover, the minimum VSD penetration level required to avert the voltage instability at various PV penetration levels have also been determined. [ABSTRACT FROM AUTHOR]

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers' feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer. [ABSTRACT FROM AUTHOR]

Energy policy is too often not designed for energy consumers in a low-cost and consumer-friendly manner. This paper proposes a novel Stackelberg game and Blockchain-based framework that enables consumer-centric decarbonization by automating iterative negotiations between policy makers and consumers or generators to reduce carbon emissions. This iterative negotiation is modeled as a Stackelberg game-theoretic problem, and securely facilitated by Blockchain technologies. The policy maker formulates carbon prices and monetary compensation rates to dynamically incentivize the carbon reduction, whereas consumers and generators schedule their power profiles to minimize bills and maximize profits of generation, respectively. The negotiating agreement is yielded by reaching a Stackelberg equilibrium. The exchanged information and controlling functions are realized by using smart contracts of Blockchain technologies. Case studies of GB power systems show that the proposed framework can incentivize 9% more bill savings for consumers and 45.13% more energy generation from renewable energy sources. As a consumer-centric decarbonization framework, it can at least reduce carbon emissions by 40%. [Display omitted] • A novel consumer-centric and negotiation-based framework to decarbonize power systems. • A Blockchain based platform to integrate the exchanged information and controlling functions of the power system scheduling into data structures, nodes, and smart contracts of Blockchain networks. • How Blockchain based platform can prevent cyber attacks is discussed. • Case studies demonstrate the effectiveness of the proposed framework in the context of Great Britain power systems. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of renewable and especially tidal energy through a political, economic, social, technology, legal and environmental (PESTLE) analysis approach and by reviewing the most up to date relevant literature. The study focuses on the United Kingdom given the favourable environmental resources for such technologies; the number of different design concepts that are currently under development as well as the research funding that has been invested over the last few years. Findings of the analysis identify the risks and multiple stakeholders involved at all stages of the tidal energy projects development from the conceptualization of the design, right through to decommissioning. Many of the stakeholders present benefits to the tidal developers through funding, incentives and knowledge sharing, but at the same time they also present potential risks to the future of projects. This is mostly down to different approaches of the most important aspect of tidal energy that needs to be considered, making it hard for technologists and developers to equally address all requirements. From this research it can be concluded that several of these risks can be mitigated early on providing that particular stakeholders are involved at the correct stage of a project. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes the concept development and work to date, of an innovative ‘true’ building integrated wind turbine. The context for this is the role of small-scale renewable energy in addressing climate change. In the UK a number of small wind turbines have reached the market, however, in almost all cases, these are existing HAWT or VAWT tower mounted systems. Due to their inherent design qualities, and issues such as planning requirements, these have much reduced output due to their form and siting and are unable to take advantage of augmented airflow around buildings. The Crossflex proposal is a radical new development of a Darrieus turbine form. As well as having a technically innovative flexible blade system, it also utilises a lightweight cowling system that can provide both augmented airflow and improved visual integration into new and existing building forms. It is a modular form that can be sited on ridges and corners of buildings to provide useful levels of generation. [ABSTRACT FROM AUTHOR]

Abstract: Possible solutions for zero energy building design in UK are discussed in this paper. Simulation software (EnergyPlus and TRNSYS 16) are employed in this study, where EnergyPlus simulations are applied to enable facade design studies considering building materials, window sizes and orientations and TRNSYS is used for the investigation of the feasibility of zero energy houses with renewable electricity, solar hot water system and energy efficient heating systems under Cardiff weather conditions. Various design methods are compared and optimal design strategies for typical homes and energy systems are provided. [Copyright &y& Elsevier]

Wind power is an increasingly used form of renewable energy. The uncertainty in wind generation is very large due to the inherent variability in wind speed, and this needs to be understood by operators of power systems and wind farms. To assist with the management of this risk, this paper investigates methods for predicting the probability density function of generated wind power from one to ten days ahead at five U.K. wind farm locations. These density forecasts provide a description of the expected future value and the associated uncertainty. We construct density forecasts from weather ensemble predictions, which are a relatively new type of weather forecast generated from atmospheric models. We also consider density forecasting from statistical time series models. The best results for wind power density prediction and point forecasting were produced by an approach that involves calibration and smoothing of the ensemble-based wind power density. [ABSTRACT FROM AUTHOR]

