As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,t...As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,traceability and tamper-proof features,is an importantway to achieve efficient consumption andmulti-party supply of new energy.In this article,we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’revenue,consider the degree of microgrid users’preference for electricity thus increasing users’reliance on the blockchainmarket,and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue.The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.展开更多
This paper investigates the issues of topology design and capacity configuration in multi-microgrid(MMG)systems.Firstly,we analyze the limitations of current researches about MMG planning,which mainly focus on either ...This paper investigates the issues of topology design and capacity configuration in multi-microgrid(MMG)systems.Firstly,we analyze the limitations of current researches about MMG planning,which mainly focus on either topology design or capacity configuration separately,and propose the idea of joint planning simultaneously considering both aspects.Secondly,we present a two-stage stochastic optimization model aimed at minimizing the planning and operational costs to derive the solutions for topology design and capacity configuration.Moreover,various constraints are taken into account,including maximum equipment capacity,load shedding penalty cost,wind and solar power curtailment costs,and energy coordination among microgrids.Finally,simulation experiments are conducted using the islanded multi-microgrid(IMMG)as the research object,and additional comparative experiments are included to demonstrate the effectiveness and feasibility of the proposed model.Experimental results demonstrate that our method can significantly improve the economic benefits of MMG systems and enhance their penetration of renewable energy,which helps promote the economic development and stable operation of MMG systems.展开更多
Contingencies,such as behavior shifts of microgrid operators(MGOs)and abrupt weather fluctuations,significantly impact the economic operations of multi-microgrids(MMGs).To address these contingencies and enhance the e...Contingencies,such as behavior shifts of microgrid operators(MGOs)and abrupt weather fluctuations,significantly impact the economic operations of multi-microgrids(MMGs).To address these contingencies and enhance the economic and autonomous performance of MGOs,a self-organizing energy management modeling approach is proposed.A second-order stochastic dynamical equation(SDE)is developed to accurately characterize the self-organizing evolution of the operating cost of MGO incurred by contingencies.Firstly,an operating model of MMG relying on two random graph-driven information matrices is constructed and the order parameters are introduced to extract the probabilistic properties of variations in operating cost.Subsequently,these order parameters,which assist individuals in effectively capturing system correlations and updating state information,are incorporated as inputs into second-order SDE.The second-order SDE is then solved by using the finite difference method(FDM)within a loop-structured solution framework.Case studies conducted within a practical area in China validate that the proposed self-organizing energy management model(SEMM)demonstrates spontaneous improvements in economic performance compared with conventional models.展开更多
An effective modeling and optimization method,which takes into account source-load-storage coordination,and full-time collaborative optimization within and outside micro-grids,is introduced.Considering the operational...An effective modeling and optimization method,which takes into account source-load-storage coordination,and full-time collaborative optimization within and outside micro-grids,is introduced.Considering the operational conditions of various resources and their interactions,an energy management model for microgrids is proposed aiming at maximization of renewable energy utilization and minimization of overall system costs.The model is suitable for both real-time pricing and time-of-use mechanisms.In microgrids,demand response and economic energy storage dispatch are introduced to enhance selfcoordination and self-balancing ability among different resources.Depending on whether there is still an imbalance between supply and demand after coordination within a niicrogrid,trade between it and external microgrids are optimized in a orderly manner by considering different transaction prices and usage rights.Finally,three different schemes are designed,where the Lagrangian multiplier method as well as a co-evolution algorithm are used to solve and analyze different examples,verifying the reliability and validity of the method proposed in this paper.展开更多
