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Electric vehicles (EVs) are pivotal in the progression toward sustainable transportation. However, a growing body of recent studies has challenged the often-assumed notion that electric vehicles are often considered to be net-zero emissions. These studies suggest that electric vehicles could potentially generate substantial emissions due to their reliance on fossil fuels to generate electricity, especially when receiving fast charging services. This phenomenon has been mitigated with the use of renewable energy sources in the power system. However, due to the intermittent nature of renewable energy sources, additional requirements have arisen. To address this situation, this paper presents an interdisciplinary study of collaborative fast-charging stations (FCS) and distributed renewable energy planning based on the interactions between traffic and power networks in order to increase the adoption rate of electric vehicles and reduce emissions caused by traffic and power systems. The locations and sizing of fast-charging stations, distributed photovoltaic generation, and renewable energy power supply for electric vehicles are determined in the proposed strategy through multi-objective integer programming. The proposed planning strategy considers heterogeneous electric vehicle driving range constraints, the operation security of the power distribution system, the reliability and expansion of the current power distribution, as well as different types of air pollutant classifications resulting from the charging behaviors. To guarantee the feasibility and accuracy of the planning results, an interactive algorithm is applied to solve the multi-objective integer model. Several cases are conducted to validate the proposed approach. The results demonstrate that the proposed planning strategy has good performance in the planning of fast-charging stations and distributed renewable energy integration. • A joint planning approach is proposed. • Optimize the locations and sizing of the fast-charging stations and distributed renewable energy. • Quantify different types of air pollutant emissions during charging services to promote the adoption of EVs and renewable energy. • An integer multi-objective model with an interactive algorithm is proposed. • The results demonstrate that the proposed method confers significant advantages to the application of EVs and renewable energy. [ABSTRACT FROM AUTHOR]

Small islands are fragile and dependent territories in many sectors, especially energy. Hence, renewable energy microgrids (MGs) can offer an opportunity for environmentally sustainable energy supply but also a driver for new development strategies in these territories. This paper aims to analyse the role that MGs can play in insular spaces for the achievement of more sustainable communities. Initially, MGs played a crucial role in ensuring energy supply in spaces characterised by a difficult supply. However, with technological improvements in both generation and storage, as well as institutional and legislative changes, MGs can play a fundamental role in achieving more socially cohesive and environmentally sustainable spaces beyond their role as energy suppliers. We discuss three main topics after a meta-analysis of 18 MGs, both on-grid and off-grid, located in insular spaces: 1) the characteristics of MGs built in insular territories in the last 25 years; 2) MGs influence islanders' well-being and lifestyle; and 3) how MGs can encourage responsible consumption and promote postgrowth strategies. Thus, this paper explores the role that MGs have played in the past and present and what role they could play in the future of small island spaces. It might be concluded that MGs are a key factor in the development of more sustainable societies. However, they must be accompanied by changes in our economies, societies and lifestyles in a direction other than the pursuit of economic growth traditionally understood as a limitless increase in consumption and production. [ABSTRACT FROM AUTHOR]

Distributed energy resources (DER), encompassing distributed renewable resources and distributed energy storage systems, are progressively emancipating themselves from reliance on subsidies and engaging in the realms of energy, green certificate, and capacity markets. However, the long-term profile of DERs under multiple market conditions remains uncertain, and traditional methods are inadequate in addressing the challenges posed by the non-linearity and non-convexity of various factors that affect investment and bidding behavior. Additionally, the varying time scales of clearing models across different markets require a quantitative approach that combines long and short-term scales to determine DER profitability under various critical boundaries. To address these challenges, this paper proposes a dual-timescale dynamics model. Firstly, the system dynamics (SD) method is employed to establish the interplay among various market entities, simulating capacity investment of generation units on a long-term scale. Secondly, the stochastic unit commitment (SUC) is modeled to verify the operating constraints of the system while simultaneously calculating the short-term market clearing results. These results are then fed back to the long-term simulation loop to evaluate the further profitability of DERs. Lastly, a price adjustment mechanism was devised to simulate the frequent occurrence of negative energy prices in high-proportion renewable energy systems, thereby enhancing the fidelity of simulated price data to real-world environments. Through a 20-year simulation, the proposed model quantitatively analyzes the impact of market mechanisms on DER profitability and the influence of DERs on market clearing results. The model has the potential to provide valuable analytical support for the design of DER-related market mechanisms and policy decisions. • The impact of the energy, capacity, and tradable green certificate market on distributed energy resources is assessed. • The competitive relationship among thermal power, renewable energy, and energy storage in multiple markets are examined. • The long-term profile of distributed energy resources is evaluated by a dual-timescale dynamics model. • The impact of negative electricity prices on renewable energy sources (RES) is examined. [ABSTRACT FROM AUTHOR]

