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A larger number of uncertain factors in energy systems influence their evolution. Owing to the complexity of energy system modeling, incorporating uncertainty analysis to energy system modeling is essential for future energy system planning and resource allocation. This study focusses on long-term energy system optimization model. The important uncertain parameters in the model are analyzed and divided into policy, economic, and technical factors. This study specifically addresses the challenges related to carbon emission reduction and energy transition. It involves collecting and organizing relevant research on uncertainty analysis of long-term energy systems. Various energy system uncertainty modeling methods and their applications from the literature are summarized in this review. Finally, important uncertainty factors and uncertainty modeling methods for long-term energy system modeling are discussed, and future research directions are proposed. [ABSTRACT FROM AUTHOR]

This paper represents the decentralised energy order as a matter of care: so as to make visible the unequal burden of care and to encourage active caring. It extends an emerging overlap that exists in studies of repair and maintenance of material objects from science and technology studies (STS) and an increasing interest in the creation and maintenance of relationships of care in energy systems. Inspiration is drawn from feminist STS work that calls attention to the continuous labour of repair and maintenance necessary to enact and sustain a socio-technical order. Fieldwork involved virtual interviews and small focus groups with 55 Australian householders who purchased decentralised energy technologies (solar, batteries and electric vehicles) and 18 intermediaries from industry and civil society. The analysis exposes how invisible care practices not only underpin householders' material engagement with the energy system, but also how they are inextricably entangled with making a decentralised energy 'order' work in practice. Relying on 'good hearted' intermediaries is unlikely to be a workable basis for a functioning and fair energy system. An alternative approach is called for: an exploration of what a caring decentralised energy system might look like. [ABSTRACT FROM AUTHOR]

Composed of multiple integrated energy systems (IESs) belonging to different stakeholders, multi‐agent IESs (MA‐IESs) are widely concerned because of data privacy protect. As the basis of planning design and reliability evaluation for MA‐IESs, distributed energy resource coordination (DERC) problem is studied in this paper. First, a DERC model for MA‐IESs is established, which considers energy conversion process specifically. Meanwhile, a novel distributed accelerated descent (DAD) algorithm is proposed to realize fully distributed solving. Different from most of the existing researches that investigate the DERC with box constraints, the presented algorithm is able to solve the DERC with general convex constraints. Moreover, the backward operators in the method improve the convergence rate to the best of distributed first‐order optimization algorithm with fixed step size, O(1/T). Furthermore, the presented approach is initialization robustness when the load fluctuations suddenly happened in MA‐IESs. The convergence property, computing, and communication complexity are strictly proved. Finally, the effectiveness of DERC model and DAD algorithm are demonstrated by some modified case studies. [ABSTRACT FROM AUTHOR]

The temperature-dependent diffusion coefficient of interstitial helium in zirconium carbide (ZrC) matrix is calculated based on the transition state theory. The microscopic parameters in the activation energy and prefactor are obtained from first-principles total energy and phonon frequency calculations including the all atoms. The obtained activation energy is 0.78 eV, consistent with experimental value. Besides, we evaluated the influence of C and Zr vacancies as the perturbation on helium diffusion, and found the C vacancy seems to confine the mobility of helium and the Zr vacancy promotes helium diffusion in some extent. These results provide a good reference to understand the behavior of helium in ZrC matrix. [ABSTRACT FROM AUTHOR]

This work objective is to evaluate the energy system and water circulation in Quintín Bandera factory. As a result of energy evaluation and the condensed system, the equipment's vapor consumption were determined. As a result the boiler generation was 136 761.41 kg/h, whit an efficiency of 78%. Fuel demand and generation index in boilers were 57 628.10 kg bagasse/h and 2.38 kgv/kgb respectively. The condensed generated quantity was determined as 179 215.97 kg/h which is enough to replace the necessity of water to feed the boilers. By means of the energy balance it was determined that 19 291.92 kg/h are vapor losses in condensation, from the general boilers vapor line to the Electric Plant and from it until process equipment. These losses are determined by the collector for general vapor with the suitable characteristics to evacuate the production from three boilers absence, as well as the insufficient thermal isolation for pipes and equipment, besides vapor losses and atmosphere flights. [ABSTRACT FROM AUTHOR]

Volume dependence of the total energy and vibrational properties of crystalline l,3,5-trinitro-l,3,5-triazine (RDX) are calculated using the density functional theory (DFT). For this molecular crystal, properties calculated with a generalized gradient approximation to the exchange-correlation energy differ drastically from experimental values. This discrepancy arises from the inadequacy in treating weak van der Waals (vdW) interactions between molecules in the crystal, and an empirical vdW correction to DFT (DFT-D approach by Grimme) is shown to account for the dispersion effects accurately for the RDX crystal, while incurring little computational overhead. The nonempirical van der Waals density-functional (vdW-DF) method also provides an accurate description of the vdW corrections but with orders-of-magnitude more computation. We find that the vibrational properties of RDX are affected in a nontrivial manner by the vdW correction due to its dual role—reduction of the equilibrium volume and additional atomic forces. [ABSTRACT FROM AUTHOR]

A cast Mg–3Gd–0.6Zr alloy with microscale growth twins was designed successfully. After the alloy was annealed at 350°C for 1 h, the volume fraction of the growth twins was increased by approximately 120%. Gd solute atoms segregated on both sides of twin boundaries and facilitated their formation in the as–cast alloy. The formation mechanism of growth twins in the as–cast alloy was discussed in five aspects: the supersaturation of Gd solute atoms, the segregation ability of Gd, the composition of Gd, the nucleate sites of growth twins, and the total energy of the system. The growth twins elicited remarkable toughening effect but a moderate strengthening effect on the alloy. [ABSTRACT FROM AUTHOR]

Abstract The development of sustainable system strategies at the municipal level is a challenging task since various factors like the business portfolio, the technological progress, the actor base, the regulatory framework and the market status might influence the results of an assessment. Given the complexity, system interdependencies between different alternatives need to be considered. One possibility to support decision makers is to apply Energy System Optimization Models (ESOMs). This paper reviews selected ESOMs with a high level of modeling detail and thus with high spatial, temporal and contextual resolutions that can be applied to support the decision-making process at municipalities. The main objective is to identify modeling approaches and future challenges to design such systems using several modeling frameworks. First, necessary system elements and interrelations are elaborated based on existing municipal system descriptions. The requirements are included in the derived definition of Integrated Multi-Modal Energy System (IMMES). Second, selected ESOMs are analyzed in terms of the requirements of the system definition. In doing so, existing fundamental approaches are demonstrated. Third, challenges for new mathematical approaches are provided. This review shows that a few modeling approaches are quite prevalent. Future design of models can be directly based on these practices. Additionally, most of the reviewed ESOMs only fulfill certain requirements of IMMES with a more complex approach. Concluding, future ESOMs need to address six research challenges: integrated view, business modeling, spatial planning, complexity level, temporal resolution and uncertainty analysis. Highlights • Energy system optimization models support decision making at the municipal level. • Adequate models exhibit approaches which are able to abstract the deployment environment. • Modeling approaches of selected energy system optimization models are analyzed. • Assessment of modeling approaches regarding municipal system characteristics is given. • Future research challenges and initial solutions are outlined. [ABSTRACT FROM AUTHOR]