The multi-directional flow of energy in a multi-microgrid(MMG) system and different dispatching needs of multiple energy sources in time and location hinder the optimal operation coordination between microgrids. We pr...The multi-directional flow of energy in a multi-microgrid(MMG) system and different dispatching needs of multiple energy sources in time and location hinder the optimal operation coordination between microgrids. We propose an approach to centrally train all the agents to achieve coordinated control through an individual attention mechanism with a deep dense neural network for reinforcement learning. The attention mechanism and novel deep dense neural network allow each agent to attend to the specific information that is most relevant to its reward. When training is complete, the proposed approach can construct decisions to manage multiple energy sources within the MMG system in a fully decentralized manner. Using only local information, the proposed approach can coordinate multiple internal energy allocations within individual microgrids and external multilateral multi-energy interactions among interconnected microgrids to enhance the operational economy and voltage stability. Comparative results demonstrate that the cost achieved by the proposed approach is at most 71.1% lower than that obtained by other multi-agent deep reinforcement learning approaches.展开更多
Multi-microgrids have many new characteristics, such as bi-directional power flow, flexible operation and variable fault current consisting of the different control strategy of inverter interfaced distributed generati...Multi-microgrids have many new characteristics, such as bi-directional power flow, flexible operation and variable fault current consisting of the different control strategy of inverter interfaced distributed generations (IIDGs), which all present challenges in multi-microgrid protection. In this paper, the current and voltage characteristics of different feeders are analyzed considering faults at different locations of the multi-microgrid. Based on the voltage and current distribution characteristics of the line parameters, a new protection scheme for the internal faults of multi-microgrids is proposed, which takes the change of phase difference and amplitude of measured bus admittances as the criterion. This proposed scheme has high sensitivity and reliability, is based on a simple principle, and can be easily adjusted. Simulation results using PSCAD/EMTDC verify the correctness and effectiveness of the protection scheme.展开更多
随着可再生能源并网比例增加及需求侧负荷多样化,多微网系统在促进分布式能源消纳方面发挥关键作用。为实现多微网系统内源荷储之间的高效协同配合,提出一种考虑虚拟储能(virtual energy storage,VES)的多微网混合博弈模型。首先根据空...随着可再生能源并网比例增加及需求侧负荷多样化,多微网系统在促进分布式能源消纳方面发挥关键作用。为实现多微网系统内源荷储之间的高效协同配合,提出一种考虑虚拟储能(virtual energy storage,VES)的多微网混合博弈模型。首先根据空调负荷等效热力学特性、电动汽车充放电特性,构建基于电动汽车集群、空调负荷集群的虚拟储能模型。其次构建以多微网运营商为领导者,负荷聚合商、储能运营商为跟随者的主从博弈模型,并在主从博弈基础上引入多微网运营商中各微网间的合作博弈,促进微网间的端对端(peer-to-peer,P2P)电能交易,在合作收益分配问题中,引入基于非线性函数贡献度的纳什议价模型,实现更加公平的微网间利益分配。最后基于结合求解器的自适应差分进化算法以及交替方向乘子法求解所提出的模型。仿真结果表明,所提多微网混合博弈模型有效均衡了各主体的效益,同时提升了多微网运营商的效益,使多微网内分布式可再生能源消纳率提升至100%,实体储能的充放电量减少16%的同时向上级电网的购电量也减少44%,降低了对实体储能以及上级电网的依赖。展开更多
Consensus has been widely used in distributed control,where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal.However,the objectives of existi...Consensus has been widely used in distributed control,where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal.However,the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost,which is an important performance indicator to assess the performance and sustainability of battery energy storage(BES)systems.In this paper,we propose a consensusbased optimal control strategy for multi-microgrid systems,aiming at multiple control objectives including minimizing battery degradation cost.Distributed consensus is used to synchronize the ratio of BES output power to BES state-of-charge(SoC)among all microgrids while each microgrid is trying to reach its individual optimality.In order to reduce the pressure of communication links and prevent excessive exposure of local information,this ratio is the only state variable shared between microgrids.Since our complex nonlinear problem might be difficult to solve by traditional methods,we design a compressive sensing-based gradient descent(CSGD)method to solve the control problem.Numerical simulation results show that our control strategy results in a 74.24%reduction in battery degradation cost on average compared to the control method without considering battery degradation.In addition,the compressive sensing method causes an 89.12%reduction in computation time cost compared to the traditional Monte Carlo(MC)method in solving the control problem.展开更多