With the rapid development of plug-in electric vehicles and hydrogen fuel vehicles, the introduction of hybrid energy supply stations into modern energy systems has attracted much attention in recent years. The hybrid energy supply stations are promising energy facilities that can provide charging services for plug-in electric vehicles and refilling services for hydrogen fuel vehicles. This paper studies electricity and carbon allowance sharing among community microgrids integrated with hybrid energy supply stations from a new perspective. The main objective of this work is to reduce the communication overheads when implementing distributed energy and carbon allowance management for microgrids, rather than merely protecting the privacy of microgrids as other studies have done. Thus, a communication-censored alternating direction method of multipliers-based communication-efficient distributed algorithm is proposed for solving the electricity and carbon allowance sharing problem in a distributed manner. Moreover, an adaptive penalty coefficient selection method is introduced and integrated into the communication-censored alternating direction method of multipliers for improving the convergence performance of the distributed algorithm. Simulation results demonstrate that the proposed mechanisms for sharing electricity and carbon allowance among microgrids can result in a 50.18% reduction in the total operation cost and a 13.70% reduction in the total carbon emissions, compared to the scenario where such sharing is not implemented. In comparison to the alternating direction method of multipliers, the proposed distributed algorithm can reduce the total communication overhead by 46.47%. Furthermore, the adaptive penalty coefficient selection method can improve the convergence performance of the communication-censored alternating direction method of multipliers by 21.26%. [ABSTRACT FROM AUTHOR]

In the last decade, the significant level of carbon emission in the atmosphere has increased the temperature of the Earth by 50% compared to the pre-industrial period. In recent years, considering renewable energy sources integrated with different energy systems such as cooling, heating, and power has become widespread around the globe as the ambition is to produce sustainable and clean energy. However, as the conventional methods for energy generation are highly reliable, their usage for supplying energy demands is inevitable. Therefore, in such renewable-based generation systems, the issues arising from uncertainties are the main challenges to the high penetration of these technologies. In this paper, the aim is to appraise such challenges in a multi-energy combined heat and power (CHP)-based microgrid integrated with power-to-gas (P-2-G) technology. In the proposed system, the downside risk constraint (DRC) approach as an effective risk management method is considered for risk assessment. The proposed model is a mixed integer linear program that is modeled as a multi-objective risk-based problem, for which the epsilon constraints method is used to achieve the optimal solutions for the objectives. According to the results, using P-2-G as an environmentally friendly tool can reduce approximately 55% of the emission cost. Further, the operating cost is increased nearly 13% to obtain a zero-risk condition for optimal management. [Display omitted] • Risk-constrained emission reduction and flexibility improvement in the fossil-fueled CHP-based multi-vector system. • A stochastic-based risk-aware multi-objective optimization framework with iterative solution mechanism. • Risk analysis with downside risk constraint (DRC) approach for the multi-vector uncertainties. [ABSTRACT FROM AUTHOR]