Abstract Studies show that energy efficiency should play a significant role towards achieving cost-efficient 100% renewable energy systems. One way to attain cleaner heating solutions for the future is to utilise waste heat from power plants and industry through district heating. In the European Union, approximately 50% of thermal energy is lost in conversion processes. This research paper investigates the potential for the implementation of district heating in a future energy system originally intended not to include district heating. The paper approaches the problem by utilising TIMES modelling to frame the initial future energy system. However, MARKAL/TIMES is not ideal to investigate the operation of different heating scenarios, due to a lack of hourly modelling. Hence, the study utilises EnergyPLAN to investigate the implementation of district heating as an alternative heating scenario to individual heating. EnergyPLAN allows for simulating the hourly operation of not only electricity systems but also heating systems. The study investigates the implementation of district heating in the CO2-80 scenario created with the Irish TIMES model. As the Irish CO2-80 scenario does not include district heating, this study uses EnergyPLAN to simulate an 80% reduction scenario, with and without district heating, to compare the operation of the two systems. A sensitivity analysis is included to reflect on the uncertainties of the study. The results show that a district heating solution is more fuel-efficient while more investment heavy, however the fuel savings more than compensates for the increased investments. In total, the district heating scenario is close to 300 M € cheaper in annual costs than the individual heating scenario for Ireland, and achieves a fuel efficiency increase of 3.5% in the whole energy system due to an efficiency increase in the heating sector. The article shows both the relevance of using multiple models, and the need to consider district heating in a future Irish energy system. Highlights • EnergyPLAN is capable of simulating energy systems identified in MARKAL/TIMES. • EnergyPLAN and Markal/TIMES combined enables better analysis of heating scenarios. • District heating can compete with individual heating in an Irish energy system. [ABSTRACT FROM AUTHOR]

Abstract Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimizing these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique fractional thermal runaway calorimeter (FTRC), designed to characterize said critical factors, was utilized to examine the TR behavior of 18650-format Li-ion cells representing a variety of manufacturers, chemistries, capacities, and safety features. Primarily, the impacts of bottom vent (BV) safety features, varied cell casing thickness, and Dreamweaver cellulose based separators were assessed for select cell types. A subset of cells also had an imbedded internal short circuiting (ISC) device to allow examination of TR behavior initiated at lower temperatures (i.e. closer to field failure conditions). The impact of bottom rupture on TR behavior was also examined for experiments that resulted in this non-standard failure mechanism. Statistical analysis of the results for each cell configuration reveals that a lognormal distribution effectively characterizes the variation of total TR energy release. Typically 20%–30% of the total energy yield is released through the cell casing with the remainder through the ejecta material. Higher energy cells tend to exhibit more violent ejections and less predictable TR events. Inclusion of a BV feature reduces the overall severity of the TR event and can increase the predictability. Results also suggest that the magnitude of the TR event may not be directly proportional to the stored electrical energy, but rather has additional dependence on other design and failure mode factors. Highlights • Li-ion cell thermal runaway characterized with fractional calorimetry techniques. • Results distinguish between energy released through cell casing vs. ejecta material. • Impacts of design variables on thermal runaway behavior are characterized. • Statistical analysis reveals the variability of total thermal runaway energy release. [ABSTRACT FROM AUTHOR]

Highlights • The complex EH model can be divided into several simple EH models. • The complex MES is highly decoupled. • The nonlinearity of a complex EH model caused dispatch factors can be eliminated. • The energy storage, demand respond and renewable energy are all integrated in the coupling matrix of EH model. Abstract The integration energy and information technology has prompted the development of the multi-carrier energy system. Energy hub model is widely used in the multi-carrier energy system study. However, it is the difficult to formulate coupling matrix and optimize operation state of complex energy hub model. This paper proposes an efficient standardized multi-step modelling method and linearized optimization method for the energy hub model. Firstly, a complex energy hub model is separated into several simple energy hub models based on nodes arrangement and virtual nodes insertion methods; then the coupling matrix of each simple energy hub model can be easily modelled; the coupling matrix of the complex energy hub model can be obtained by multiplying the coupling matrix of each simple energy hub model. In addition, energy storage, demand response and renewable energy are considered and integrated in the energy hub model. Further, the nonlinear optimal operation model of energy hub is reformulated to a linear programming problem by using variable substitution in each simple energy hub model. Cases study is performed on a resident district in a city of China on a typical summer day with the energy storage devices, demand response and renewable energy considered. Compared with the traditional calculation method, the computational burden is significantly reduced based on the proposed calculation method, which can guarantee the global optimal operation decision. [ABSTRACT FROM AUTHOR]

Summary: The charge, discharge, and total energy efficiencies of lithium‐ion batteries (LIBs) are formulated based on the irreversible heat generated in LIBs, and the basics of the energy efficiency map of these batteries are established. This map consists of several constant energy efficiency curves in a graph, where the x‐axis is the battery capacity and the y‐axis is the battery charge/discharge rate (C‐rate). In order to introduce the energy efficiency map, the efficiency maps of typical LIB families with graphite/LiCoO2, graphite/LiFePO4, and graphite/LiMn2O4 anode/cathode are generated and illustrated in this paper. The methods of usage and applications of the developed efficiency map are also described. To show the application of the efficiency map, the effects of fast charging, nominal capacity, and chemistry of typical LIB families on their energy efficiency are studied using the generated maps. It is shown how energy saving can be achieved via energy efficiency maps. Overall, the energy efficiency map is introduced as a useful tool for engineers and researchers to choose LIBs with higher energy efficiency for any targeted applications. The developed map can be also used by energy systems designers to obtain accurate efficiency of LIBs when they incorporate these batteries into their energy systems. Energy efficiency map for Li‐ion batteries (LIBs) is introduced.Determination of energy efficiency is important for LIBs operating at ≥C/2.This map can be used for selection of LIBs with higher efficiency.This map can be used to find the LIB efficiency when it is incorporated into an energy system.This map can be used to study effects of fast charging, capacity, C‐rate, and chemistry of LIBs. [ABSTRACT FROM AUTHOR]

