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The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [ABSTRACT FROM AUTHOR]

In order to facilitate the carbon emission reduction to mitigate climate change, this paper proposes a coordinated multi-stage planning strategy for the transmission-level integrated electricity-gas-heating system. The strategy coordinates installations of gas-fired generation plants, renewable energy plants, gas wells, power-to-gas plants, transmission lines and pipelines, considering retirements of coal-fired generation plants. It can help facilitate carbon emission reduction of the electricity system as well as the integrated energy system. The objective is to minimize the total present value of the investment and the operation economic cost, with consideration of constraints from each sub-system and carbon emission restriction. In the case studies, the proposed planning strategy is verified to be able to obtain the installation plan of the related facilities. With which the system can reduce the proportion of fossil fuel energy utilization and increase renewable energy utilization. Hence, carbon emission reduction is achieved. In addition, it has demonstrated that integrating the multi-energy systems can help reduce the economic cost in the planning result. • Multi-stage planning strategy of the integrated energy system is proposed. • Energy conversions among different sub-systems are considered. • An aggregated model of district heating system is adopted. • Capability of carbon emission reduction is verified. • Contributions from flexibility of gas and heating systems are demonstrated. [ABSTRACT FROM AUTHOR]

Faced with international climate obligations and domestic pressure, Singapore has recently raised its climate goals significantly. The government had affirmed its intention for carbon emissions to peak before 2030 and for Singapore to attain net zero greenhouse gas emissions by 2050. However, as Singapore transitions to green energy, there remains much uncertainty if this transformation, coupled with rapidly evolving geopolitics, would present vulnerabilities to energy security. Hence, this paper is an attempt to investigate Singapore's possible paths to achieve these goals while enhancing energy security in view of present and future energy plans. Key parameters of energy security in Singapore's context are identified to determine how different policy decisions would influence them. The effects of various current and potential policies can thus be evaluated using a systems thinking and system dynamics approach to propose new energy solutions to improve energy security. System dynamics modelling reveals that new energy supply solutions would have to be considered in Singapore's Energy 2050 Plan while furthering efforts in reducing energy demand. Findings reveal that Singapore should have a target of >80% renewable energy by 2050, pursue a central strategy towards sustainable diversification of its energy sources into hydrogen, electricity imports and solar energy and reduce energy consumption. Accordingly, Singapore's energy security can then be improved in terms of the economic, energy supply chain and environmental dimensions, and towards attaining net-zero emissions. [Display omitted] • Systems approach to Singapore Green Plan 2030 and simulation of policies towards energy security and net zero. • Systems thinking and system dynamics modeling to evaluate key assumptions and energy security parameters. • Model validation, both structural and behavioral, through base model simulations as well as behavioral tests. • Effect of government policies on hydrogen energy, low carbon electricity imports and energy saving on energy security. • Simulations suggest policies for higher renewable energy targets to attain net zero carbon emissions and energy security. [ABSTRACT FROM AUTHOR]

An increasing number of federal and state regulations and financial incentive programs have been enacted in recent years to promote renewable energy systems integration in new buildings. This requires designers to analyze the initial and lifecycle costs of feasible renewable energy systems in order to optimize their integration in buildings during all design phases. The goal of this study is to support designers in generating optimal building schematic designs to maximize the integration and generation of onsite renewable energy. To accomplish this goal, this paper presents the development of a novel multi-objective optimization model that can be used during the schematic design phase to identify optimal building design decisions including dimensions, orientation, location on site, solid-to-void ratio, and the type and size of onsite renewable energy systems. The optimization objectives of the developed model focus on maximizing the generation of onsite renewable energy, maximizing savings-to-investment ratio of all integrated renewable energy, and minimizing both construction and renewable energy costs. An application example of optimizing the schematic design of a 6500 m2 building was analyzed to highlight the model original contributions and its novel capabilities. The results of this analysis highlight the original contributions of the developed model and its novel capabilities that can be used to maximize the generation of onsite renewable energy and its savings-to-investment ratio while minimizing building cost by optimizing building schematic design and renewable energy (RE) technology decisions. • Optimizing building schematic design with renewable energy integration. • Maximizing RE generation, savings-to-investment ration, and minimizing bilding costs. • Complying with building design requirements and renewable energy constraints. • Optimal building design parameters and renewable energy technologies. • Analyzing the impact of design decisions on renewable energy and building costs. [ABSTRACT FROM AUTHOR]

Multiple geographically dispersed data center buildings have been increasingly positioned in renewable-rich areas due to their high energy consumption. This paper proposes an optimal multi-energy portfolio for zero carbon data center buildings in the presence of proactive demand response programs. In the data center buildings, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via multi-energy conversion and storage devices, which are modeled as 100% renewable energy hubs for zero carbon multi-energy supplies. In order to exploit the hub-internal operational dispatchability and flexibility, a comprehensive energy consumption model of data center buildings is proposed to facilitate the demand response in terms of available serves, while the variable speed pumped storage (VSPS) is modeled to capture its dynamic operational characteristics. The energy‑carbon production, conversion, storage, and consumption are formulated as an energy‑carbon matrix, which are solved via a two-stage method to obtain the optimal portfolio. Case studies on southwest China data center buildings are implemented to demonstrate the effectiveness and superiority of the proposed methodology on cost-effective accommodation of RESs. Simulations results show that the system portfolio cost can be reduced by at most 17.8% with a higher operational flexibility. • A cost-effective data center building is proposed to accommodate zero carbon targets. • Hydro-solar-wind 100% renewables are formulated for multi-energy supplies. • VSPS and data center energy consumption are modeled to exploit inherent flexibility. • The energy-carbon production, conversion, storage, and consumption are optimized. [ABSTRACT FROM AUTHOR]

