With the increasing connection of controllable devices to isolated community microgrid,an economic operation model of isolated community microgrid based on the temperature regulation characteristics of temperature con...With the increasing connection of controllable devices to isolated community microgrid,an economic operation model of isolated community microgrid based on the temperature regulation characteristics of temperature controlling devices composed of wind turbine,micro-gas turbine,energy storage battery and heat pump is proposed.With full consideration of various economic costs,including fuel cost,start-stop cost,energy storage battery depletion expense and penalty for wind curtailment,the model is solved by hybrid particle swarm optimization(HPSO)algorithm.The optimal output of the micro-sources and total operating cost of the system in the scheduling cycle are also obtained.The case study demonstrates that temperature adjustment of temperature controlling devices can adjust the power load indirectly and increase the schedulability of the isolated community microgrid,and reduce the operating cost of the microgrid.展开更多
In rural territories, the communities use energy sources based on fossil fuels to supply themselves with electricity, which may address two main problems: greenhouse gas emissions and high fuel prices. Hence, there is...In rural territories, the communities use energy sources based on fossil fuels to supply themselves with electricity, which may address two main problems: greenhouse gas emissions and high fuel prices. Hence, there is an opportunity to include renewable resources in the energy mix. This paper develops an optimization model to determine the optimal sizing, the total annual investment cost in renewable generation, and other operating costs of the components of a hybrid microgrid. By running a k-means clustering algorithm on a meteorological dataset of the community under study, the hourly representative values become input parameters in the proposed optimization model. The method for the optimal design of hybrid microgrid is analyzed in six operating scenarios considering:(1) 24-hour continuous power supply;(2) load shedding percentage;(3) diesel power generator(genset) curtailment;(4) the worst meteorological conditions;(5) the use of renewable energy sources including battery energy storage systems(BESSs);and(6) the use of genset. A mathematical programming language(AMPL) tool is used to find solutions of the proposed optimization model. Results show that the total costs of microgrid in the scenarios that cover 100% of the load demand(without considering the scenario with 100% renewables) increase by over 16% compared with the scenario with genset operation limitation. For the designs with power supply restrictions, the total cost of microgrid in the scenario with load shedding is reduced by over 27% compared with that without load shedding.展开更多
Smart grid has integrated an increasing number of distributed energy resources to improve the efficiency and flexibility of power generation and consumption as well as the resilience of the power grid.The energy consu...Smart grid has integrated an increasing number of distributed energy resources to improve the efficiency and flexibility of power generation and consumption as well as the resilience of the power grid.The energy consumers on the power grid,e.g.,households,equipped with distributed energy resources can be considered as"microgrids"that both generate and consume electricity.In this paper,we study the energy community discovery problems which identify energy communities for the microgrids to facilitate energy management,e.g.,load balancing,energy sharing and trading on the grid.Specifically,we present efficient algorithms to discover such communities of microgrids considering both their geo-locations and net energy(NE)over any period.Finally,we experimentally validate the performance of the algorithms using both synthetic and real datasets.展开更多
Energy storage devices can effectively balance the uncertain load and significantly reduce electricity costs in the community microgrids(C-MGs) integrated with renewable energy sources. Scheduling of energy storage is...Energy storage devices can effectively balance the uncertain load and significantly reduce electricity costs in the community microgrids(C-MGs) integrated with renewable energy sources. Scheduling of energy storage is a multi-stage decision problem in which the decisions must be guaranteed to be nonanticipative and multi-stage robust(all-scenario-feasible). To satisfy these two requirements, this paper proposes a method based on a necessary and sufficient feasibility condition of scheduling decisions under the polyhedral uncertainty set. Unlike the most popular affine decision rule(ADR) based multistage robust optimization(MSRO) method, the method proposed in this paper does not require the affine decision assumption, and the feasible regions(the set of all feasible solutions) are not reduced, nor is the solution quality affected. A simple illustrative example and real-scale scheduling cases demonstrate that the proposed method can find feasible solutions when the ADR-based MSRO fails, and that it finds better solutions when both methods succeed. Comprehensive case studies for a real system are performed and the results validate the effectiveness and efficiency of the proposed method.展开更多