Power sharing can improve the benefit of the multi-microgrid(MMG)system.However,the information disclosure may appear during the sharing process,which would bring privacy risk to a local microgrid.Actually,the risk an...Power sharing can improve the benefit of the multi-microgrid(MMG)system.However,the information disclosure may appear during the sharing process,which would bring privacy risk to a local microgrid.Actually,the risk and coordination cost are different in different sharing modes.Therefore,this paper develops a decision-making method to decide the most suitable one of three mostly used sharing modes(i.e.,cooperative game with complete information,cooperative game with incomplete information,and noncooperative game).Firstly,power sharing paradigms and coordination mechanisms in the three modes are formulated in detail.Particularly,different economic operation models of MMG system are included to analyze the economic benefit from different sharing modes.Based on the different disclosed information,the risk cost is evaluated by using the simplified fuzzy analytic hierarchy process(FAHP).And the coordination cost for different sharing modes is expressed in different functions.In addition,a hierarchical evaluation system including three decision-making factors(e.g.,economics,risk,and coordination)is set up.Meanwhile,a combination weighting method(e.g.,the simplified FAHP combined with the anti-entropy weight method)is applied to obtain the weight of each factor for comprehensive evaluation.Finally,the optimal sharing solution of MMG system is decided by comparing and analyzing the difference among the three sharing modes.Numerical results validate that the proposed method can provide a reference to deciding a suitable sharing mode.展开更多
基金This research was funded by the NSFC under Grant No.61803279in part by the Qing Lan Project of Jiangsu,in part by the China Postdoctoral Science Foundation under Grant Nos.2020M671596 and 2021M692369+3 种基金in part by the Suzhou Science and Technology Development Plan Project(Key Industry Technology Innovation)under Grant No.SYG202114in part by the Open Project Funding from Anhui Province Key Laboratory of Intelligent Building and Building Energy Saving,Anhui Jianzhu University,under Grant No.IBES2021KF08in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.KYCX23_3320in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.SJCX22_1585.
文摘As the current global environment is deteriorating,distributed renewable energy is gradually becoming an important member of the energy internet.Blockchain,as a decentralized distributed ledger with decentralization,traceability and tamper-proof features,is an importantway to achieve efficient consumption andmulti-party supply of new energy.In this article,we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’revenue,consider the degree of microgrid users’preference for electricity thus increasing users’reliance on the blockchainmarket,and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue.The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.
基金support provided by the Major Open Project of Xiangiiang Laboratory(No.22XJ02003)the National Natural Science Foundation of China(Nos.62122093,72301287,and 72071205)+3 种基金the Science and Technology Project for Young and Middle-aged Talents of Hunan(No.2023T-Z03)the Science and Technology Innovation Program of Hunan Province(No.2023RC1002)the Hunan Provincial Natural Science Foundation of China(No.2022JJ10069)the Scientific Project of National University of Defense Technology(Nos.ZK21-07 and 23-ZZCX-JDZ-28).
文摘This paper investigates the issues of topology design and capacity configuration in multi-microgrid(MMG)systems.Firstly,we analyze the limitations of current researches about MMG planning,which mainly focus on either topology design or capacity configuration separately,and propose the idea of joint planning simultaneously considering both aspects.Secondly,we present a two-stage stochastic optimization model aimed at minimizing the planning and operational costs to derive the solutions for topology design and capacity configuration.Moreover,various constraints are taken into account,including maximum equipment capacity,load shedding penalty cost,wind and solar power curtailment costs,and energy coordination among microgrids.Finally,simulation experiments are conducted using the islanded multi-microgrid(IMMG)as the research object,and additional comparative experiments are included to demonstrate the effectiveness and feasibility of the proposed model.Experimental results demonstrate that our method can significantly improve the economic benefits of MMG systems and enhance their penetration of renewable energy,which helps promote the economic development and stable operation of MMG systems.