Recently, numerous significant advances in control methods have been made in Microgrid development especially in grid-connected mode to ensure a reliable and sustainable operation. The concept of control strategies for inverter systems to ensure proper microgrid integration has sparked a lot of research towards innovation. This review provides a comprehensive overview and analysis of microgrid integrated control methods and energy management systems for both grid-connected and island-based systems. The Scopus database is used to compile a list of the most cited published papers in the field of microgrid control methods and energy management systems, based on predetermined criteria. In the second week of January 2021, the study was performed using the Scopus database. The papers with the most citations were published in 33 different journals from 30 different countries. An 85% of the published articles are based on the control system development and experimental setup whereas 15% are review-based articles. Thus, it can be deduced that this research topic has always been under constant investigation and development in order to enhance the sustainability of microgrid systems in the electric power sector. The paper aims to identify and analyze the highly cited published articles on the respective field to provide future research direction on the microgrid integrated control method and energy management system. The review also underlines numerous factors, issues, challenges, and difficulties that next-generation microgrids must compete with in regards to grid sustainability. Thus, this review will strengthen the scopes and provide context for the development of microgrid integrated control methods and energy management systems in order to achieve an efficient, reliable, cost-effective, and sustainable power supply. • MG integrated grid control methods and energy management systems to sustainable operation. • Highly cited literatures are considered for analysing MG control methods and energy management. • Identified and analyzed the highly cited articles to provide future research direction on MG control. • Underlined numerous factors, issues, challenges, and difficulties for next generation microgrids. • Strengthen the scope of MG control methods and EMS to achieve reliable and sustainable power. [ABSTRACT FROM AUTHOR]

Reducing environmental pollution, developing and utilizing low-carbon integrated energy system, making economic development maintain a good momentum of sustainable development, has become hot issues of energy research around the world. The Multi-energy Complementary Distributed Energy System (MCDES), that can not only meet the changing energy supply structure and user demand, but also promote the efficient use of resources in the energy system and low-carbon environmental protection, has become the main direction of future energy development. The energy units in MCDES often have large time scale difference and strong uncertainty, which makes the planning and operation of the system more complex than the traditional energy system. Research on the characteristics of system configuration and operation optimization is one of the key measures to ensure the sustainable development and effective utilization of MCDES. Therefore, from three aspects of low-carbon, life cycle and optimization method, the MCDES life cycle low-carbon optimization method is studied in this paper. By reviewing the low-carbon optimization, life cycle optimization and system optimization methods of MCDES, the main problems in the current research status of MCDES life cycle low carbon optimization are pointed out. On this basis, according to low carbon measures and life cycle coordination theory, a multi-objective collaborative optimization method for MCDES life cycle planning and operation is proposed. The research content of this paper provides theoretical guidance for MCDES design optimization. [ABSTRACT FROM AUTHOR]

Nowadays it is estimated that the Earth's temperature is above the standard level compared to pre-industrial time. The main reason for this issue is the burning of conventional energy resources namely oil, gas, and coal which speeds up global warming. In this concern, a CHP-based multi-energy microgrid is studied in this paper which involves heating, cooling, and electricity carriers to supply the energy demands. The proposed system is a multi-objective problem with operation cost management and emission cost reduction. In order to develop the environmental and economic aspects, a power-to-gas (P2G) technology as an environmentally friendly system is taken into account to curb CO2 emissions and achieve a sustainable function. The presence of the P2G system can minimize the emission level and improve the ability to take advantage of Notwithstanding this, the uncertain parameters originate from the thermal, electrical, and cooling loads, electricity price, and the renewable generations impose inflexibility and financial threats to the system function. In this regard, a scenario-based risk assessment approach, p-robust optimization, is applied to handle these uncertainties. The uncertainty analysis is carried out in With-p-robust, No-p-robust, With-P2G, and No–P2G models to appraise the components' performance. Results showed 11% of the operation cost increment to achieve a zero-level risk. Also, 55% of the emission cost is minimized in the presence of the P2G facility, which enhances the efficiency of the system. [Display omitted] • Optimal multi-objective operation of CHP-based multi-energy microgrids with emission constraints. • Use of P2G facilities for carbon recycling and emission reduction. • Scenario generation and reduction through the stochastic programming for uncertainty modeling. • Modeling the regret of uncertainties using the hybrid modeling approach called p-robust optimization. [ABSTRACT FROM AUTHOR]