Integrated energy system (IES) is characterized by high self-consumption ratio of on-site generated renewable energy, high efficiency of conventional energy utilization and possesses a significant flexibility in its operation. This overall, constitute to the foundation of low-carbon communities. Considering economic and environmental benefits, this paper proposes a two-layer co-optimization model with the upper layer optimizing the IES configuration and the lower layer optimizing IES operation. A community in Beijing is introduced as a case study to analyze the benefits of IES and compared with the conventional energy system. Multiple scenarios are researched, including (a) IES for low-carbon communities with PV roof area limitation, (b) IES for each of the four building types with PV roof area limitation, (c) IES for low-carbon communities without PV roof area limitation. The results indicate that the optimized IES for community can reduce the cost by 25% and CO 2 emissions by 32% per year by considering the limitation of roof area for the PV system. Without this constraint, the costs and emissions could be reduced by 20% and 62%, respectively. In addition, IES is more appropriate for office and commercial buildings since their load characteristics allow for load shifting and community-level IES costs and emissions are 8% and 10% lower than building-level due to the complementary of community load. This study provides suggestions for the IES planning and application in low-carbon community. [Display omitted] • An IES with multiple renewable energy and energy storage subsystems is proposed. • A two-layer co-optimization model of IES design and operation is developed. • IES optimization results for building-level and community-level are compared. • Impact of roof area limitation for PV on IES optimization results is investigated. [ABSTRACT FROM AUTHOR]

• Imported green e-H 2 is more expensive than e-H 2 produced in Germany and Finland. • Local supply of e-H 2 found to be more economical across all scenarios and years. • Transportation costs constitute 29–63% of the total imported e-H 2 cost. • Pipeline transmission may be cheaper than shipping for distances of 2000–2500 km. Widely available and low-cost solar photovoltaics and wind power can enable production of renewable electricity-based hydrogen at many locations throughout the world. Hydrogen is expected to emerge as an important energy carrier constituting some of the final energy demand; however, its most important role will be as feedstock for further processing to e-fuels, e-chemicals, and e-steel. Apart from meeting their own hydrogen demand, countries may have opportunities to export hydrogen to countries with area limitations or higher production costs. This paper assesses the feasibility of e-hydrogen imports to Germany and Finland from two case regions with a high availability of low-cost renewable electricity, Chile and Morocco, in comparison to domestic supply. Special attention is paid to the transport infrastructure, which has a crucial impact on the economic viability of imports via two routes, shipping and pipelines. This study has found that despite lower e-hydrogen production costs in Morocco and Chile compared to Germany and Finland, additional transportation costs make imports of e-hydrogen economically unattractive. In early 2020s, imported fuel costs are 39–79% and 34–100% higher than e-hydrogen produced in Germany and Finland, respectively. In 2050, imported e-hydrogen is projected to be 39–70% more expensive than locally produced e-hydrogen in Germany and 43–54% in the case of Finland. e-Hydrogen may become a fuel that is mostly produced domestically and may be feasible for imports only in specific locations. Local e-hydrogen production may also lower dependence on imports, enhance energy security, and add jobs. [ABSTRACT FROM AUTHOR]

This paper discusses the application of distributed energy resources (DERs) at water resource recovery facilities (WRRF). The DERs considered include solar photovoltaic (PV) systems, biomass electricity generation, and energy storage systems (ESS). The financial and demand management implications of the deployment of various DER combinations are analyzed. The load profile of a single plant is studied in order to draw conclusions regarding the optimal size for energy storage solutions based on the goals of the WRRF. A case study of a Medium sized WRRF, located in a large metropolitan area, is used to compare different financial and technical implementation strategies. An ideal combination of DERs is determined based on analysis of various scenarios for nine distinct use cases. The overarching goal of this paper is to understand the potential of various combinations of DERs for managing peak demand and resilience at WRRFs. Elements in the financial models are compared to determine the combination that creates a financially viable project while providing tangible benefits in resilience and/or demand management to the WRRF. • Energy efficiency is key for urban regions to combat global warming. • Distributed energy resources (DERs) improve resiliency during power failures. • Energy efficiency is possible through deployment of DERs and better use of biogases • Distributed energy resources (DERs) improve resiliency during power failures. [ABSTRACT FROM AUTHOR]

Renewable energy in Middle East and North Africa (MENA) region, particular solar energy, can be connected to Europe to provide the Northern neighbouring countries with electricity. To achieve this long term objective, it is necessary to understand the local domestic consumption of electricity in the MENA region as the main consumer of energy. The understanding of current and future trends could help to provide a complete picture of the energy situation in MENA region and the feasibility of exporting energy to Europe. For this reason, this paper investigates the domestic energy use and occupants’ energy behaviour in Libya. The aim of this study is to evaluate the effect of domestic energy consumption and householders’ awareness, attitudes and behaviour on the overall energy consumption in Libya and how this could affect the peak demand, capacity, future trends and government energy budget. The paper also investigates the sustainability aspect of consumer products and the awareness and attitude of consumers towards consumption and demand. A comprehensive survey has been conducted to evaluate several aspects of domestic energy demand and characteristics in Libya. The findings have indicated that there is a significant increase in energy demands in the household sector in Libya and it is significant to have a clear strategy to reduce carbon emission and energy use by improving occupants’ behaviour as well as utilising other sustainable measures. Minor adjustment in householders’ energy consumption behaviour and the technology used to generate energy could provide significant financial savings and contribute significantly to the reduction in carbon emission and energy consumption. This will allow significant benefit to the local economy and the energy sector in Libya but at the same time could provide sustainable energy resources for Europe on the long term. [ABSTRACT FROM AUTHOR]

This paper presents a review of the optimization techniques and strategies applied to wind turbine performance optimization. The topic is addressed by identifying the most significant objectives, targets and issues, as well as the optimization formulations, schemes and models available in the published literature. The current energy demand combined with depletion of fossil-fuel reserves and stricter environmental regulations have led to the development of alternative renewable energy solutions like wind energy. The current 2030 United States target is to have at least 20% of the US energy supply by onshore and offshore wind farms. To meet these demands, wind energy costs have to be able to compete with traditional fossil fuel sources. Hence, it is essential and vital that wind turbine designers and manufactures search the optimal solution that fits the objectives under a set of design constraints. Throughout the last 30 years, the objective function has evolved from the earlier maximized metric of the power coefficient to the maximization of the annual energy production. Common alternatives such as blade mass minimization and maximization of the rotor thrust and torque have been examined. However, the main objective has been focused on the minimization of the cost of energy in order for wind energy to become more competitive and economically attractive. The purpose of this paper is to review previous work that undertakes the performance optimization of horizontal wind turbines by highlighting the main aspects when tackling the wind turbine optimization problem such as: objective functions, design constraints, tools and models and optimization algorithms. In addition, in a conclusion of the review, a discussion and argument about the challenges, issues and future developments are identified. [ABSTRACT FROM AUTHOR]