Demand response (DR) has been recognized as a powerful tool to help mitigate power imbalances in a future smart energy system. This paper takes the point of view of a grid operator (GO) to establish an intraday resource trading framework, over which DR resources from different sectors (large industrial consumers and small- or middle-sized customers) are brought to the system level and are assessed by the GO along with the generators, with the aim of procuring the required system resources at minimal cost. Considering the distinct behaviors of the involved entities, Stackelberg game theory was adopted to analyze the coordination among the various decision makers. A unique Stackelberg equilibrium was identified that yields the optimal outcome for the resource trading game between the GO and demand-side participators. Simulation results demonstrated that the total procurement cost was minimized by applying the proposed approach. [ABSTRACT FROM AUTHOR]

The electricity output of combined heat and power (CHP) units is constrained by their heat output corresponding to customers’ heat demand, which makes it difficult for the CHP units to frequently adjust their electricity output. Therefore, additional balancing power is required to integrate the variable wind power in the CHP-based heat and electricity integrated energy system (HE-IES). This paper expands the demand response (DR) concept to the HE-IES. A comprehensive DR strategy combining energy substitution and load shifting is first developed to exploit the demand flexibility of smart buildings. Besides electric balancing power, heat balancing power is also provided to relax the production constrains of CHP units. Moreover, a real-time DR exchange (DRX) market is developed where the building aggregators are stimulated to adjust buildings’ energy consumption behaviors and provide the required balancing power. Compared with the existing day-ahead DRX market, the real-time DRX market can balance the very short-term wind power fluctuation and reduce price spikes. Additionally, a novel optimum feasible region method is proposed to achieve the fast clearing of the DRX market to meet the higher requirement for clearing speed in the real-time market. Simulation results verify the advantages of the proposed technique. [ABSTRACT FROM AUTHOR]

Highlights • An novel active method is proposed for the mitigation of induced voltage. • The circuit-model analysis is conducted for the characteristics of induced voltage. • The idea and the theoretical analysis of the active mitigation method are presented. • The practical issues for real-world implecation are investigated. • An active mitigation device is developed to validate the active method. Abstract The emerging integrated energy systems accelerate the coupling of natural gas-electricity networks. Both pipeline and power companies are drawing increasing attention to the voltage induction on pipelines caused by powerline currents. This paper proposes a novel active method for mitigating induced voltage along pipelines. This method employs controllable voltage generators to apply proper voltage to pipeline and mitigate the induced voltage from nearby power lines. The applied voltage can be adjusted by the embedded feedback controller according to the measured voltage. By solving the coordination and interference issues, the whole active mitigation system is established. This paper provides the case study, the experimental study and the results to show the capability of the proposed method. [ABSTRACT FROM AUTHOR]

Highlights • A new system identification method called DITER to detect defects in structures. • Employing an element-wise, time domain-based approach. • A robust method against static deflection variation and uncertainties. • Numerical verification of the DITER method on a two-span beam sample. Abstract This paper presents a new system identification method called Damage Identification based on Total Energy Rate (DITER) to detect defects in structures. The proposed method employs an element-wise, time domain-based approach. Identification of elemental structural properties is performed through least squares optimization of an objective function created from the rate of total energy of the targeted elements. Using the total energy rate allows for a significant simplification in creating the objective function as compared to previous approaches that rely on equations of motion. Moreover, introduction of boundary elements' contribution in the derived objective functions makes the method flexible. As a result, it can be applied either to the whole structure or to any specific portion of the structure. In this novel approach, DITER converts displacement data into total displacement, measured from the undeformed configuration of the structure, by introducing static deflection correction terms. Thus, the proposed method is robust against static deflection variation and eliminates uncertainties in the initial displacement values. Numerical verification of the DITER method was performed on a two-span beam sample. Based on the results, DITER can be used as an efficient tool for nondestructive damage detection in existing structures. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a discrete single-axis solar tracking system that only actuates three times a day in the azimuthal plane to follow the sun. The preset tracking angles for the system are based on simulation runs for the site with incorporation of weather data to find optimum angles of discrete tracking. Simulation results indicate that there are no significant differences in total solar energy generation when using tracking angles based on either the isotropic or anisotropic models. Moreover, experimental results in the summer season showed that tracking the sun in only three optimized angle movements yielded around 91–94% of solar energy collection as a continuous single-axis solar tracker that moves three times an hour based on solar calculations. Experimental results agree within 11–17% with simulation data. Highlights • The effect of a PV discrete solar tracking technique on system performance and total energy gain compared to an identical single-axis tracking approach. • Discrete and continuous systems tracking angles are obtained from simulations based on typical solar conditions. • Theoretical and experimental results show no significant impact of using either Isotropic or Anisotropic models on the total energy collection of the tracking system. • Experiment results show that implementing a three step per day discrete tracking technique achieves around 91-94% of solar energy collection. • Potential of discrete solar trackers is clearly demonstrated as the number of tracker actuations is reduced dramatically relative to a continuous tracker. [ABSTRACT FROM AUTHOR]

Abstract To achieve carbon neutrality by 2025 the University of California, Davis (UCD) seeks to eliminate its dependence on fossil energy sources. This study outlines a methodology to identify optimal equipment phase-in and capacities, and the major technical and economic drivers influencing the implementation of a carbon-neutral energy system. The analysis, focused on UCD, considers solar photovoltaic and thermal, biomass combined heat and power, biomass boiler, heat pump and electric boiler as replacement systems. Three cases besides the baseline are presented: 1) biomass-based system, 2) combination of biomass and electrification, and 3) electrification. Analysis period spans 2016–2035, with equipment phasing limited to the 2020–2025 period, and capacity limited to the peak campus loads of 40 MW e for electricity and 80 MW t for thermal. Results indicate that balancing the supply-demand mismatch is the greatest challenge for high renewable penetration at UCD, thus making thermal storage and generation systems which can modulate with variable loads crucial. The cost of carbon credits offset has negligible influence in the results due to its low value in the present market. Relative to the baseline 20-yr present cost of $634M, the 3 alternate cases are projected to incur between $629M (Case 1) and $704M (Case 3). Highlights • Supply-demand mismatch is the greatest technical challenge for the campus. • Thermal storage and generators that can modulate quickly based on load are crucial. • NPC of alternate systems ranges $629M-$704M, relative to the baseline $634M • Carbon cost need to exceed $170/ton CO 2 to break even on the costliest option. [ABSTRACT FROM AUTHOR]