基金supported by the National Natural Science Foundation of China(No.52077035)the Liaoning Revitalization Talents Program of China(No.XLYC2007181).
文摘Contingencies,such as behavior shifts of microgrid operators(MGOs)and abrupt weather fluctuations,significantly impact the economic operations of multi-microgrids(MMGs).To address these contingencies and enhance the economic and autonomous performance of MGOs,a self-organizing energy management modeling approach is proposed.A second-order stochastic dynamical equation(SDE)is developed to accurately characterize the self-organizing evolution of the operating cost of MGO incurred by contingencies.Firstly,an operating model of MMG relying on two random graph-driven information matrices is constructed and the order parameters are introduced to extract the probabilistic properties of variations in operating cost.Subsequently,these order parameters,which assist individuals in effectively capturing system correlations and updating state information,are incorporated as inputs into second-order SDE.The second-order SDE is then solved by using the finite difference method(FDM)within a loop-structured solution framework.Case studies conducted within a practical area in China validate that the proposed self-organizing energy management model(SEMM)demonstrates spontaneous improvements in economic performance compared with conventional models.
基金supported by the Shanghai Sailing Program(20YF1418800)outstanding Ph.D.graduate development scholarship of Shanghai Jiao Tong University.
文摘An effective modeling and optimization method,which takes into account source-load-storage coordination,and full-time collaborative optimization within and outside micro-grids,is introduced.Considering the operational conditions of various resources and their interactions,an energy management model for microgrids is proposed aiming at maximization of renewable energy utilization and minimization of overall system costs.The model is suitable for both real-time pricing and time-of-use mechanisms.In microgrids,demand response and economic energy storage dispatch are introduced to enhance selfcoordination and self-balancing ability among different resources.Depending on whether there is still an imbalance between supply and demand after coordination within a niicrogrid,trade between it and external microgrids are optimized in a orderly manner by considering different transaction prices and usage rights.Finally,three different schemes are designed,where the Lagrangian multiplier method as well as a co-evolution algorithm are used to solve and analyze different examples,verifying the reliability and validity of the method proposed in this paper.
基金supported by Sichuan Province Innovative Talent Funding Project for Postdoctoral Fellows (No. BX202210)。
文摘The multi-directional flow of energy in a multi-microgrid(MMG) system and different dispatching needs of multiple energy sources in time and location hinder the optimal operation coordination between microgrids. We propose an approach to centrally train all the agents to achieve coordinated control through an individual attention mechanism with a deep dense neural network for reinforcement learning. The attention mechanism and novel deep dense neural network allow each agent to attend to the specific information that is most relevant to its reward. When training is complete, the proposed approach can construct decisions to manage multiple energy sources within the MMG system in a fully decentralized manner. Using only local information, the proposed approach can coordinate multiple internal energy allocations within individual microgrids and external multilateral multi-energy interactions among interconnected microgrids to enhance the operational economy and voltage stability. Comparative results demonstrate that the cost achieved by the proposed approach is at most 71.1% lower than that obtained by other multi-agent deep reinforcement learning approaches.
文摘Multi-microgrids have many new characteristics, such as bi-directional power flow, flexible operation and variable fault current consisting of the different control strategy of inverter interfaced distributed generations (IIDGs), which all present challenges in multi-microgrid protection. In this paper, the current and voltage characteristics of different feeders are analyzed considering faults at different locations of the multi-microgrid. Based on the voltage and current distribution characteristics of the line parameters, a new protection scheme for the internal faults of multi-microgrids is proposed, which takes the change of phase difference and amplitude of measured bus admittances as the criterion. This proposed scheme has high sensitivity and reliability, is based on a simple principle, and can be easily adjusted. Simulation results using PSCAD/EMTDC verify the correctness and effectiveness of the protection scheme.