Electricity generation presents the biggest opportunity to lower CO 2 emissions and it is foreseen that hydrogen energy technology will play an important role in realising the scenario to cap global warming at 2 °C through replacement of fossil fuels with renewables. The transition to electric power for transport in battery- and fuel-cell-electric vehicles will further increase the need for low-carbon electricity generation. For a successful transition to a renewable energy economy the traditional approach of designing energy systems to meet only goals related to the technology (capacity, availability, reliability) and economics (return on investment, cost to the consumer) must evolve to take on a more holistic viewpoint and be able to take into account other goals addressing environmental and social considerations. This paper reviews approaches for integrating hydrogen energy technology into hybrid energy systems, emphasising electricity generation using a hydrogen fuel cell. Integration of energy storage, sizing methodologies, energy flow management and their associated optimization algorithms and software implementation are addressed. Few published case studies go beyond technical considerations. This reality is discussed in the light of available software packages. A four-dimensional multi-objective meta-heuristic function is proposed with weighting of technical, economic, environmental and socio-political factors to suit the design goals for the energy system. [ABSTRACT FROM AUTHOR]

• Four environmental indicators suitable for use in energy system models are proposed (85) • The indicators allow direct comparison of decarbonisation potential of renewables (84) • Gearbox double-fed induction generators are the preferred form of wind turbine (80) • Cadmium telluride photovoltaics exhibit best overall raw materials outcomes (78) Raw materials and their related environmental impacts will play a key role in the implementation of renewable energy infrastructures for decarbonization. Despite the growing amount of data quantifying raw materials for energy production technologies, few examples of these data sources are being included in current energy system models. Accordingly, this paper introduces possible pathways for integrating material-specific life cycle assessment outputs and material metabolism indicators into energy system models so that raw material requirements, and their associated impacts, can be accounted for. The paper discusses the availability of life cycle inventories, impact assessment methods and important output indicators. The material metabolism indicators most relevant to the current policy debate surrounding the European Green Deal–namely, material supply risk and contribution of recycled materials to total supply–are also discussed alongside the value of adding this information to energy system models. A methodology for using data from both approaches is offered and operationalised using four sub-technologies of both wind turbines and solar photovoltaic panels as case studies. The results show that considerable variation exists between and within the two groups for all indicators. The technologies with the lowest global warming potential, cumulative energy demand and supply risk are turbines with gearbox double-fed induction generators and cadmium telluride photovoltaics. Furthermore, wind turbines exhibit significantly higher recycling rates than photovoltaics. Ultimately, the integration of such methodologies into energy system models could greatly increase the awareness of raw material issues and guide policies that maximise compatibilities between resource availability and cleaner energy systems. [ABSTRACT FROM AUTHOR]

Transactive energy systems use dynamic electricity markets to present an improved way to control large numbers of distributed energy resources while maintaining user privacy, autonomy and scalability. However, this access to dynamic electricity prices can introduce negative emergent behavior like high peak loads if not adequately regulated by grid operators. To solve this, this paper proposes a regulated peer-to-peer market structure for residential prosumers. Prosumers bid energy demand or supply curves into a peer-to-peer market, which can then be directly used by the utility to quantify and dispatch demand flexibility. A utility surcharge mechanism can then be employed to dispatch this flexibility, and achieve significant improvements to reliability. This framework is tested in a simulation environment of electrified residential buildings with significantly enhanced fidelity representing the real-world housing stock. New York State and the month of January was chosen for the demonstration purpose, considering that January is one of the most challenging months for fully electrified systems in cold climates as solar production occurs at opposite times of the highest heating load. Results show that the surcharge can reducing peak load and ramp rates by nearly 50%, while also encouraging consumption of locally generated electricity. • Unregulated peer-to-peer electricity markets neglect grid network constraints. • These markets can be regulated by a surcharge imposed by the grid operator. • This surcharge dispatches demand flexibility in a predictable, quantifiable manner. • Decentralized demand flexibility is then quantified by aggregating demand bid curves. • This regulation method is decentralized, scalable, and privacy-preserving. [ABSTRACT FROM AUTHOR]

• First reviews on coupling utilisation of thermal sources in vapour compression heat pumps. • The existing thermal source coupling attempts in applied energy fields are summarised and compared. • Design features and performance enhancement principles are analysed in detail. • Recommendations for research and marketisation of energy source coupling methods are made. Vapour compression heat pump provides efficient cooling and heating through the use of various renewable energy sources and plays a significant role in the energy conservation of modern buildings. Its performance enhancement gains increasing attention under the background of conventional energy and environmental crisis. Since the efficiency of a heat pump cycle is closely related to its thermal source condition, a stable high-temperature heat source or low-temperature cold source could benefit its heating or cooling efficiency a lot. Following this improvement strategy, significant progress has been made over the past years on the use of different renewable energy sources as coupled thermal sources of heat pumps. However, a specialised review that summarises relevant studies remains to be published. This paper aims at presenting operating mechanisms, characteristics, benefits, and limitations of different energy source coupling methods for heat pump performance enhancement towards its building application. The most concerning research on solar-assisted air source heat pumps, solar-assisted ground source heat pumps, and air-ground dual source heat pumps is emphasised. The existing thermal source coupling attempts under other renewable energy fields, such as waste heat, biomass, and water sources, are also summarised. Recommendations for further research and marketisation of such technologies are made based on detailed performance characterisation and comparison. The review is expected to benefit researchers in heat pumps and relevant applied energy fields to understand the challenges and opportunities in thermal source coupling technology and to promote its research and application development. [ABSTRACT FROM AUTHOR]