Abstract Developing net-zero energy communities powered by renewable energy (RE) resources has become a popular concept. To make the best choices for community-level net-zero energy systems, it is necessary to identify the best energy technologies at local level. Evaluation of RE technologies has to be extended from technical and economic aspects to include environmental and social wellbeing. It is possible to identify the true costs and benefits of energy use by taking a cradle-to-grave life cycle perspective. In this study, a RE screening and multi-stage energy selection framework was developed. A fuzzy multi-criteria decision making approach was used in ranking the technologies to incorporate the conflicting requirements, stakeholder priorities, and uncertainties. Different scenarios were investigated to reflect different decision maker priorities. Under a pro-environment scenario, small hydro, onshore wind, and biomass combustion technologies perform best. Under a pro-economic decision scenario, biomass combustion, small hydro, and landfill gas have the best rankings. Triple bottom line sustainability was combined with technical feasibility through a ruled-based approach to avoid the theoretical pitfalls inherent in energy-related decision making. This assessment is geared towards providing decision makers with flexible tools, and is expected to aid in the pre-project planning stage of RE projects. Highlights • Energy planning needs to be done at community level for optimal outcomes. • Considering life cycle impacts and uncertainty is important in energy planning. • Different decision scenarios were considered in selecting technologies. • Small hydro and biomass perform particularly well for British Columbia. • The developed method provides decision makers with flexible planning tools. [ABSTRACT FROM AUTHOR]

Abstract Power-to-gas is a key area of interest for decarbonisation and increasing flexibility in energy systems, as it has the potential both to absorb renewable electricity at times of excess supply and to provide backup energy at times of excess demand. By integrating power-to-gas with the natural gas grid, it is possible to exploit the inherent linepack flexibility of the grid, and shift some electricity variability onto the gas grid. Furthermore, provided the gas injected into the gas grid is low-carbon, such as hydrogen from renewable power-to-gas, then overall greenhouse gas emissions from the gas grid can be reduced. This work presents the first review of power-to-gas to consider real-life projects, economic assessments and systems modelling studies, and to compare them based on scope, assumptions and outcomes. The review focuses on power-to-gas for injection into the gas grid, as this application has specific economic, technical and modelling opportunities and challenges. The review identified significant interest in, and potential for, power-to-gas in combination with the gas grid, however there are still challenges to overcome to find profitable business cases and manage local and system-wide technical issues. Whilst significant modelling of power-to-gas has been undertaken, more is needed to fully understand the impacts of power-to-gas and gas grid injection on the operational behaviour of the gas grid, taking into account dynamic and spatial effects. Highlights • Review found great interest in power-to-gas (P2G) & H 2 injection into the gas grid (HIGG). • Strong potential for P2G & HIGG to increase penetration of renewables in energy system. • Studies generally agree that efficiency of P2G and HIGG will increase by 2030. • Electricity balancing market and government support will drive viable business cases. • There is a lack of whole-systems optimisation studies with HIGG and linepack storage. [ABSTRACT FROM AUTHOR]

Highlights • Novel methodology to endogenise modal shift in energy system models. • Substitution elasticities are adopted to regulate transport modal shares. • Modal demands self-adjust elastically in response to shadow price changes. • Sensitivity analysis on elasticities reveals substitution saturation. • Interactions between novel methodology and traditional model structure explained. Abstract Several efforts have been directed lately towards the endogenisation of transport modes competition in Energy/Economy/Environment/Engineering (E4) models. TIMES-DKEMS is a novel methodology paving the way for applying elasticities of substitution to incorporate transport modal shift into TIMES (The Integrated MARKAL-EFOM System) models. Substitution elasticities are defined for four transport demand aggregates, each corresponding to a different distance range class. Within an aggregate, modal demands can adjust their levels according to the defined substitution elasticity and in response to changes of their shadow prices relative to a reference case. The total volume of the transport demand over the aggregate is conserved and modal shift potentials are implemented to guarantee realistic dynamics. The behavior of TIMES-DKEMS is tested under an arbitrary environmental policy, an increasingly stringent bound on CO 2 emissions. Modal shares are compared with the standard version of TIMES-DK. Results show that in 2050, 11% of car mobility demand is substituted by more efficient and less costly modes such as train and coach. A sensitivity analysis on the values of substitution elasticities indicates that higher absolute values correspond to larger modal shift. Finally, other model constraints, such as mode-specific travel patterns, interact with the substitution mechanism resulting in a modal shift containment. [ABSTRACT FROM AUTHOR]

Abstract The GAS-function methodology is introduced in this paper in order to identify the sustainability objective function for optimisation of multiple interconnected complex steam turbines and utility network (ICSTUN) systems. Also, the complex steam turbine was modelled based on induction machine operation which enhances its performance. The boiler models were identified as the sustainability objective function which was further investigated under given operating constraints for optimisation of the ICSTUN system. The validated results show that relative error between field operation and simulation data were less than 1% on average, which is acceptable for engineering applications. The optimisation results indicate that contrary to previous authors' results and by comparing with actual field operational data information, coal flow rates for total site utility system of this investigated ICSTUN can be significantly reduced. It was therefore concluded that a significant reduction in the coal flow rate amounts is practicable in order to significantly reduce operating costs as well as the environmental and social issues associated with utilising fossil-fuels, while still satisfying the demand-side management objectives for the plant. Highlights • The GAS-function methodology is introduced for analysis of ICSTUN systems. • This model combines basic equations with matrix steam tables for analysis of the system. • The model is practical with the actual energy system based on data acquisition methods. • The results show that induction machine operation enhances the turbine performance. • The results also indicate that fossil-fuel consumption rates can be significantly sustained. [ABSTRACT FROM AUTHOR]

Abstract With the revolution of the traditional economic and social pattern based on centralized fossil energy consumption, the regional integrated energy system (RIES) has gained rapid development in recent years for achieving higher energy efficiency. This paper expands the Demand Response (DR) concept to the RIES and presents an optimal operation model of RIES considering the DR mechanism on the energy price. In this paper, a comprehensive DR strategy combining energy price and different loads is firstly developed to exploit the demand flexibility of RIES in the DR model established. Based on the DR modeling of the RIES, an operation optimization model with environmental, economic benefits and energy supply reliability as objective functions has been firstly established in detail. Secondly, a complete scheduling scheme is built based on the energy consumption characteristics and system operation characteristic of the integrated energy system. The model presented could reduce the cost of system without causing a significant amount of environmental pollution, and improve the energy efficiency of the RIES efficiently. Besides, the scheduling strategy proposed could also provide support for the operation strategy of integrated energy system under the energy development. Hopefully, this paper will provide reference for future research and engineering projects on DR programs in the RIES. Highlights • The typical structure of the RIES is introduced. • A DR model suitable for the RIES considering different loads is established. • An optimal operation model of the RIES based on DR is established. • The load in the RIES is affected not only by energy price but also by other loads. [ABSTRACT FROM AUTHOR]