By constructing digital twins (DT) of an integrated energy system (IES), one can benefit from DT's predictive capabilities to improve coordinations among various energy converters, hence enhancing energy efficiency, cost savings and carbon emission reduction. This paper is motivated by the fact that practical IESs suffer from multiple uncertainty sources, and complicated surrounding environment. To address this problem, a novel DT-based day-ahead scheduling method is proposed. The physical IES is modelled as a multi-vector energy system in its virtual space that interacts with the physical IES to manipulate its operations. A deep neural network is trained to make statistical cost-saving scheduling by learning from both historical forecasting errors and day-ahead forecasts. Case studies of IESs show that the proposed DT-based method is able to reduce the operating cost of IES by 63.5%, comparing to the existing forecast-based scheduling methods. It is also found that both electric vehicles and thermal energy storages play proactive roles in the proposed method, highlighting their importance in future energy system integration and decarbonisation. • A deep learning and digital twins (DT) based scheduling method is proposed. • Physical IES performance is addressed by its virtual replica's predictive capability. • A machine learning method is proposed to address multiple uncertainty challenges. • Historical U.K. datasets are used for performance evaluations. • Results demonstrate the Digital Twin model reduces the extra operating cost by 63.5%. [ABSTRACT FROM AUTHOR]

Apart from numerous technical challenges, the transition towards a carbon-neutral energy supply is greatly hindered by limited economic feasibility of renewable energy sources. This results in their slow and bounded penetration in both commercial and residential sectors that are responsible for over 40% of final energy consumption. This paper aims to demonstrate that combined application of sophisticated planning methodologies at building-level and presents incentive mechanisms for renewables that can result in prosumers, featuring hybrid renewable energy systems (HRES), with economic performance comparable to that of conventional energy systems. The presented research enhances existing planning methodologies by integrating appliance-level demand side management into the decision process and investigates its effect on the planning problem. Moreover, the proposed methodology features an innovative and holistic approach that simultaneously assess electrical and thermal domain in both an isolated and grid-connected context. The analyzed hybrid system consists of solar photovoltaic, wind turbine and battery with thermal supply featuring solar thermal collector and a ground-source heat pump. Overall optimization problem is modeled as a mixed-integer linear program, while ranking of all feasible alternatives is made by the multicriteria decision-making algorithm against several technological, economic, and environmental criteria. A real-life scenario of energy system retrofit for a building in the United Kingdom was employed to demonstrate overall cost savings of 12% in the present market and regulation context. [ABSTRACT FROM AUTHOR]

In the context of challenging targets for renewable energy generation, this paper draws out social implications of moves towards low carbon energy systems. As renewable energy develops as a heterogeneous category, many potential forms of social relation between ‘publics’ and technologies are emerging. Utilising perspectives from science and technology studies, we outline five modes in which renewable energy has been implemented in the UK and how these involve different configurations of technology and social organisation. We argue that a multiplicity of roles for ‘the public’ are implicated across this increasingly complex landscape, cutting across established categories and raising questions of meaning, differentiation, interrelation and access. Policy assumptions and conceptions are questioned, highlighting that dominant characterisations of public roles have been part of a concentration on particular socio-technical pathways to the exclusion of others. [ABSTRACT FROM AUTHOR]

Abstract: There are varieties of physical and behavioral factors to determine energy demand load profile. The attainment of the optimum mix of measures and renewable energy system deployment requires a simple method suitable for using at the early design stage. A simple method of formulating load profile (SMLP) for UK domestic buildings has been presented in this paper. Domestic space heating load profile for different types of houses have been produced using thermal dynamic model which has been developed using thermal resistant network method. The daily breakdown energy demand load profile of appliance, domestic hot water and space heating can be predicted using this method. The method can produce daily load profile from individual house to urban community. It is suitable to be used at Renewable energy system strategic design stage. [Copyright &y& Elsevier]

This paper presents a new model of domestic lighting demand. The model is based on half-hourly data measured for a sample of 100 UK homes. It represents one sub-model in an end-user based distributed load model that is being developed to support investigations into the effects on low voltage urban electricity networks of future wide-scale uptake of solar technologies. To capture these effects and to serve applications involving renewable energy technologies (RETs) generally, the model is capable of representing load variations on very fine time-scales, down to 1 min intervals. Additionally, scaling factors are provided to enable prediction of long-term trends and to model some of the most important elements of diversity between connection points that are likely to impact on network performance and design below the 11 kV substation level. [Copyright &y& Elsevier]

• Temporal characterization of marine energy resources, at varying time scales. • Characterized wave, tidal, and ocean currents, and compared to wind and solar. • Data based exposition of grid benefits for wave power at high renewable scenarios. • Data based exposition of higher capacity adequacy and stability for wave power. • Detailed discussion on market implications of grid integration of marine energy. In this paper, the applicability of marine renewable energy (MRE) for potential grid applications is presented. We show that many of the unique value streams from marine-based electricity generation resources stem from their inherent temporal characteristics, especially when compared to wind and solar. Specifically, in this work, we evaluate the timing value for three types of MRE resources: (a) tidal, (b) wave, and (c) ocean currents. First, through a suite of novel metrics, such as resource availability, persistence, and versatility, we evaluate the temporal value characteristics of these resources. Second, through a more grid-oriented numerical study, we comment on the potential ramifications of those temporal characteristics in context of energy balancing and effective load carrying capability for one marine-based resource i.e., wave. Finally, we further our understanding of the relative advantages that may be leveraged by operating wave-based generation in tandem with more established renewable resources, such as wind and solar. Our results indicate that compared to wind and solar, MRE resources are consistently more available and persistent on an hourly level throughout an entire year of operation. In addition, wave resources are also seen to reduce the balancing requirements within the power system. Our work focuses on sites specific to the United States (US) and a parallel study for a location in Great Britain (GB). Results are found to be consistent for sites in both the US and GB, implying that the grid benefits discussed in this work could apply to a number of locations globally. [ABSTRACT FROM AUTHOR]