文摘随着可再生能源并网比例增加及需求侧负荷多样化,多微网系统在促进分布式能源消纳方面发挥关键作用。为实现多微网系统内源荷储之间的高效协同配合,提出一种考虑虚拟储能(virtual energy storage,VES)的多微网混合博弈模型。首先根据空调负荷等效热力学特性、电动汽车充放电特性,构建基于电动汽车集群、空调负荷集群的虚拟储能模型。其次构建以多微网运营商为领导者,负荷聚合商、储能运营商为跟随者的主从博弈模型,并在主从博弈基础上引入多微网运营商中各微网间的合作博弈,促进微网间的端对端(peer-to-peer,P2P)电能交易,在合作收益分配问题中,引入基于非线性函数贡献度的纳什议价模型,实现更加公平的微网间利益分配。最后基于结合求解器的自适应差分进化算法以及交替方向乘子法求解所提出的模型。仿真结果表明,所提多微网混合博弈模型有效均衡了各主体的效益,同时提升了多微网运营商的效益,使多微网内分布式可再生能源消纳率提升至100%,实体储能的充放电量减少16%的同时向上级电网的购电量也减少44%,降低了对实体储能以及上级电网的依赖。
基金supported by the BNRist Program(No.BNR 2021TD01009)Fundamental Research Funds for the Central Universities of China(Grant No.B200201071).
文摘Consensus has been widely used in distributed control,where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal.However,the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost,which is an important performance indicator to assess the performance and sustainability of battery energy storage(BES)systems.In this paper,we propose a consensusbased optimal control strategy for multi-microgrid systems,aiming at multiple control objectives including minimizing battery degradation cost.Distributed consensus is used to synchronize the ratio of BES output power to BES state-of-charge(SoC)among all microgrids while each microgrid is trying to reach its individual optimality.In order to reduce the pressure of communication links and prevent excessive exposure of local information,this ratio is the only state variable shared between microgrids.Since our complex nonlinear problem might be difficult to solve by traditional methods,we design a compressive sensing-based gradient descent(CSGD)method to solve the control problem.Numerical simulation results show that our control strategy results in a 74.24%reduction in battery degradation cost on average compared to the control method without considering battery degradation.In addition,the compressive sensing method causes an 89.12%reduction in computation time cost compared to the traditional Monte Carlo(MC)method in solving the control problem.
基金supported by the National Key R&D Program of China(No.2019YFE0123600)the National Natural Science Foundation of China(No.52077146)the Sichuan Science and Technology Program(Grant No.2021YFSY0052).
文摘Power sharing can improve the benefit of the multi-microgrid(MMG)system.However,the information disclosure may appear during the sharing process,which would bring privacy risk to a local microgrid.Actually,the risk and coordination cost are different in different sharing modes.Therefore,this paper develops a decision-making method to decide the most suitable one of three mostly used sharing modes(i.e.,cooperative game with complete information,cooperative game with incomplete information,and noncooperative game).Firstly,power sharing paradigms and coordination mechanisms in the three modes are formulated in detail.Particularly,different economic operation models of MMG system are included to analyze the economic benefit from different sharing modes.Based on the different disclosed information,the risk cost is evaluated by using the simplified fuzzy analytic hierarchy process(FAHP).And the coordination cost for different sharing modes is expressed in different functions.In addition,a hierarchical evaluation system including three decision-making factors(e.g.,economics,risk,and coordination)is set up.Meanwhile,a combination weighting method(e.g.,the simplified FAHP combined with the anti-entropy weight method)is applied to obtain the weight of each factor for comprehensive evaluation.Finally,the optimal sharing solution of MMG system is decided by comparing and analyzing the difference among the three sharing modes.Numerical results validate that the proposed method can provide a reference to deciding a suitable sharing mode.