Abstract District energy systems are a central element in transforming the energy system towards a low-carbon system. Simulation is regarded as key method for concept development and assessment as well as for operational optimization to address the growing complexity of these systems and to derive quantitative feedback e.g., as input for decision-support or operational processes. In this paper we present a comprehensive comparison of four widely used general-purpose modelling tools for district-scale energy systems, including a detailed discussion of modelling paradigms and co-simulation capabilities. This comparison is based on an extensive literature review, a comprehensive questionnaire that was conducted by tool and library developers, as well as a comparison of pipe model behavior of various libraries against measured data. The results including the experimental data are openly available and can support users in academia and industry with the selection of suitable modelling paradigms and associated tools and libraries. [ABSTRACT FROM AUTHOR]

Abstract An overview of recent developments, trends and challenges in the synthesis, design and operation optimization of energy systems is presented in this manuscript. The static and dynamic optimization problems are stated mathematically, solution methods are mentioned in brief and classification of optimization problems based on the presence and treatment of time is presented. Examples of objective functions in single-objective optimization are given and the need for multi-objective optimization is highlighted. Special reference is made to Prof. Szargut's early statement about the need for optimization with ecological concerns. Emphasis is given to optimal synthesis of energy systems, a subject that is still between (or combines) art and science/technology. Furthermore, it is interesting to note that optimization is applied also during the development of models of systems. Hints are given on further considerations and research needs in subjects such as global optimization, as well as optimization with uncertainty, reliability, maintenance and social aspects. Examples of algorithms appearing in recent publications are given as an indication of the related strong activity. The manuscript closes with general remarks and a rather comprehensive, even though not exhaustive, list of references. Highlights • A variety of methods and algorithms for optimization of energy systems is available. • Optimization problems become more and more complex. • Development of effective and efficient algorithms for global optimization is still needed. • Synthesis optimization is challenging. • Introduction of reliability, maintenance and social aspects in optimization is needed. [ABSTRACT FROM AUTHOR]

Abstract The research presented in this paper aims to assess the technical effectiveness of demand response as a demand-side flexibility option to mitigate variability in the energy system in Finland in 2030. The results show that heating loads can provide a significant long-term technical potential for demand-side resource capacity. This demand-side resource capacity is not always available, as it varies according to the season and time of the day. The temporal availability of demand-side resource capacities varies between 80 and 5600 MW. Furthermore, the results show that the utilisation of demand-side resource capacity decreases significantly when the shifting time interval becomes more constrained. The utilisation of demand-side resource capacity results in balancing of residual demand in the day-ahead market, and thus more efficient utilisation of wind power generation in the Finnish power market. This smoothing effect reduces operating hours of thermal power production and the need for cross-border balancing by electricity imports during the peak hours. According to the sensitivity analysis, the ramping occurrences of district heating CHP units increase significantly with increased share of inflexible baseload nuclear power, while some of the efficiency gains can leak to the neighbouring countries. Highlights • Demand response can be utilised in VRE integration. • Demand response can substitute peak production capacity. • Demand response can reduce the need for cross-border balancing. [ABSTRACT FROM AUTHOR]

Abstract Optimal control and design of energy systems in some instances require the fast exergoeconomic optimization. Fuzzy inference systems (FIS) were previously employed for either the computerized iterative exergoeconomic optimization or fast optimization of the energy system. The shortcoming of the FIS system was that the requirement to have numerous fuzzy rules and fuzzy membership function that must be collected based on experts' knowledge and usually with try and error steps. On the other hand, conventional optimization methods such as genetic algorithm consume significant calculation time that makes them unsuitable for the fast optimization. In this paper, the adaptive neuro-fuzzy interference system known as the ANFIS was introduced for fast exergoeconomic optimization of energy systems. The ANFIS system automatically developed the required fuzzy items and used them for fast optimization of energy systems. It was employed on two case studies, one for exergoeconomic design and optimization of a benchmark energy system known as the CGAM problem. It was shown that the ANFIS could achieve the optimal solutions of systems with reasonable accuracy, very low computation time, and without dependency on experts' knowledge to develop fuzzy data. The ANFIS was found as an optimistic alternative for the fast optimization of energy systems. Highlights • A methodology based on adaptive neuro-fuzzy inference system, ANFIS, is developed. • The developed ANFIS method is introduced for exergoeconomic optimization. • It was found that the ANFIS could be used for real-time optimization. • It has superior features over the conventional optimization and fuzzy methods. • It has no requirement for knowledge of experts to develop fuzzy data. [ABSTRACT FROM AUTHOR]

Highlights • An overview of the state of the art in community energy storage (CES) is provided. • CES is conceptualized and analyzed as complex socio-technical system. • Responsibility in CES design and implementation is operationalized. • CES is not only technical but also social innovation. • The added-value of CES go beyond economic benefits to wider societal benefits. Abstract The decreasing cost of energy storage and increasing demand for local flexibility are opening up new possibilities for energy storage deployment at the local level. Community energy storage (CES) is expected to contribute positively towards energy transition while accommodating the needs and expectations of citizens and local communities. Yet, the technological and societal challenges of integrating CES in the largely centralized present energy system demand for socio-technical innovation. In this article, we develop and discuss several configurations of CES. Applying system innovation and socio-technical transition frameworks and conceptualizing CES as a complex socio-technical system, different dynamics of CES in the energy systems such as coordination and interaction among actors and components of CES and the larger energy system is explored. The responsible research and innovation (RRI) framework can provide a new discourse in design and implementation of CES, facilitating the transition to a sustainable, reliable, inclusive and affordable future energy system. [ABSTRACT FROM AUTHOR]

Highlights: • A robust optimal method for distributed energy system (DES) design considering uncertainties is developed. • The life-cycle performance of DES is used as the design optimization objective. • Uncertainties of design inputs and equipment degradation are quantified. • A probabilistic approach is adopted to perform the process of the robust optimal design. • Advantages of this proposed design method in DES planning are provided. Abstract Uncertainties in design inputs (i.e. energy demand and energy price) and equipment degradations in operation result in that the actual performance of distributed energy systems (DESs) deviates from the design expectations significantly. To ensure that DESs designed can operate at high performance when the actual working environment and equipment performance change over a large range, a robust optimal design method based on life-cycle performance analysis is developed. This method adopts a probabilistic approach, which is based on qualifying the uncertainties of design inputs and equipment degradations, while Monte Carlo simulation method is adopted to model the uncertainty propagation and generate the probability distribution of the predicted DES performance in the design process. The "probabilistic" life-cycle performance of DES is therefore obtained and used for the robust optimal design. The method further identifies the optimum DES which has the best life-cycle performance expectation under the above conditions concerned. A case study is conducted on the DES design in a district in Hong Kong to test the application of this method. It is found that, compared with other schemes, the optimum DES has least life-cycle total cost and better robustness of performance under different operating conditions. The DES identified by this method achieves economic benefits and higher total system energy efficiency in the latter years of its life-cycle compared with the DES identified by optimal design method without considering the life-cycle performance. Conclusions of this study can be also used as references for DES life-cycle performance assessment for DES designers. [ABSTRACT FROM AUTHOR]