This paper proposes a novel optimization strategy for hybrid-renewable energy systems in microgrids. The multi-objective optimization approach is formulated for a PV-wind-diesel-battery hybrid system. Its main objectives are to minimize the levelized cost of energy (LCOE) and loss of power supply probability (LPSP) whilst maximizing the use of renewable energy sources (RES). The proposed optimization strategy combines the Taguchi method with a novel fuzzy decision-maker-based multi-objective optimization algorithm. It implements, a) an energy management strategy to optimize the use of the energy sources, b) a Taguchi method to determine the upper bounds of the model's decision variables, c) a multi-objective moth flame optimization algorithm to optimize the size of the renewable energy sources, and d) a fuzzy decision-making approach to obtain the best Pareto front. The proposed strategy was implemented to optimize the design of a hybrid renewable energy system based on three different scenarios consisting of 10, 15, and 20 residential houses located in Sønderborg, a town in the Region of Southern Denmark. The results of the proposed model in terms of loss of power supply probability and levelized cost of energy for the scenarios I, II, and III are [0.224, 0.754], [0.313, 0.612], and [0.368, 0.547] respectively. In addition, the optimal design of the hybrid renewable-based microgrid system for scenarios I, II, and III are [PV: 32 kW, AD: 4.86, WT: 6], [PV: 36 kW, AD: 4.73, WT: 7], and [PV: 47 kW, AD: 5, WT: 7], respectively. The effectiveness of the proposed multi-objective optimization algorithm (MOMFO) in solving the optimization problem was examined and the results were further compared with those of the Non-Dominated Sorting Algorithm II(NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Social Engineering Optimizer (MOSEO). [ABSTRACT FROM AUTHOR]

To achieve the European climate targets and the Paris Agreements, at least 65% of the electricity needs to be generated from renewable energy sources by 2030. This requires a significant increase of distributed energy resources, posing a challenge for distribution system operators to integrate them into existing hierarchical grids. The concept of Local Flexibility Markets has recently gained attention as a market-based tool to tackle this challenge, making use of demand side flexibility. In this paper a Delphi method has been performed, showing that there are still numerous barriers in place preventing a widespread adoption of such markets in Europe. The main obstacles for market participants refer to standardisation issues. Based on that, a hybrid market model has been developed, comprising elements of a Local Flexibility Market and a Local Energy Market. To activate demand side flexibility from local energy transactions, spatio-temporally varying price signals are introduced, reflecting the constraints of the distribution grid. The paper shows, that this novel market approach helps to overcome relevant standardisation issues, but also certain barriers regarding end-users' lifestyles, which is because prices are comprehensible signals that can motivate end-users to participate. Moreover, a set of numerical examples is provided to illustrate the monetary benefits that could be gained by consumers and prosumers in the proposed hybrid market model. The examples show that the major share of the cost savings result from local energy trading, but the hybrid market model is also able to accumulate additional smaller revenues from providing flexibility. Finally, the systematic approach of characterising the market model in this paper offers a valuable framework for other researchers to map their ideas among existing approaches of Local Energy and Flexibility Markets. • A framework for characterising Local Energy and Flexibility Markets is provided. • Main barriers for adopting such markets are related to standardisation issues. • A hybrid market model is proposed, featuring local energy and flexibility trading. • Trades are steered by dynamic price signals, reflecting various flexibility needs. • Numerical examples indicate the expected financial implications. [ABSTRACT FROM AUTHOR]