This research addresses the planning and scheduling problem in and among the smart homes in a community microgrid. We develop a bi-linear algorithm, named ECO-Trade to generate the near-optimal schedules of the househ...This research addresses the planning and scheduling problem in and among the smart homes in a community microgrid. We develop a bi-linear algorithm, named ECO-Trade to generate the near-optimal schedules of the households’ loads, storage and energy sources. The algorithm also facilitates Peer-to-Peer (P2P) energy trading among the smart homes in a community microgrid. However, P2P trading potentially results in an unfair cost distribution among the participating households. To the best of our knowledge, the ECO-Trade algorithm is the first near-optimal cost optimization algorithm which considers the unfair cost distribution problem for a Demand Side Management (DSM) system coordinated with P2P energy trading. It also solves the time complexity problem of our previously proposed optimal model. Our results show that the solution time of the ECO-Trade algorithm is mostly less than a minute. It also shows that 97% of the solutions generated by the ECO-Trade algorithm are optimal solutions. Furthermore, we analyze the solutions and identify that the algorithm sometimes gets trapped at a local minimum because it alternately sets the microgrid price and quantity as constants. Finally, we describe the reasons of the cost increase by a local minimum and analyze its impact on cost optimization.展开更多
随着分布式能源的大量接入和电力系统运行方式的逐渐转变,社区微网系统(community microgrid system,CMS)中用户已经从传统的消费者转变为具有电能生产/消费行为的产消者。在此背景下,通过引入点对点(peer to peer,P2P)能源交易机制,实...随着分布式能源的大量接入和电力系统运行方式的逐渐转变,社区微网系统(community microgrid system,CMS)中用户已经从传统的消费者转变为具有电能生产/消费行为的产消者。在此背景下,通过引入点对点(peer to peer,P2P)能源交易机制,实现社区微网系统中的产消者自主能量管理以及自主竞价策略最终达成P2P能量交易。首先,考虑产消者的差异化特征,对CMS内部资源自主形成的4种典型类型的产消者进行整合和建模。然后,基于连续双边拍卖机制搭建了日前阶段多类型产消者P2P能量交易框架,各产消者考虑历史交易决策信息以个体利益最大为目标,并通过交互有限的信息,在产消者之间互相发起交易请求,实现CMS内产消者之间P2P能量交易。针对在交易过程中产消者可能出现的隐私性保护,提出基于多段报价机制的P2P竞价策略,既能降低交易方的信息暴露风险,又能减少单次竞价决策的风险度,保证产消者收益稳定。最后,通过算例验证文中设计的P2P交易机制能够有效保护产消者的交易隐私性的同时,提高其经济效益。展开更多
随着分布式能源(distributed energy resources,DERs)以及需求侧柔性资源的广泛应用,城市园区微网系统(urban community microgrid system,UCMS)的架构、形态和运行方式将发生根本性改变,终端用户在微网中的身份将从传统的消费者转变为...随着分布式能源(distributed energy resources,DERs)以及需求侧柔性资源的广泛应用,城市园区微网系统(urban community microgrid system,UCMS)的架构、形态和运行方式将发生根本性改变,终端用户在微网中的身份将从传统的消费者转变为兼具能量生产与消费能力的产消者。通过建立端对端(peer-to-peer,P2P)能量交易机制,各个产消者之间可以在市场的引导下实现能量资源的协调优化,有效提升经济效益、供需平衡以及可再生能源就地消纳等UCMS全局效用。为此,分别从交易机制、运营策略以及建模分析3个角度,对城市园区微网系统P2P能量交易技术的研究现状进行了分析,希望能够对未来UCMS市场化运营提供一定的思考和借鉴。展开更多
基金the National Natural Science Foundation of China under Grant 51677011.
文摘With the increasing connection of controllable devices to isolated community microgrid,an economic operation model of isolated community microgrid based on the temperature regulation characteristics of temperature controlling devices composed of wind turbine,micro-gas turbine,energy storage battery and heat pump is proposed.With full consideration of various economic costs,including fuel cost,start-stop cost,energy storage battery depletion expense and penalty for wind curtailment,the model is solved by hybrid particle swarm optimization(HPSO)algorithm.The optimal output of the micro-sources and total operating cost of the system in the scheduling cycle are also obtained.The case study demonstrates that temperature adjustment of temperature controlling devices can adjust the power load indirectly and increase the schedulability of the isolated community microgrid,and reduce the operating cost of the microgrid.
基金supported in part by SENESCYT and in part by PRESTIGE Research Group,and CERA from ESPOL.
文摘In rural territories, the communities use energy sources based on fossil fuels to supply themselves with electricity, which may address two main problems: greenhouse gas emissions and high fuel prices. Hence, there is an opportunity to include renewable resources in the energy mix. This paper develops an optimization model to determine the optimal sizing, the total annual investment cost in renewable generation, and other operating costs of the components of a hybrid microgrid. By running a k-means clustering algorithm on a meteorological dataset of the community under study, the hourly representative values become input parameters in the proposed optimization model. The method for the optimal design of hybrid microgrid is analyzed in six operating scenarios considering:(1) 24-hour continuous power supply;(2) load shedding percentage;(3) diesel power generator(genset) curtailment;(4) the worst meteorological conditions;(5) the use of renewable energy sources including battery energy storage systems(BESSs);and(6) the use of genset. A mathematical programming language(AMPL) tool is used to find solutions of the proposed optimization model. Results show that the total costs of microgrid in the scenarios that cover 100% of the load demand(without considering the scenario with 100% renewables) increase by over 16% compared with the scenario with genset operation limitation. For the designs with power supply restrictions, the total cost of microgrid in the scenario with load shedding is reduced by over 27% compared with that without load shedding.