Highlights • A multi-energy management method with energy complementarity prosumers was proposed. • A multi-objective optimisation framework was developed to reduce total energy cost. • The economic impact of the energy complementarity strategy was investigated. • The new method could promote the sustainable development of the urban energy system. Abstract The increasing complexities of energy internet integrated with distributed renewable energy resources and multiple energy infrastructures require more effective multi-energy management method. The prosumers with multiparty interaction represent major potential contributors for comprehensively improving the energy efficiency and socioeconomic benefits. In this paper, a novel multi-energy management strategy based on the complementarity of multi-energy demand was proposed to explore optimal energy scheduling problems of prosumers. The residential prosumer with a multi-energy coupling matrix and the industrial prosumer with a resource-task network were formulated to optimise the local operations. Furthermore, a joint planning for the prosumers was developed to minimise the global operating costs, where the prosumers' interests in terms of the energy exchange process were formulated as a multi-objective optimisation problem based on the Pareto efficiency theory. In addition, an optimisation method that integrates the epsilon-constraint algorithm and the extreme points of the feasible solution space was proposed to obtain better and more diverse solutions. The proposed methodology was applied to an urban multi-energy system. Simulation results demonstrated that the proposed multi-energy management method could effectively solve the optimal energy scheduling problems. At the compromise solution point, cost reductions of 7% and 10% can be obtained by the two prosumers on a summer day, with cost reductions of 9% and 11% obtained on a winter day. The use of multi-energy management method could establish a win-win relationship for prosumers and generate substantial benefits for the whole system. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Propose novel benefit allocation constraints inspired from Game-theory. • Integrate benefit allocation constraints with multi-objective optimization. • Quantify the difference of considering the benefit allocation or not. • Build a flexible neighborhood urban energy network optimization model. • Compare centralized installation mode and distributed mode. Abstract By connecting stand-alone energy systems, the neighborhood-level urban energy network can serve several buildings in a more economic and ecological manner. In some cases, in order to achieve the best performance of the entire network, the benefit of some buildings within the network may not be guaranteed. Few attentions have been paid to the benefit allocation fairness for energy networks. This study proposes novel cost and emission benefit allocation constraints inspired from cooperative Game theory to ensure that each involved building shares the benefit together. A Mixed Integer Linear Programming (MILP) model is developed to investigate the impacts of benefit allocation constraints. The model offers different network topologies, i.e., centralized mode and distributed mode. Multi-objective optimization and decision-making are further conducted to assess the trade-offs between different objectives via generating the Pareto frontier. Through an illustrative case study, a three-building neighborhood-level energy network is optimal designed in Shanghai, China. The results indicate that when benefit allocation is considered, the solution space will slightly shrink compared to the scenario not considering benefit allocation. Meanwhile, distributed mode achieves better performance than the centralized mode. Overall, the analyses provide a solid approach to enhance infrastructure planning for urban energy networks particularly when the stakeholders of each participating building within a network are different. [ABSTRACT FROM AUTHOR]

Highlights • Computationally efficient method proposed to characterise latent storage units. • Model validated using two different salt hydrate based latent storage devices. • Model applicable with analytic equations for effective conductivities. • High accuracy proven without calibration. • Approach suitable for annual energy system simulations with latent storages. Abstract Latent storages utilising phase change materials (PCM) to store thermal energy offer a considerably higher energy density at a nearly constant temperature level in comparison to sensible storage systems. Despite this advantage, only a few latent storage technologies have been integrated successfully to the market. This may be due several engineering challenges and in particular the lack of a computationally fast and accurate mathematical model to facilitate the optimal incorporation of latent heat storages into an energy system. The presented study fills this gap and proposes a new, fast and experimentally validated mathematical modelling approach for latent heat storage units. The numerical model proposed combines high accuracy, low computational effort and numerical stability. The validation was performed with two different commercial latent storage units supplied by Sunamp Ltd. with a nominal phase change temperatures of 34 °C and of 58 °C. Both units use a salt hydrate based phase change material in combination with a fin-tube heat exchanger. The proposed model may be used for both fast system level performance investigations as well as latent storage design for a given application. It may therefore be implemented in commercial software packages such as TRNSYS [1] or Simulink [2]. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Long-term (hydrogen) and short-term (batteries and thermal) storage are evaluated. • Multi-objective optimization platform minimizes both costs and CO 2 emissions. • Optimal solutions for neighbourhoods are compared against national CO 2 targets. • Three future scenarios between 2015 and 2050 are developed predict future outcomes. • Two test decentralized neighbourhoods (one urban and one rural) are compared. Abstract The potential of both long-term (hydrogen storage) and short-term (batteries and thermal) storage systems in decentralized neighbourhoods are assessed using a multi-objective optimization approach that minimizes both costs and CO 2 emissions. A method is developed, which evaluates the performance of long and short-term storage systems in the future based on multi-objective optimization. More specifically, hydrogen storage is investigated for its future potential to be used as a long-term storage in a decentralized context and it is compared with short-term storage systems such as batteries and thermal storage. In order to analyze potential future developments, a scenario approach is deployed based on the Intergovernmental Panel of Climate Change's 'Special Report on Emissions Scenarios'. Three future scenarios are defined and simulated for the years of 2015, 2020, 2035, and 2050 for both a rural and an urban neighbourhood in Switzerland. Based on the scenarios, the energy demand and renewable potential projections until 2050 are simulated including retrofitted buildings and renewable potential in the neighbourhoods. The Pareto front of solutions is then benchmarked against national carbon and energy targets from 2020 until 2050. In addition, a range of parameter assumptions (e.g., for economic variables, policy changes, environmental conditions) are used in each scenario to incorporate uncertainty into the analysis. The long-term storage potential of hydrogen, in particular, is evaluated for its capability to shift renewable surpluses in summer towards demand later in the year. From the results, it is predicted that neighbourhoods with high renewable surpluses (i.e., in rural settings) should consider the advantages of a hydrogen storage system from 2035 to 2050. For neighbourhoods with low surpluses, short-term battery and thermal storage systems are predicted to be sufficient for load shifting. It is also observed that a high feed-in remuneration undermines on-site consumption, thus resulting in lower levels of storage deployment due the selling of production back to the centralized electricity grid. Lastly, it is concluded that both an increase in renewable technology deployment and in the retrofit rate of buildings will both be required to meet energy targets for the two case studies. As the renewable potential in urban contexts is limited, it is particularly important for older building stock to be retrofitted at a high rate (more than 2% of buildings per year) in order to reduce the end energy demand of the buildings. The approach used in this article is widely applicable both in spatial scope (e.g., other decentralized energy systems, geographies) and temporal scope (e.g., different years, scenarios) and allows for an optimization with a range of objective functions, thus making it an effective approach to identify the renewable and storage technologies that can contribute to most of the decarbonization of the building stock in the future. [ABSTRACT FROM AUTHOR]

