| 引用本文: | 程 杉,汪业乔,廖玮霖,左先旺,代 江.含电动汽车的新能源微电网多目标分层优化调度[J].电力系统保护与控制,2022,50(12):63-71.[点击复制] |
| CHENG Shan,WANG Yeqiao,LIAO Weilin,ZUO Xianwang,DAI Jiang.Bi-level multi-objective optimization of a new energy microgrid with electric vehicles[J].Power System Protection and Control,2022,50(12):63-71[点击复制] |
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| 摘要: |
| 电动汽车(EV)和新能源微电网(NEMG)分属不同利益主体。针对EV接入NEMG后的经济运行问题，建立计及EV有序充放电行为和车主综合满意度的NEMG多目标分层调度数学模型并提出求解计算方法。EV层以最大化车主的综合满意度为目标，通过CPLEX软件求解得到EV充放电计划并传递给NEMG层。NEMG层基于EV充放电计划调整微电网内部可控分布式电源出力，以达到最小化系统综合成本和交互功率波动的目标。为求解该高维、非线性和多目标模型，提出基于可信度的三黑洞系统捕获策略多目标粒子群优化算法。仿真结果表明，含EV微电网分层架构相比不分层架构能实现EV和NEMG的互利共赢，验证了所提方法的科学性及有效性。 |
| 关键词: 电动汽车 新能源微电网 满意度 分层优化 多目标粒子群优化 |
| DOI：DOI: 10.19783/j.cnki.pspc.211149 |
| 投稿时间：2021-08-23修订日期：2021-12-08 |
| 基金项目:国家自然科学基金项目资助(51607105) |
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| Bi-level multi-objective optimization of a new energy microgrid with electric vehicles |
| CHENG Shan,WANG Yeqiao,LIAO Weilin,ZUO Xianwang,DAI Jiang |
| (1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China;
2. Yichang Key Laboratory of Intelligent Operation and Security Defense of Power System (CTGU), Yichang 443002,
China; 3. DC Operation Maintenance Company of State Grid Hubei Electric Power Co., Ltd., Yichang 443000, China;
4. Electric Power Dispatching and Control Center of Guizhou Power Grid Co., Ltd., Guiyang 550002, China) |
| Abstract: |
| Electric vehicles (EVs) and the New Energy Microgrid (NEMG) belong to different stakeholders. There can be economic operational problems after EVs are connected to an NEMG. A mathematical model of NEMG multi-objective hierarchical scheduling considering EV orderly charge and discharge behavior and owner’ comprehensive satisfaction is established, and calculation method for analysis is proposed. The EV layer aims to maximize the comprehensive satisfaction of the vehicle owner. The EV charge and discharge plan is established by CPLEX software and transmitted to the NEMG layer. The NEMG layer adjusts the output of controllable distributed generation in the microgrid based on the EV charge and discharge plan to minimize the comprehensive cost of system and interactive power fluctuation. To analyze the high-dimensional, nonlinear and multi-objective model, a multi-objective particle swarm optimization algorithm of a three-black-hole-system capture based on reliability is presented. The simulation results show that the layered architecture of the microgrid with EV can achieve mutual benefit and win-win of EV and NEMG compared with a non-layered architecture. This verifies the validity and effectiveness of the proposed method.
This work is supported by the National Natural Science Foundation of China (No. 51607105). |
| Key words: electric vehicle new energy microgrid satisfaction layered optimization multi-objective particle swarm optimization |