• Examines the effect of banking performance on renewable energy consumption (REC). • Improved banking performance enhances renewable energy consumption globally. • Heterogenous effect of the relationship between banking performance and REC across income groups. • Market capitalization, asset quality and managerial inefficiency explain REC in HI countries. • Return on asset, market capitalization, asset quality and z-score explain REC in MI and LC countries. • Heterogenous effect of the relationship between banking performance and REC types is observed. To secure future universal access to modern energy, large investments in renewable energy technology are required. This paper estimates the impact of five banking sector performance indicators (return on asset, market capitalisation, asset quality, managerial efficiency and financial stability) on renewable energy consumption for a global panel consisting of 124 countries. The study used two-step system-GMM panel model to handle potential endogeneity and serial correlation. The paper considers three homogenous subpanels which are constructed based on the income group classification (high-, middle-, and low-income countries). Generally, our results show that improved banking sector performance enhances renewable energy consumption, with heterogenous effect across income group classification. For high -income (HI) countries, an increase in bank size together with improved asset quality and managerial efficiency have positive effects on renewable energy consumption. For middle-income (MI) and low-income (LI) countries, a high return on asset, an increase in bank size and financial stability are positive determinants of renewable energy consumption. We also find heterogenous effect of banking performance indicators across various renewable energy consumption types. The results highlight the importance of a well-functioning bank sector to achieve the investment in renewable energy needed to meet future energy demand and simultaneous decrease CO 2 emissions. [ABSTRACT FROM AUTHOR]

Chongming’s current energy system is highly import-dependent and the distributed energy system with high renewable energy penetration should be taken into consideration. In this paper, a simulation model based on EnergyPLAN software with 2014 as the reference year is developed to represent Chongming’s present energy structure. Four future scenarios which propose different further energy constructions have been observed. Results show that reductions in primary energy consumption, electricity import, annual operating costs as well as CO 2 emissions are realizable when switching to an energy system with a high share of renewable sources combining natural gas CHP (Combined Heating and Power). After preliminary discussions, the feasibility of different renewable sources penetration are analyzed through calculating the excess electricity production (CEEP). The estimated optimal combination is generated when the PV fraction is 20% while wind energy fraction is 80%. Moreover, the analyses have taken into account that several flexible techniques are needed in order to balance supply and demand and to ensure the grid voltage and frequency stabilities. As a result, through the recommended three techniques, the excess production can be avoided as far as a renewable energy input of up to nearly 60%. [ABSTRACT FROM AUTHOR]

In this paper we study the performance of 855 large (⩾10 kW) commercial rooftop photovoltaic (PV) system installations in California. Drawing on the nonparametric data envelopment analysis (DEA) method, our study takes the PV capacity, electricity generation, modules, system cost, solar irradiance, and ambient air temperature into account to provide a unified measure of the PV installation performance. This approach can overcome some of the limitations of simple output-to-input ratio analysis and allow us to assess whether solar capacity and electricity generation have been efficiently integrated into the grid in a holistic way. We find widespread inefficiencies in roughly 80–90% of the installations both within a specific year and across different years. There is a significant efficiency gain in solar installation from 2008 to 2012. Through regional analysis, we find high dispersions of performance across counties and cities, and identify locations where PV installations have achieved the best performance. The analysis also sheds lights on the magnitude of the gap between inefficient installations and efficient ones. [ABSTRACT FROM AUTHOR]

Sorption thermal energy storage (STES) is perceived as one prospective way of thermal energy storage (TES) owing to the advantages of high energy density, negligible heat loss, flexible working modes and long-term storage capability. Based on STES, this paper exhibits an innovative resorption thermal energy storage (RTES) system, and the experimental prototype is established for heat and refrigeration cogeneration. Working pair of MnCl 2 CaCl 2 NH 3 is chosen, 4.8 kg MnCl 2 and 3.9 kg CaCl 2 impregnated in expanded natural graphite treated with sulfuric acid are filled in two sorption beds respectively. Experimental results indicate that the largest energy storage density reaches 1706 kJ/kg when charging and discharging temperature are 160 °C and 30 °C, respectively. The maximum average cooling power achieves 1.07 kW during discharging phase and corresponding SCP is 27.33 W/kg within the overall cycle period. When charging temperature increases from 135 °C to 160 °C, the energy efficiency of the resorption system for heat and refrigeration cogeneration augments steadily from 0.72 to 0.87 while the exergy efficiency rises slowly from 0.29 to 0.35. [ABSTRACT FROM AUTHOR]

• A hydrogen-based MEMG in the electricity market is exploited. • A multiple time-scale energy management solution for MEMG is developed. • Electricity and hydrogen trading among subsystems are considered. • Daily operational cost of the hydrogen-based MEMG is minimized. With the technological advances in energy conversion and utilization of multiple forms of energy sources, hydrogen energy has attracted increasing attention. The hydrogen energy can be used to directly supply the hydrogen demand and generate both electricity and heat through fuel cell-based combined heat and power (FC-CHP) unit. This paper proposed a multiple time-scale energy management solution for a hydrogen-based multi-energy microgrid (MEMG) to supply electricity, hydrogen and heating loads aiming to minimize the MEMG operational cost with consideration of renewable energy generation and demand uncertainties. The proposed solution consists of day-ahead energy scheduling and model predictive control (MPC) based real-time energy dispatch in the presence of the electricity market. In the hydrogen-based MEMG, the electricity and hydrogen can be dispatched and utilized across multiple interconnected subsystems to improve the overall system energy utilization efficiency. The proposed solution is extensively assessed through simulation experiments compared with a benchmark solution. The numerical results confirm that the proposed solution outperforms the benchmark solution with the mean daily actual operational costs reduced by 37.08%. [ABSTRACT FROM AUTHOR]