Decarbonisation is becoming a central aim of countries around the globe, ensuring the effects of climate change do not increase exponentially in the coming years. Renewable energy generation is at the core of this decarbonisation process, enabling economies to divorce themselves from a reliance on oil and coal. Hybrid energy systems can utilise multiple generation methods to supply electrical demand best. This paper investigates the use of localised hybrid energy systems around the UK, comparing the financial viability of solar, wind and hydrokinetic generation methods both as a hybrid system and individually in different scenarios. The significance of having localised hybrid energy systems is that they address two large problems within renewable energy generation, that of storage issues and also generating the electricity far away from where it is actually used, requiring extensive infrastructure. The microgrid optimisation software HOMER was used to simulate each of the generation methods alongside the national grid, including lithium ion batteries and converters to create a comprehensive hybrid system. Net Present Cost, which is the current value of all the costs of installing and operating the system over the project lifetime, was considered as the metric. The analysis finds that for each modelled location, wind turbines in combination with lithium ion batteries and a converter is the system with the lowest Net Present Cost, with the exception of Bristol, which also uses hydrokinetic turbines within the system. The findings indicate the extensive wind resources available within the UK, along with identifying that certain locations around the country also have very high potential for tidal power generation. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RES) are gradually becoming one of the key elements in the process of achieving energy efficiency worldwide. This trend can be observed in many developed Western economies—for example, in the United States, as well as in the United Kingdom. Hence, the role of innovative policies for promoting energy efficiency is becoming crucial in transition to the post-carbon economy. The shift to the carbon-free future make all actors to face forgoing commitments Nevertheless, customers and residential households are the first and the most important players in the pursuit of the energy-efficient future. Without them, carbon-free economy based on RES would never take the shape as envisaged. Our paper focuses on the innovative strategies and policies studying the effect and the scope of RES penetration into the households. We employ and empirical analysis of the effects from using RES in households using an example of the residential households in the northwest region of the United Kingdom (UK) with and without solar photovoltaic (PV) panels and electric vehicles (EV). We analyse the four scenarios that are aimed at analysing the system dynamics and providing differentiation between systems in terms of the varying values of the gross demand, tariffs, metered import, and the total revenue. Our results demonstrate that the solar PV leads to the transfer of costs and wealth regardless of the ownership of PV and EVs. Solar energy generation reduces the share of UK solar PV households per kWh costs of the distribution system which causes the augmenting of the per unit charges as well as to the changes in payments for the electricity that impoverishes less wealthy customer groups. It also becomes clear that with the increase of EV penetration, the existing energy efficiency schemes would have to be revised. [ABSTRACT FROM AUTHOR]

Taking the UK as a case study, this paper describes current energy use and a range of sustainable energy options for the future, including solar power and other renewables. I focus on the area involved in collecting, converting and delivering sustainable energy, looking in particular detail at the potential role of solar power. Britain consumes energy at a rate of about 5000 watts per person, and its population density is about 250 people per square kilometre. If we multiply the per capita energy consumption by the population density, then we obtain the average primary energy consumption per unit area, which for the UK is 1.25 watts per square metre. This areal power density is uncomfortably similar to the average power density that could be supplied by many renewables: the gravitational potential energy of rainfall in the Scottish highlands has a raw power per unit area of roughly 0.24 watts per square metre; energy crops in Europe deliver about 0.5 watts per square metre; wind farms deliver roughly 2.5 watts per square metre; solar photovoltaic farms in Bavaria, Germany, and Vermont, USA, deliver 4 watts per square metre; in sunnier locations, solar photovoltaic farms can deliver 10 watts per square metre; concentrating solar power stations in deserts might deliver 20 watts per square metre. In a decarbonized world that is renewable-powered, the land area required to maintain today's British energy consumption would have to be similar to the area of Britain. Several other high-density, high-consuming countries are in the same boat as Britain, and many other countries are rushing to join us. Decarbonizing such countries will only be possible through some combination of the following options: the embracing of country-sized renewable power-generation facilities; large-scale energy imports from country-sized renewable facilities in other countries; population reduction; radical efficiency improvements and lifestyle changes; and the growth of non-renewable low-carbon sources, namely 'clean' coal, 'clean' gas and nuclear power. If solar is to play a large role in the future energy system, then we need new methods for energy storage; very-large-scale solar either would need to be combined with electricity stores or it would need to serve a large flexible demand for energy that effectively stores useful energy in the form of chemicals, heat, or cold. [ABSTRACT FROM AUTHOR]