Abstract To maximize the environmental performance of the energy systems, a paradigm change towards the concept of smart multi energy systems is needed. Optimal planning, design and operation of such energy systems, which efficiently integrate different energy sources, vectors and needs, is intrinsically a multi-objective problem in terms of sustainability. In this study, a decision support system based on performance indicators and Pareto multi-objective optimization is developed. System design combines renewable energy sources and combined cooling heat and power serving a cluster of firms through district energy distribution networks. Results show that the model enables the analysis of the trade-off between the different objective functions, allowing to identify the optimal energy systems layout through the selection of the proper size of the generation units. It also provides design directions such as the thermal energy storage capacity. The case study evidences that the smart energy systems concept can really represent a main opportunity to industrial districts both from the sustainability and the competitiveness perspective. Research also suggests that some financial incentives should be studied so that the solution providing the largest energy saving and carbon dioxide emission reduction could improve its economic attractiveness. Highlights • A framework for planning and design of smart multi energy systems is proposed. • The multi-objective optimization method is based on indicators and Pareto analysis. • Sustainability is evaluated. • The method was applied on a food industrial district. • Smart multi-energy system solution based on distributed generation. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A novel approach is presented to construct energy and waste scenarios. • Joint scenarios are used in prospective life cycle assessment of waste management. • The approach relies on existing energy scenarios and waste storylines. • Waste storylines are developed in close interaction with stakeholders. • The approach is applied to the case of Swiss municipal solid waste management. Abstract Multiple international and supranational organizations call upon changes in current waste management practices to play a key role in developing more sustainable economies. Life cycle assessment (LCA) is a popular method used to assess the sustainability of future waste management options. The uncertainties about future energy systems and waste compositions, however, may lead to ambiguous LCA results. One way to deal with this challenge is the development of joint energy and waste scenarios to investigate the robustness of waste management options. To date, joint energy and waste scenarios rely on the integration of large economic and engineering models. Complex models can hamper the transparency required for decision-makers to understand and implement LCA recommendations. Here we present the alternative of combining diverse energy scenarios and stakeholder-based waste storylines. This is a more qualitative approach than previous sustainable energy/waste evaluations and has a double aim: to address upfront the energy and waste composition sensitivity and enhance transparency by both relying on well-documented energy scenarios and involving stakeholders in the waste storyline formulation. We apply the approach to the Swiss municipal solid waste (MSW) management system in the context of the energy transition away from nuclear power. Three energy scenarios capture how radical the transition might be, while the storylines reflect societal developments and waste policies leading to low, high, and average MSW amounts. The approach delivers feasibility spaces of energy systems and waste compositions as input to the LCAs. It ensures a high level of transparency, which, in conjunction with the participation of decision-makers, has the potential to increase the chances of implementation of the recommendations based on LCA results. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a new method, based on the Smart Energy Systems concept. The aim is to increase the share of renewable energy penetration on islands. The method is applied to the island of Gran Canaria (Spain), considering the entire energy system of the island. Several smart renewable energy strategies are proposed following a cross-sectoral approach between the electricity, heating/cooling, desalination, transport and gas sectors. The different smart renewable energy strategies were applied in a series of steps, while looking for a transition from the current energy system to a nearly 100% renewable energy system. Based on the results, the study concludes that the suggested method is applicable for increasing renewable integration on islands and can potentially be used in helping energy planners to take decisions about priorities in development of the sector to improve such integration. The results indicate that, for the case of Gran Canaria, a 75.9% renewable energy system could be attained with technologies that can be implemented at present. Furthermore, it is shown that a nearly 100% renewable energy system in Gran Canaria is technically feasible and could be achieved if certain technologies acquire greater maturity. Highlights • A new Smart Renewable Energy approach for islands is presented. • A cross-sectoral method is proposed to increase the renewable energy on islands. • A new strategy is used to select the optimal energy configuration for each scenario. • The more demand becomes manageable, the more the proposed method increases PV power. [ABSTRACT FROM AUTHOR]

Abstract The modernization of the grid and increased renewable penetration had led to a requirement of alternative tariff mechanisms for the consumers. The increasing PV deployment trend, as well as implementation of smart meters under smart grid pilot projects in India, opened up avenues for alternative retail rates and net metering policies. The rooftop PV deployment had led to an increase in the number of net metered consumers. The present work studies the impact of different retail rate mechanisms on bill savings of net metered consumers, with increasing solar penetration scenario. Seven different scenarios, based on increasing solar penetration in the energy mix, are designed. After simulating wholesale electricity prices through a unit commitment based energy system model, retail rates (two time-invariant and three time-variant) are designed using simulated electricity prices. To evaluate the impact of increasing PV penetration on consumer economics, the electricity bills of 97 net metered consumers are calculated using designed retail rates for all the scenarios. It is observed from the results, that the value of bill savings decreases with increasing PV penetration for all the retail rates. Also, the decrease in the value of bill savings is more in time-variant rates as compared to time-invariant rates. Highlights • Scenario analysis with varied penetration for solar are considered. • Wholesale electricity prices are modeled through energy system model. • Five types of retail rates are modeled using simulated wholesale electricity prices. • Based on the designed retail rates, savings of net metered consumers are calculated. [ABSTRACT FROM AUTHOR]

A single-inductor multiple-output (SIMO) dc–dc converter with output-voltage-aware charge control (OVACC) is presented in this paper. The OVACC scheme reduces the cross regulation by computing the total energy required by all outputs to extract exactly the same amount of energy from the input. Moreover, the proposed design also extends the load capability range of the SIMO converter by supporting the operation in both continuous conduction mode and discontinuous conduction mode while boosting the overall power efficiency. The proposed SIMO (five outputs) dc–dc converter has been implemented in a 0.18 μm 1P6M CMOS process. Measurement results show that the best cross regulation is 0.016 mV/mA when the output current of 250 mA abruptly changes. And no cross regulation is observed when the first output current changes 150 mA, the second output current changes 160 mA, the third and fourth output currents change 180 mA, and the last output current changes 250 mA. Also, the measured peak power efficiency is 86%. [ABSTRACT FROM AUTHOR]