• A method for scenario analysis that takes into account the uncertainty of renewable energy was developed. • Two demand side response approaches were utilized to evaluate the response impacts of two different types of loads. • Carbon trading market was considered in the suggested microgrid model, and carbon emissions could be decreased by a maximum of 10.13 percent compared to case 1 when the market was not considered. • A multi-stage optimization framework for microgrid energy management was proposed. The benefits of more comprehensive energy use and promotion of renewable energy (RE) consumption enable large-scale microgrid deployment. However, the uncertainty of renewable energy sources and the diversity of load types pose a threat to the microgrid's stability. Recently, energy scheduling optimization for microgrids (MGs) has been primarily based on ideal models, but incorporating as many real-world characteristics as feasible can improve the reliability of the optimization outcome. This paper provides a multi-stage methodology for solving the energy management optimization (EMO) problem of MG under uncertainty considering carbon trading market and demand side response (DSR). To begin, scenario analysis method was used to address the uncertainty associated with RE in MG, and four typical scenarios of renewable energy were generated. Then, the flexible configuration and operational constraints of each power source in MG are dealt with under the premise of considering the carbon trading market. The third stage involved merging the characteristics of various load types and analyzing the response impacts of different percentage residential and industrial loads, respectively, using the price-based and load-transfer-based DSR approaches. Finally, quantum particle swarm optimization (QPSO) algorithm was used to obtain the optimal solution. The acquired results demonstrate the efficacy of the proposed multi-stage energy optimization framework, and support the following two conclusions: 1) The carbon trading market policy contributes to the reduction of carbon emissions and fossil fuel consumption. 2) A high load participation rate in DSR can increase MG operation economics by up to 27.48% compared to not considering DSR. [ABSTRACT FROM AUTHOR]

Abstract: Portugal is a country with an energy system highly dependent on oil and gas imports. Imports of oil and gas accounted for 85% of the country’s requirements in 2005 and 86% in 2006. Meanwhile, the share of renewable energy sources (RES) in the total primary energy consumption was only 14% in 2006. When focusing only on electricity production, the situation is somewhat better. The share of RES in gross electricity production varies between 20% and 35% and is dependent on the hydropower production in wet and dry years. This paper presents, on a national scale, Portugal’s energy system planning and technical solutions for achieving 100% RES electricity production. Planning was based on hourly energy balance and use of H2RES software. The H2RES model provides the ability to integrate various types of storages into energy systems in order to increase penetration of the intermittent renewable energy sources or to achieve a 100% renewable island, region or country. The paper also represents a stepping-stone for studies offering wider possibilities in matching and satisfying electricity supply in Portugal with potential renewable energy sources. Special attention has been given to intermittent sources such as wind, solar and ocean waves that can be coupled to appropriate energy storage systems charged with surplus amounts of produced electricity. The storage systems also decrease installed power requirements for generating units. Consequently, these storages will assist in avoiding unnecessary rejection of renewable potential and reaching a sufficient security of energy supply. [ABSTRACT FROM AUTHOR]

[Display omitted] • A model is proposed to maximize market performance including tradable certificates. • The long-term impacts of regulations on market are discussed by fine and subsidy. • Three important objectives for government are investigated under four scenarios. • The obtained results are validated by Turkey's energy data as a real case study. • Fine policy is more effective than a subsidy to empower renewable electricity. In the last decades, due to the increasing environmental concerns such as energy-resource depletion and global warming, energy efficiency instruments and renewable energy production has been promoted more than ever. This paper investigates a comprehensive comparison between two energy markets, i.e., the tradable white certificate (TWC) market and the tradable green certificate (TGC) market. How to coordinate the two energy markets and what the coordination impacts become the main issues under a reward-penalty mechanism. This multi-agent problem is discussed in an electricity supply chain consisting of two populations of traditional energy suppliers who want to decide about using one of them under government intervention. In this regard, the behavior of the suppliers is analyzed under three different Scenarios, including traditional power generation, energy efficiency program (EEP), and renewable portfolio standards (RPSs). An evolutionary game is applied to formulate the problem. The results show that a mandatory fine policy is more useful than an energy-saving subsidy to motivate the traditional suppliers to move toward sustainable energy generation. This policy also helps governments to meet their sustainable-oriented goals, as we discussed in this work. The findings can be applied to extend sustainable-based energy projects in developing countries. [ABSTRACT FROM AUTHOR]

• A new structure of off-grid integrated energy system (OIES) for an isolated renewable energy hydrogen refueling station (HRS) is proposed. • A mixed integer quadratic constrained programming (MIQCP) model of the OIES is built. • These three loads are obtained by using the authoritative building model to simulate the operation in EnergyPlus software. • The optimal sizing and scheduling results and the sensitivity analysis results are presented numerically and visually. When designing an isolated renewable energy hydrogen refueling station (HRS), it is important to consider the electrical, heating and cooling demands of the supporting building as it is crucial for maintaining the stable HRS operation. Therefore, this paper proposed a new structure of off-grid integrated energy system (OIES) for an isolated renewable energy HRS, which can meet the hydrogen load of the market and the three kinds of loads of the supporting building. The OIES in question consists of wind generators, PV panels, batteries, electrolyzers, heat storage tanks, hydrogen tanks, and absorption chillers. A mixed integer quadratic constrained programming (MIQCP) model of the OIES is built based on the minimization of the total life cycle cost (TLCC). It is built to obtain the optimal solution for sizing and the equipment units' scheduling strategy. To accord with the actual situation, the electrical, heating, and cooling loads of the supporting building in the simulation are obtained by the EnergyPlus software. Furthermore, the 'community' hydrogen demand is obtained by the HOMER software. The results indicate that the proposed structure meets a wide array of energy demands and is more sensible solution when compared to other configurations with one component less. In addition, sensitivity analyses of the influence of economic data, meteorological data, and hydrogen load on TLCC are performed. These results show that the capital and replacement cost of the PV panels are the major economic factors influencing the TLCC. They also confirm that the PV is the system's main component due to a high correlation between the hourly hydrogen demand per year and the hourly solar radiation per year. Lastly, the effects of meteorological data and hydrogen load are also quantitatively analyzed. [ABSTRACT FROM AUTHOR]

This paper assesses the energy efficiency of a prototype of a dynamic photovoltaic (PV) greenhouse that has an asymmetric cross section and allows the rotation of the PV modules around their longitudinal axis throughout the day to select the degree of shading inside the structure. The goal of this research is to study the production of energy and the microclimate inside the structure with different tilt angles of the PV panels to improve the information available to support the farmers and to create a PV greenhouse capable of producing income from electrical and agricultural activity. The average values of the internal air temperature and relative humidity, measured during the hottest period and on days with clear skies, are within the optimal ranges for major vegetable species (17–27 °C and 60–90%, respectively). The values of the solar radiation available for the plants were always sufficient for normal agricultural operations, except for the last two days of the experiment (values lower than 5 MJ m −2 ) in which the shading percentage analyzed was too high for normal production. When the shading percentage was highest (78%), the maximum value of PV power (102 W m −2 ) was recorded and when the shading percentage was equal to 0%, the minimum value of PV power (20 W m −2 ) was recorded. The results show that it is possible to balance the electricity production using photovoltaic panels and the agricultural production as a function of the type of crop grown, latitude, operating season, and characteristics of the greenhouse. [ABSTRACT FROM AUTHOR]