As distributed renewable energy sources (RES) continue to expand, the necessity arises for more robust coordination approaches and conversion techniques to tackle the challenges introduced by uncertainties in renewable generation. Increasing concerns about energy efficiency and power grid security, such as the significant number of conversion stages for energy production from renewable resources and the bidirectional power flow in the distribution system, have attracted attention to the topic. The presented comprehensive review in this paper discusses the merits and weaknesses of different integration strategies as supported by the literature review. In particular, the focus is placed on the challenges of interconnection and opportunities for direct current (DC) systems. The ultimate objective of this paper is to explore the most important power grid-wide effects due to the expected renewable energy expansion and to gain insights on the availability characteristics of DC microgrids to facilitate their integration with the power grid. The idea behind this is to establish inferences that energy conversion based DC microgrids can be a possible solution to mitigate the negative effect of renewable energy expansion. This is accomplished by systematically reviewing studies on power grid integration as well as providing technical analysis of the resulting outcomes in relation to the general impact of renewable energy production, and then, conducting a comparative study on renewable energy conversion based DC and alternating current (AC) systems. The types of bus topologies and control of DC distribution systems are also intensively reviewed and discussed. Moreover, the protection design considerations, control classifications and standards of DC microgrids are highlighted to explore the future research trends to be undertaken. The review concluded that the impact of interconnection on power grid can be eliminated through the use of intelligent control with advance communication technologies and the implementation of DC microgrids powered by sustainable resources in the distribution system. • Energy production from renewable sources is reviewed by discussing the merits and weaknesses of grid integration. • Renewable energy conversion based DC system is the possible solution to overcome the issues of generation expansion. • The standards of DC microgrids need to be enhanced to ensure the security during different operating conditions. • The review confirms that efficient protective devices of DC systems have not been developed as compared to AC systems. [ABSTRACT FROM AUTHOR]

In the current close-to-smart power systems, renewable energies are the most significant elements that need to be carefully addressed in power system studies. In this regard, microgrids (MGs) have been introduced recently to activate the large penetration of renewables. However, integration of such generation technologies that are associated with severe uncertainty in their power output would significantly impact the scheduling of energy resources in MGs. Thus, efficient energy management systems are required to be employed in MGs. Therefore, this paper presents a day-ahead scheduling framework for an MG equipped with a solar photovoltaic (PV) unit. In this respect, different climate conditions and their impacts on the power output of the PV unit and the optimal scheduling of the MG have been investigated in this paper. To this end, four different days from the four seasons have been used to extract the data of solar irradiance. The scheduling problem has been formulated in a single-objective optimization framework, where the objective function is defined as minimizing the total operating cost over the scheduling period. An effective optimization algorithm named "modified krill herd (MKH)" algorithm is proposed to solve the mentioned day-ahead scheduling problem, while there are renewable and non-renewable generating units, besides an energy storage system. Furthermore, a comprehensive comparison has been made between the MKH algorithm and some well-known optimization algorithms to verify the superior performance of the suggested method. [ABSTRACT FROM AUTHOR]

Dispatchable distributed energy resources (DERs) in distribution networks are envisioned to aid frequency regulation for transmission systems. In this paper, a real-time optimal dispatch framework for DERs in distribution networks is designed to offer frequency regulation services simultaneously. Different from the existing research that distribution networks track uniaxially the predetermined auxiliary-services commands of the transmission system, here we regard transmission system frequency regulation as a black box and learn the parameters of its proxy satisfaction function from the perspective of DER optimization. To solve such a special optimization problem with control performance feedback, first we employ Gaussian processes to learn the satisfaction function, and, especially, build pertinent upper confidence bounds to achieve the optimal provision of ancillary services. Next, the primal-dual gradient projection process is embedded into the Gaussian process upper confidence bound algorithm to pursue the optimal DER dispatch. Accordingly, the output powers of DERs can be controlled in real-time: in disaggregate mode, they meet the goal of the distribution network; in aggregate mode, they provide a more satisfactory tie-line power flow to the transmission system. Simulations for illustrative systems are provided to validate the approach. • Real-time optimization of DNs with DERs participating in frequency regulation is studied. • A special optimal scheduling problem of DMS with control feedback from EMS is solved. • A real-time optimization algorithm that embeds the PDGP into the GP-UCB is designed. • Learning proxy function is performed concurrently with the execution of optimization. • Nodal voltage in DNs are taken into account when provide frequency regulation recourses. [ABSTRACT FROM AUTHOR]