Highlights • A northern energy model has been developed for the Yukon Territory. • Uncertainties and complexities in the Yukon energy system are discussed. • The impact analysis of policy implementations is conducted. • Optimal strategies are obtained for energy planning and GHG mitigation. Abstract This study developed an inexact optimization modelling approach for supporting regional energy systems decision-making and greenhouse gas emission mitigation under uncertainty. The developed model integrates multiple inexact optimization programming approaches, incorporating interval linear programming, mixed-integer programming, and chance-constrained programming in an optimization framework. Uncertainties expressed as interval values and probabilistic distributions can be effectively handled. This is the first attempt that applies an optimization-based modelling approach to Yukon Territory, Canada. Three scenarios and one business-as-usual scenario are evaluated. System costs are minimized in this model. Results obtained from this model can help identify optimal patterns of renewable energy expansions in the Yukon. The interval solutions obtained could help decision makers to identify desirable renewable energy polices and emission reductions. [ABSTRACT FROM AUTHOR]

Community energy systems, which rely on demand-side self-organisation of energy distribution, can encounter situations in which demand exceeds supply, and unless the community members schedule energy usage by and between themselves, there will be a blackout. This is effectively a collective action dilemma typically modelled as a repeated game and analysed using Game Theory. In this paper, we investigate the situation from an empirical (rather than analytic) perspective using instead a Serious Game. Motivated firstly by Elinor Ostrom’s institutional design principles for sustainable common-pool resource management, and secondly by the idea that collective attention is a prerequisite for successful collective action, we present the design and implementation of a Serious Game which both encapsulates (some of) the design principles and promotes collective attention within the game’s interface, affordances and interactions. Our experimental results show that as more interface design features which promote collective attention are enabled, then more often successful collective action is observed. These results have, we argue, important implications for Smart Meter design and roll-out programmes, as well as leveraging the active participation of prosumers in innovative operational and management principles for future Smart Grids. [ABSTRACT FROM AUTHOR]

Highlights • Municipal utilities need to assess future strategies considering various actors. • Formalized integrated model framework is mathematically stated. • Actor-oriented optimization interface between supply and demand side is proposed. • Based on the actor-oriented dispatch, community flexibility potential is discussed. Abstract Against the backdrop of a changing political, economic and ecological environment, energy utilities are facing several challenges in many countries. Due to an increasing decentralization of energy systems, the conventional business could be undermined. Yet the reliable integration of small-scale renewable technologies and associated system transformations could represent an opportunity as well. Municipal energy utilities might play a decisive role regarding successful transition. For better decision-making, they need to investigate under which conditions certain novel business cases can become a sustainable part of their future strategy. The development of the strategy is a challenging task which needs to consider different conditions as business portfolio, the customer base, the regulatory framework as well as the market environment. Integrated Multi-Modal Energy System (IMMES) models are able to capture necessary interactions. This research introduces a model-driven decision support system called Integrated Resource Planning and Optimization (IRPopt). Major aim is to provide managerial guidance by simulating the impact of business models considering various market actors. The mixed-integer linear programming approach exhibits a novel formal interface between supply and demand side which merges technical and commercial aspects. This is achieved by explicit modeling of municipal market actors on one layer and state-of-the-art technology components on another layer as well as resource flow relations and service agreements mechanism among and between the different layers. While this optimization framework provides a dynamic and flexible policy-oriented, technology-based and actor-related assessment of multi-sectoral business cases, the encapsulation in a generic software system supports the facilitation. Based on the actor-oriented dispatch strategy, flexibility potential of community energy storage systems is provided to demonstrate a real application. [ABSTRACT FROM AUTHOR]

Highlights • Demand-side flexibility is integrated into an energy systems model (ESM) • Household appliances and electric cars can provide significant load management. • By 2050, the peak load can be significantly reduced, with large cost savings. • ESMs should consider demand-side flexibility as a key mitigation option. Abstract Demand-side flexibility from smart appliances and passenger electric vehicles has been increasingly regarded in recent years as an effective measure to reduce peak loads and to aid system balancing. While numerous studies have been undertaken to investigate the benefits of demand-side flexibility, most have either focused only on the power sector or provided a snapshot for a future year or day. The influence of interactions between sectors in the long-term under energy transition pathways has therefore been under explored. This paper presents a novel modelling approach in a whole energy systems model, UK TIMES, to investigate the benefits of demand-side flexibility from smart appliances and passenger electric vehicles, including the reduction in the costs of moving to a low carbon economy. This analysis shows that demand-side control increases system flexibility, enabling the integration of high levels of low carbon power, such as nuclear and wind, whilst reducing the requirements for storage. By 2050, the peak load is reduced by around 7 GW (9%), and cumulatively about 30.9 billion GBP saved with the help of this demand-side flexibility. This approach could be integrated into other energy systems models to improve the representation of this important flexibility mechanism. [ABSTRACT FROM AUTHOR]

Highlights • We assess how land and water constraints shape Great Britain’s 2050 power system. • We consider restrictions on nuclear/renewables siting and water for cooling. • Combined these lead to an up to 25% more costly electricity system. • Such constraints impact the system design both spatially and technologically. • The cost optimal share of renewable generation is found to be at least 50%. Abstract The decarbonisation of the power sector is key to achieving the Paris Agreement goal of limiting global mean surface temperature rise to well below 2 °C. This will require rapid, national level transitions to low carbon electricity generation, such as variable renewables (VRE), nuclear and fossil fuels with carbon capture and storage, across the world. At the same time it is essential that future power systems are sustainable in the wider sense and thus respect social, environmental and technical limitations. Here we develop an energy-land-water nexus modelling framework and use it to perform a scenario analysis with the aim of understanding the planning and operational implications of these constraints on Great Britain’s (GB) power system in 2050. We consider plausible scenarios for limits on installed nuclear capacity, siting restrictions that shape VRE deployment and water use for thermal power station cooling. We find that these factors combined can lead to up to a 25% increase in the system’s levelised cost of electricity (LCOE). VRE siting restrictions can result in an up to 13% increase in system LCOE as the deployment of onshore wind is limited while nuclear capacity restrictions can drive an up to 17% greater LCOE. We also show that such real-world limitations can cause substantial changes in system design both in terms of the spatial pattern of where generators are located and the capacity mix of the system. Thus we demonstrate the large impact simultaneously considering a set of nexus factors can have on future GB power systems. Finally, given our plausible assumptions about key energy-land-water restrictions and emission limits effecting the GB power system in 2050, the cost optimal penetration of VREs is found to be at least 50%. [ABSTRACT FROM AUTHOR]