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Optimal Scheduling of Distribution Network Incorporating Topology Reconfiguration,Battery Energy System and Load Response 被引量:1
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作者 Xuebo Qiao Yuyao Luo +6 位作者 Juanxia Xiao Yong Li Li Jiang Xia Shao Jiazhu Xu Yi Tan Yijia Cao 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2022年第3期743-756,共14页
Distributed generation(DG)is becoming increasingly important due to the serious environmental pollution caused by conventional fossil-energy-based generation and the depletion of non-renewable energy.As the flexible r... Distributed generation(DG)is becoming increasingly important due to the serious environmental pollution caused by conventional fossil-energy-based generation and the depletion of non-renewable energy.As the flexible resources in the active distribution network(ADN),battery energy system(BES)and responsive load(RL)are all able to assist renewable DG integration in day-ahead dispatch.In addition,the security and economic level can be significantly improved by adjusting network topology.Therefore,in this paper,a coordinated day-ahead scheduling method incorporating topology reconfiguration,BES optimization and load response is presented to minimize the total day-ahead operational costs in the ADN.Linearized current injection models are presented for renewable DG,RL and BES based on the linear power flow model,and an extensible linear switching operations calculation(ELSOC)method is proposed to address the network reconfiguration.Thus,a mixed integer linear programming(MILP)model is proposed for optimal coordinated operation of an ADN.The correctness and effectiveness of the proposed method are demonstrated by simulations on a modified test system.In addition,the combined scenario and Monte-Carlo method is used to handle the uncertainties of loads and DGs,and the results of different uncertainties can further verify the feasibility of the proposed model. 展开更多
关键词 Active distribution network battery energy system linearized current injection models mixed integer linear programming network topology reconfiguration responsive load
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