Energy-intensive enterprises (EIEs) are typical kinds of industrial loads. They consume large amounts of electricity, and are very sensitive to electricity prices. Moreover, they have very good schedulability: they own various adjustable devices and dispatchable self-owned generation units, and have great flexibility in making production decisions. The characteristics of EIEs make them potentially ideal for coordinating with power systems and gaining a win–win situation, especially when the renewable energy penetration rate is high. However, problems still remain as to how to organize this coordination. In this paper, we design a decomposed coordinative scheduling (DCS) approach in which independent EIEs and the system exchange information iteratively to achieve final settlements. Based on a general modeling of EIEs, we introduce a mathematical formulation for DCS. The corresponding algorithm is also provided. We compare DCS to other scheduling approaches in case studies. It shows that DCS can significantly improve the benefits of the two sides without harming the privacy of EIEs. [ABSTRACT FROM AUTHOR]

This paper proposes an energy management strategy for a residential microgrid comprising photovoltaic (PV) panels and a small wind turbine. The microgrid is connected to the main grid, allowing for a controlled power exchange through a battery system and its control strategy. As input data, the proposed control strategy uses the battery state of charge (SOC), the power at each microgrid node as well as the load and renewable generation forecasts. By using forecasted data and correcting any forecasting errors according to the SOC of the battery, the strategy manages to make a better use of the battery resulting in a better grid power profile. The simulation of the system using a one-year data period shows that the proposed energy management strategy results in a better grid power profile for a given storage system when compared with other state-of-the-art strategies. Finally, the proposed strategy was experimentally validated in the microgrid built in the Renewable Energy Laboratory at the UPNa. [ABSTRACT FROM AUTHOR]

To reduce global greenhouse gas emissions, the world must find intelligent solutions to maximise the utilisation of carbon-free renewable energy sources. In this paper, multi-agent reinforcement learning is used to control a microgrid in a mixed cooperative and competitive setting. The agents observe fluctuating energy demand, dynamic wholesale energy prices, and intermittent renewable energy sources to control a hybrid energy storage system to maximise the utilisation of the renewables to reduce the energy costs of the grid. In addition, an aggregator agent trades with external microgrids competing against one another and the aggregator to reduce their own energy bills. For this, the algorithm deep deterministic policy gradients (DDPG) and multi-agent DDPG (MADDPG) are used to compare the use of a single global controller versus multiple distributed agents, along with the single and multi-agent variants of distributional DDPG (D3PG) and twin delayed DDPG (TD3). The research found it is significantly more profitable for the primary microgrid to sell energy on its own terms rather than selling back to the utility grid, and is also beneficial for the external microgrids as they also reduce their own energy bills. The methods that produced the greatest profits were the multi-agent approaches where each agent has its own reward function based on the principle of marginal contribution from game theory. The multi-agent approaches were better able to evaluate their performance controlling individual components of the environment which allowed them to develop their own unique policies for the different types of energy storage system. • Novel use of MADDPG for mixed cooperative and competitive microgrid environment. • Compare use of a central controller or multiple distributed agents in microgrids. • Hybrid energy storage system for long, medium, and short-term storage. • Case studies for renewable utilisation and trading with neighbouring microgrids. • Showcase the benefit of using rewards based on marginal contribution in a MAS. [ABSTRACT FROM AUTHOR]

Desalination has become imperative as a drinking water source for many parts of the world. Due to the large quantities of thermal energy and high quality electricity requirements for water purification, the desalination industry depends on waste heat resources and renewable energy sources such as solar collectors, photovoltaic arrays, geothermal and wind and tidal energy sources. Considering the mismatch between the source supply and demand and intermittent nature of these energy resources, energy storage is a must for reliable and continuous operation of desalination facilities. Thermal energy storage (TES) requires a suitable medium for storage and circulation while the photovoltaic/wind generated electricity needs to be stored in batteries for later use. Desalination technologies that utilize thermal energy and thus require storage for uninterrupted process operation are multi-stage flash distillation (MSF), multi-effect evaporation (MED), low temperature desalination (LTD) and humidification–dehumidification (HD) and membrane distillation (MD). Energy accumulation, storage and supply are the key components of energy storage concept which improve process performance along with better resource economics, and minimum environmental impact. Similarly, the battery energy storage (BES) is essential to store electrical energy for electrodialysis (ED), reverse osmosis (RO) and mechanical vapor compression (MVC) technologies. This research-review paper provides a critical review on current energy storage options for different desalination processes powered by various renewable energy and waste heat sources with focus on thermal energy storage and battery energy storage systems. Principles of energy storage (thermal and electrical energy) are discussed with details on the design, sizing, and economics for desalination process applications. [ABSTRACT FROM AUTHOR]

• Multi-agent dueling double deep Q-network optimization framework was established. • Prioritized experience replay and feasible action screening mechanism was applied. • Value-decomposition network was used to solve multi-agent reliability problems. • Simulation results prove the economy and doability of the method. Under the background of high global building energy consumption, meeting the ever-growing energy consumption demand of building energy system (BES) through renewable energy is one of the effective ways to promote the clean transformation of global energy structure and achieve "carbon neutrality". However, with the introduction of renewable energy, BES control becomes more complicated. The mismatch between supply and demand sides limits the further growth of renewable energy consumption, which is caused by fluctuation of renewable energy and randomness of load. Therefore, it is challenging to develop an efficient framework to realize the cooperative control of various controlled objects in supply and demand sides. To address this challenge, a multi-agent deep reinforcement learning framework was proposed to optimize the energy management of the building. In this paper, a dueling double deep Q-network was used for optimization of single agent, and value-decomposition network was put forward to solve the cooperation optimization of multiple agents. Also, considering the controlled characteristics of BES, prioritized experience replay and feasible action screening mechanism were introduced to accelerate the convergence and maintain stability of the algorithm applied to BES. Simulation results show that, the multi-agent cooperation algorithm can realize the control of variously different devices at the same time and achieve multi-objective cooperation optimization of BES. Moreover, the proposed approach reduced the uncomfortable duration by 84%, the unconsumed amount of renewable energy by 43%, and the energy cost by 8% compared with the conventional rule-based control approach. [ABSTRACT FROM AUTHOR]