In recent years, electrical appliances have played a significant role in the energy consumption of the residential sector. Despite providing positive impacts on the quality of life, some devices suffer from various defects such as substantial environmental concerns and high-energy bills. As a relatively modern residential power tool, a home-connected Green Electric Vehicle (GEV) can discharge energy and supply power to the Home. This paper proposes a combined home Energy management system including Vehicle -To- Home (V2H) technology (or Home Centralized Photovoltaic-HCPV)). The proposed approach seeks to control home energy demand by scheduling optimal automation appliances. Without additional grid power, the proposed HCPV design will cover household electricity demand in sunny and cloudy weather. In contrast, the combination of PV and electricity transmitted by V2H is sufficient to meet household load demand by cloudy weather. In this vein, a scheduling Home Energy Management System is designed and discussed with various constraints to perform correct system operations and satisfy load demand. The proposed algorithm attempts to characterize and perceive source circumstances utilizing energy demand. The obtained results demonstrate that H2V operating technology is can effectively be reducing energy demand under solar-load volatility. [ABSTRACT FROM AUTHOR]

The microgrid has become a promising area to mitigate multiple challenges of the power system, resulting from renewable energy integration, climate change, as well as economic issues. However, the integration of flexible emerging technologies in microgrid operation to enhance the efficiency of energy supply, as well as environmental and economic challenges are urgently needed. Motivated by these challenges, this paper elaborates on the two-stage multi-objective optimization model for optimal scheduling of microgrid. The demand response program based on the time of use model, and plug-in electric vehicles have been integrated into the microgrid to contribute in economic and environmental goals. The proposed model extends the realistic EVs model based on the Wohler curve and AC-power flow equations. The proposed model is exposed to a wide range of random parameters, including wind output, load, price, and EVs' behaviours. To handle the uncertainties, and solving problem, scenario-based stochastic and weighted sum based on fuzzy decision-making strategies are respectively applied. The proposed model is tested on the 33-bus microgrid and examined for different cases. Results prove the impacts of the efficient integration of demand response, and a plug-in electric vehicle in the reducing of operational cost, and emission by 3.57% and 3.4%, respectively. • Proposing a realistic model for EV based on DoD and battery degradation. • Providing high-level flexibility for MG with the integration of PEV and DR. • Emission-economic assessment of renewable-based MG with flexible resources. • Proposing a two-stage stochastic programming model to capture uncertainties. [ABSTRACT FROM AUTHOR]

In the smart microgrid system, the optimal sizing of battery energy storage system (BESS) considering virtual energy storage system (VESS) can minimize system cost and keep system stable operation. This paper proposes a two-layer BESS optimal sizing strategy considering dispatch of VESS in a smart microgrid with high photovoltaic (PV) penetration. In the first layer, VESS modelling and aggregation are established, and the initial size of BESS is determined by considering VESS participation in demand response program. In the second layer, the optimal sizing of BESS is studied and the optimal energy resources dispatching strategy is formulated via considering various constraints in the system. The mean-variance Markowitz theory is applied to assess the risk of system cost variability due to the presence of PV and load uncertainties. With the ratio of load varies from 70% to 130%, and PV generation ratio from 40% to 100%, sensitivity analysis reveals the optimal size of BESS is less impacted by PV generation change. Also with VaR(95%) the risk of system cost variability can be further reduced through VESS participation. • Formulated an VESS model and aggregated to participate system dispatch and control. • A two-layer BESS sizing strategy considering system constraints and dispatch. • Reduced system operating cost via optimally dispatching of resources. • Risk component considers system uncertainties which affects system dispatch. [ABSTRACT FROM AUTHOR]