基金partially supported by the National Science Foundation(NSF)(No.CNS-1745894)the WISER ISFG grant+1 种基金partly sponsored by the Air Force Office of Scientific Research(AFOSR)(No.YIP FA9550-17-1-0240)the Maryland Procurement Office(No.H98230-18-D-0007).
文摘Smart grid has integrated an increasing number of distributed energy resources to improve the efficiency and flexibility of power generation and consumption as well as the resilience of the power grid.The energy consumers on the power grid,e.g.,households,equipped with distributed energy resources can be considered as"microgrids"that both generate and consume electricity.In this paper,we study the energy community discovery problems which identify energy communities for the microgrids to facilitate energy management,e.g.,load balancing,energy sharing and trading on the grid.Specifically,we present efficient algorithms to discover such communities of microgrids considering both their geo-locations and net energy(NE)over any period.Finally,we experimentally validate the performance of the algorithms using both synthetic and real datasets.
基金supported in part by National Key R&D Program of China (No.2022YFA1004600)Science and Technology Project of State Grid Corporation of China (No.5400-202199524A-0-5-ZN)National Natural Science Foundation of China (No.11991023)。
文摘Energy storage devices can effectively balance the uncertain load and significantly reduce electricity costs in the community microgrids(C-MGs) integrated with renewable energy sources. Scheduling of energy storage is a multi-stage decision problem in which the decisions must be guaranteed to be nonanticipative and multi-stage robust(all-scenario-feasible). To satisfy these two requirements, this paper proposes a method based on a necessary and sufficient feasibility condition of scheduling decisions under the polyhedral uncertainty set. Unlike the most popular affine decision rule(ADR) based multistage robust optimization(MSRO) method, the method proposed in this paper does not require the affine decision assumption, and the feasible regions(the set of all feasible solutions) are not reduced, nor is the solution quality affected. A simple illustrative example and real-scale scheduling cases demonstrate that the proposed method can find feasible solutions when the ADR-based MSRO fails, and that it finds better solutions when both methods succeed. Comprehensive case studies for a real system are performed and the results validate the effectiveness and efficiency of the proposed method.
文摘This research addresses the planning and scheduling problem in and among the smart homes in a community microgrid. We develop a bi-linear algorithm, named ECO-Trade to generate the near-optimal schedules of the households’ loads, storage and energy sources. The algorithm also facilitates Peer-to-Peer (P2P) energy trading among the smart homes in a community microgrid. However, P2P trading potentially results in an unfair cost distribution among the participating households. To the best of our knowledge, the ECO-Trade algorithm is the first near-optimal cost optimization algorithm which considers the unfair cost distribution problem for a Demand Side Management (DSM) system coordinated with P2P energy trading. It also solves the time complexity problem of our previously proposed optimal model. Our results show that the solution time of the ECO-Trade algorithm is mostly less than a minute. It also shows that 97% of the solutions generated by the ECO-Trade algorithm are optimal solutions. Furthermore, we analyze the solutions and identify that the algorithm sometimes gets trapped at a local minimum because it alternately sets the microgrid price and quantity as constants. Finally, we describe the reasons of the cost increase by a local minimum and analyze its impact on cost optimization.
文摘随着分布式能源的大量接入和电力系统运行方式的逐渐转变,社区微网系统(community microgrid system,CMS)中用户已经从传统的消费者转变为具有电能生产/消费行为的产消者。在此背景下,通过引入点对点(peer to peer,P2P)能源交易机制,实现社区微网系统中的产消者自主能量管理以及自主竞价策略最终达成P2P能量交易。首先,考虑产消者的差异化特征,对CMS内部资源自主形成的4种典型类型的产消者进行整合和建模。然后,基于连续双边拍卖机制搭建了日前阶段多类型产消者P2P能量交易框架,各产消者考虑历史交易决策信息以个体利益最大为目标,并通过交互有限的信息,在产消者之间互相发起交易请求,实现CMS内产消者之间P2P能量交易。针对在交易过程中产消者可能出现的隐私性保护,提出基于多段报价机制的P2P竞价策略,既能降低交易方的信息暴露风险,又能减少单次竞价决策的风险度,保证产消者收益稳定。最后,通过算例验证文中设计的P2P交易机制能够有效保护产消者的交易隐私性的同时,提高其经济效益。
文摘随着分布式能源(distributed energy resources,DERs)以及需求侧柔性资源的广泛应用,城市园区微网系统(urban community microgrid system,UCMS)的架构、形态和运行方式将发生根本性改变,终端用户在微网中的身份将从传统的消费者转变为兼具能量生产与消费能力的产消者。通过建立端对端(peer-to-peer,P2P)能量交易机制,各个产消者之间可以在市场的引导下实现能量资源的协调优化,有效提升经济效益、供需平衡以及可再生能源就地消纳等UCMS全局效用。为此,分别从交易机制、运营策略以及建模分析3个角度,对城市园区微网系统P2P能量交易技术的研究现状进行了分析,希望能够对未来UCMS市场化运营提供一定的思考和借鉴。