• Cloud computing technologies applied to microgrid management. • Supervised machine learning strategies associated with the energy management system. • Used architecture by the energy management system to control a cluster of microgrids. • Considered elements in developing a scalable and autonomous architecture. The way to organize the generation, storage, and management of renewable energy and energy consumption features has taken relevance in recent years due to demands that define the social welfare of this century. Like demand increases, other factors require grid infrastructure improvement, updates, and opening to other technologies that assuage the final customer needs. Precisely, the interest in renewable energy sources, the constant evolution of energy storage technologies, the continuous research involving microgrid management systems, and the evolution of cloud computing technologies and machine learning strategies motivate the development of this article. Tasks associated with a microgrid cluster like the integration of a considerable number of heterogeneous devices, real-time support, information processing, massive storage capabilities, security considerations, and advanced optimization techniques usage could take place in an autonomous and scalable energy management system architecture under a machine learning perspective running in real-time and using Cloud resources. This paper focuses on identifying the elements considered by different authors to define a cloud-based architecture and ensure the appropriately supervised learning functionality under a microgrids cluster environment. Namely, it was necessary to revise and run microgrid simulations, real-time simulation platforms usage, connection to a virtual server for microgrid control and set the energy management system using cloud computing and machine learning. Based on the review and considering the scenarios mentioned, this article presents a scalable and autonomous cloud-based architecture that allows power generation forecast, energy consumption prediction, a real-time energy management system using machine learning techniques. [ABSTRACT FROM AUTHOR]

Abstract: A strong and intermeshed electricity grid allows the cost-efficient achievement of renewable energy targets by enabling the use of favorable sites and by facilitating the balancing of stochastic infeed from renewables and electricity demand. However, construction of new lines is currently proceeding slowly in Europe. This paper quantifies the benefits of optimal transmission grid extensions for Europe up to 2050 by iterating an investment and dispatch optimization model with a load flow based grid model. We find that large grid extensions, allowing the full exploitation of the most favorable RES-E sites throughout Europe, are beneficial from a least-cost perspective. If the electricity network were to be cost-optimally extended, 228,000km would be built before 2050 (+76% compared to today). Only for sites located furthest from large consumption areas in Central Europe would the value of grid extensions not always outweigh its costs. Furthermore, the capacity of transmission lines connecting favorable RES-E sites with demand centers is cost-optimally dimensioned to almost entirely export all RES-E generation that exceeds local electricity demand. Only in periods with the highest infeed of fluctuating renewables, electricity is stored. When optimal grid extensions are impeded, storage investments are chosen to a larger extent. [Copyright &y& Elsevier]

Abstract: Forest biomass is one of the renewable sources of energy that has been used for generating electricity. The feasibility and cost of producing electricity from forest biomass depend on long term availability of biomass, its cost and quality, and the cost of collecting, pre-processing, handling, transportation, and storage of forest biomass, in addition to the operating and maintenance costs of the conversion facility. To improve the cost competitiveness of forest biomass for electricity generation, mathematical programming models can be used to manage and optimize its supply chain. In this paper, the supply chain configuration of a typical forest biomass power plant is presented and a dynamic optimization model is developed to maximize the overall value of the supply chain. The model considers biomass procurement, storage, energy production and ash management in an integrated framework at the tactical level. The developed model is a nonlinear mixed integer programming which is solved using the outer approximation algorithm provided in AIMMS software package. It is then applied to optimize the supply chain of a real biomass power plant in Canada. The optimum solution provides more profit compared to the actual profit of the power plant. Different scenarios for maximum available supply and also investment in a new ash recovery system were evaluated and the results were analyzed. The model in particular shows that investment in a new ash recovery system has economic as well as environmental benefits for the power plant. [Copyright &y& Elsevier]

Abstract: The objective of the work presented in this paper is to contribute to the development of CHP systems based on conventional diesel engines but fuelled with pyrolysis oil or pyrolysis oil derived fuels. Experiments have been carried out using a one-cylinder, 20kWe diesel engine, which was adapted to enable the feeding of different fuels and the monitoring of its performance. Apart from the introduction of a completely new stainless steel fuel injection system also specific measures have been implemented to overcome the difficult and slow ignition behavior of pyrolysis oil. Pyrolysis oil could be successfully combusted provided the air inlet temperature was increased to 100–120°C at an engine compression ratio of 17.6. This temperature can be reduced by approximately 40°C when the compression ratio is increased to 22.4. Generally, pyrolysis oil fuelling led to an increase in CO emission and a decrease in NO x emission. Apparently, peak temperatures in the cylinder are lower upon fuelling pyrolysis oil. A ‘duration’ experiment of 40h was carried out while fuelling pyrolysis oil, without any notable effect on flue gas emissions and fuel consumption. This is considered as a very promising result, but further long-term testing will be required. [Copyright &y& Elsevier]

Abstract: This paper presents a novel energy storage system which stores excessive energy in the form of compressed air and thermal heat. It is different from the conventional compressed air energy storage (CAES) technology in that the new system allows trigeneration of electrical, heating and cooling power in energy releasing process. Uniquely, the cooling power from this system is generated by direct expansion of compressed air instead of the use of absorption chilling technology. In addition, the system can meet the end users’ demands for electricity, and heating and cooling powers through controlling the inlet pressure and temperature of an air based expander. A new parameter, the comprehensive efficiency, is proposed to evaluate the performance of the trigeneration system. Energy requirements of a small office building located in Chicago is used for the evaluation. The results show that the comprehensive efficiency of the system is very high (∼50%) in winter months when no cooling is needed. In summer months, due to the high power consumption in air compression process and inefficient expansion of the compressed air (for cooling power production) the comprehensive efficiency decreases to about 30%. However such a value is still higher than the conventional trigeneration system based on absorption chilling technology. The system is therefore very promising for practical applications particularly for the use of renewable energy due to good flexibility and simple configuration. [Copyright &y& Elsevier]