The solar photovoltaic (PV) system with battery energy storage have a lot of potential to provide reliable and cost-effective electricity and to contribute in micro-grid operation. However, the operational performance of such type of micro-grid system depends on many factors (e.g. techno-economic sizing, energy management among the sources, market energy prices dynamics, energy dispatch strategies, etc.). In this paper, a typical Indian institutional energy system has considered for techno-economic performance evaluation for operating as a smart micro-grid under market energy pricing dynamics. The institutional energy system has integrated PV, battery storage and DG for operating as a smart micro-grid. An operational energy dispatch strategy for micro-grid has proposed and evaluated for maximizing the local energy resources utilization with contemplation of peak demand and grid outage conditions under market energy pricing dynamics. With techno-economic sizing of PV, battery and DG of considered system; the peak demand has reduced by 10%, DG contribution by 92% and annual energy savings by 45% compare to operation of base system. With proposed energy management strategy, the annual battery energy throughput has increased from 0.4% to 10%, and the DG's contribution has decreased from 7% to 5% with 10% reduction in levelized cost of energy (CoE) compare to case with techno-economic sizing of PV, battery and DG for considered system. With inclusion of electrical energy pricing dynamics scenario, it has observed that the CoE has increased by 89% with change in time-of-use (ToU) tariff from 100% to 200% and considering energy-selling price to the grid at 100%. However, 8% reduction in the CoE has observed, when the energy-selling price to grid has increased from 100% to 200% at ToU of 100%. The results from this work are going to be useful for developing electrical tariff policies for promoting the PV based institutional micro-grid system under market energy pricing dynamics. • Market energy pricing impact on techno-economic operation of institutional photovoltaic based micro-grid. • Performance evaluation of photovoltaic based institutional micro-grid under time-of-use energy pricings. • Energy dispatch strategies to maximize photovoltaic contribution via battery energy throughput during energy pricing dynamics. [ABSTRACT FROM AUTHOR]

This paper considers the case study of a smart microgrid district at Graciosa Island in the Canary Islands. The smart energy microgrid district consists of several households and a public use building (school) that includes renewable energy sources (photovoltaic), Li-ion batteries for electric energy storage, domestic hot water heaters acting as thermal energy storage, a pool for balancing energy consumption and supplies, and the connection to the electric grid. We have modelled such a problem as a nonlinear mathematical programming model that is linearly approximated using special ordered sets of type 2. The linear approximation is solved using Gurobi optimization software, providing close-to-optimum solutions within an interval of 15 min that allows near-real-time operation of the smart energy district. The obtained results allow advancement of the net-zero energy neighbourhood concept in all the evaluated scenarios within a daily horizon and a positive energy balance in wider horizons. Obviously, these results are obtained in part due to the magnificent insolation conditions of the Canary Islands, but they allow justifying that the appropriate use of renewable energy resources and energy storage systems together with a balancing mechanism at the district level (such as the pool in our case study) may also lead to near-net-zero energy neighbourhoods in other geographical locations. [ABSTRACT FROM AUTHOR]

A distributed energy system (DES) can integrate renewable resources and achieve efficient energy utilization, and it is a common form of energy system for isolated systems. However, a multienergy complementary energy supply scheme makes operating a DES complicated. To ensure the system operates efficiently, it is necessary to study its operation strategy. However, currently, the research on DES operation optimization mostly is in the optimization result itself, hence lacking the transferring of the optimized operation strategy to engineering applications, which is difficult to apply to the actual energy saving operation. Therefore, this paper takes the DES of a scientific research station in Antarctica as an example when it comes to the optimization of its operation strategy, extracting the control logic for engineering applications from the optimized operation strategy. Aiming for the lowest primary energy consumption of the DES across an entire year, a model for optimal operation is presented and formulated as a Mixed Integer Linear Program (MILP), and further solved by the General Algebraic Modeling System (GAMS). The operation strategy of the DES is optimized and the energy saving space is analyzed. Furthermore, through strategy interpretation, the available control logic of the project is extracted from the optimized strategy, and the extraction effect is verified. The results show that the primary energy consumption of the optimized operation strategy can be reduced by 11.8% when compared with the original operation strategy. By using the engineering control logic extracted from the optimized operation strategy to adjust the original operation strategy, the primary energy consumption of the system can be reduced by 9.6%. The current study can provide a scientific and reasonable scheduling strategy for the actual operation of a DES and provide guidance and reference for the optimal operation of an existing DES. [ABSTRACT FROM AUTHOR]