Abstract: The technical and economic feasibility study of an innovative wind–solar hybrid renewable energy generation system with rainwater collection feature for electrical energy generation is presented in this paper. The power generated would supply part of the energy requirements of the high-rise building where the system is installed. The system integrates and optimizes several green technologies; including urban wind turbine, solar cell module and rain water collector. The design was conceptualized based on the experiences acquired during the development and testing of a suitable wind turbine for Malaysian applications. It is compact and can be built on top of high-rise buildings in order to provide on-site renewable power to the building. It overcomes the inferior aspect on the low wind speed by channeling and increasing the speed of the high altitude free-stream wind through the power-augmentation-guide-vane (PAGV) before it enters the wind turbine at the center portion. The shape or appearance of the PAGV that surrounds the wind turbine can be blended into the building architecture without negative visual impact (becomes part of the building). The design improves the starting behavior of wind turbines. It is also safer to people around and reduces noise pollution. The techno-economic analysis is carried out by applying the life cycle cost (LCC) method. The LCC method takes into consideration the complete range of costs and makes cash flows time-equivalent. The evaluations show that for a system with the PAGV (30m diameter and 14m high) and an H-rotor vertical axis wind turbine (17m diameter and 9m high) mounted on the top of a 220m high building, the estimated annual energy savings is 195.2MWh/year. [Copyright &y& Elsevier]

Abstract: This paper aims to test the ETSAP [2] ETSAP (Energy Technology Systems Analysis Programme) is an IEA Implementation Agreement since 1976, developing the MARKAL-TIMES family of models. 2 -TIAM global energy system model and to try out how far it can go towards a global 100% renewable energy system with the existing model database. This will show where limits in global resources are met and where limits in the data fed to the model until now are met. Results from the modelling are global and regional energy consumption, emission of greenhouse gasses and thereby potential increase in global mean temperature. Furthermore, total system costs are compared to a reference scenario. Existing analysis with TIAM shows different ways of reaching the 2°C target (increase in global mean temperature) and also how uncertainty on different factors influences the optimal solution. The main conclusion from existing analysis with TIAM is that the 2°C target is possible to reach, but it will be expensive. Another very important point is that if uncertainty on the value of the climate sensitivity (Cs ) is taken into account then the optimal strategy calls for early action compared to a full foresight optimisation using the most probable value of Cs . [ABSTRACT FROM AUTHOR]

The energy transition faces the challenge of increasing levels of decentralised renewable energy injection into an infrastructure originally laid out for centralised, dispatchable power generation. Due to limited transmission capacity and flexibility, large amounts of renewable electricity are curtailed. In this paper, we assess how Power-to-Gas facilities can provide spatial and temporal flexibility by shifting pressure from the electricity grid to the gas infrastructure. For this purpose, we propose a two-stage model incorporating the day-head spot market and subsequent redispatch. We introduce Power-to-Gas as a redispatch option and apply the model to the German electricity system. Instead of curtailing renewable electricity, synthetic natural gas can be produced and injected into the gas grid for later usage. Results show a reduction on curtailment of renewables by 12 % through installing Power-to-Gas at a small set of nodes frequently facing curtailment. With the benefits of decentralised synthetic natural gas injection and usage, we exploit the advantages of coupling the two energy systems. The introduction of Power-to-Gas provides flexibility to the electricity system, while contributing to a higher effective utilisation of renewable energy sources as well as the natural gas grid. • Power-to-Gas can shift pressure from electricity to gas infrastructure. • The utilisation of Power-to-Gas in redispatch reduces curtailment by 12%. • Based on 427 analysed node, 5 nodes show a high potential for Power-to-Gas usage. • Results are supported by ongoing projects of transmission system operators. • The feasibility of Power-to-Gas depends on technology efficiency and the CO 2 price. [ABSTRACT FROM AUTHOR]

• First comprehensive review on two-phase loop thermosyphon technology. • Characteristics, mechanism, and research progress of two-phase loop thermosyphon. • Independent two-phase loop thermosyphon for effective heat transfer. • Novel integration and coupling with vapour compression cycle. • Challenges and prospects of two-phase loop thermosyphon technology. Two-phase loop thermosyphon is a natural phase-change heat transfer cycle widely used for thermodynamic applications. In additon to low manufacturing and maintenance costs, the primary advantages of such device include high heat transfer capability, reliability, and sustainability. Significant progress has been made in the two-phase loop thermosyphon and its integrated/coupled systems for energy conservation and environment protection. This paper represents a comprehensive review that discusses the physical mechanisms, characteristics and research progress of the two-phase loop thermosyphon based on recent experimental and simulative studies. The review extends to worldwide applications of independent two-phase loop thermosyphon in the renewable and sustainable energy fields and its utilisation for performance enhancement of vapour compression cycles by system integration and coupling. Challenges and recommendations for future research and application of two-phase loop thermosyphon are identified. This review will help researchers and engineers better understand the mechanisms, features and potential of the two-phase loop thermosyphon technology and promote its development. [ABSTRACT FROM AUTHOR]

• Energy flexibility in water pumping and storage systems is explored. • Proposed methodology can be used to support the operation of power systems. • A real water distribution system is considered to assess the proposed methodology. • Energy costs and pumping cycles are reduced by 16% and 57%, respectively. Renewable energy integration in power systems and increasing electrification of energy demand create new challenges to which energy flexibility can provide effective solutions. Trough an innovative use of cumulative energy consumption curves, which represent the maximum and minimum energy limits, as well as the associated flexible energy consumption, this paper presents a methodology to characterise and use the energy flexibility provided by water pumping and storage systems (WPSS) in order to achieve specific objectives at different levels of power systems. The methodology is applied to a case study considering a real WPSS where energy flexibility is used to reduce electricity costs and support the operation of the power system during a wind generation curtailment event. Collected results show that savings around 16% can be achieved while reducing pumping cycles by 57%. Furthermore, the WPSS operation can be modified according to the needs of the power system using the available energy flexibility. [ABSTRACT FROM AUTHOR]