| 引用本文: | 卞栋,卫志农,黄向前,等.电力市场中含分布式电源的配电网重构模型[J].电力系统保护与控制,2013,41(11):117-123.[点击复制] |
| BIAN Dong,WEI Zhi-nong,HUANG Xiang-qian,et al.Distributed network reconfiguration model including distributed generation in the electricity market[J].Power System Protection and Control,2013,41(11):117-123[点击复制] |
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| 摘要: |
| 电力市场体制中，分布式电源(DG)一般由用户所有，具有削峰、紧急功率支持等诸多作用。在电力市场的背景下，为了使得配电网在正常运行条件下最大程度的得到优化，将DG视为可调度设备，将DG注入功率作为优化变量，加入配电网重构综合优化的过程。提出把DG注入功率、网络损耗、效益分配按电价转换成综合费用，以综合费用最小为目标函数，采用提出的改进量子进化算法(IQEA)进行求解。该改进算法采用改良策略，提高了搜索效率，结合基于环路的量子坍塌策略避免了不可行解的产生，提高了重构效率。采用IEEE33节点测试系统进行仿真计算，结果表明了所提方法的正确性和有效性。 |
| 关键词: 分布式电源 配电网重构 综合优化 综合费用 改进量子进化算法 |
| DOI：10.7667/j.issn.1674-3415.2013.11.019 |
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| 基金项目:国家自然科学基金项目(51277052, 51107032, 61104045) |
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| Distributed network reconfiguration model including distributed generation in the electricity market |
| BIAN Dong1,WEI Zhi-nong1,HUANG Xiang-qian2,SUN Guo-qiang1,SUN Yong-hui1 |
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| Abstract: |
| In the electricity market system, distributed generations (DGs) are usually owned by users, which can eliminate the peak load and support emergency power. In the background of electricity market, in order to optimize the distribution network at the greatest degree, DGs in this paper will be considered as dispatched equipments during the distribution network reconfiguration optimization process, and the injected power is regarded as optimization variables. DG injected power, network loss, and benefit distribution are changed into comprehensive costs according to tariff, and the minimum of costs is taken as the objective function, and improved quantum evolutionary algorithm (IQEA) is proposed to solve the reconfiguration problem. The improved algorithm uses modified strategy to enhance the efficiency of search, combining with loop quantum collapse strategy to avoid the infeasible solutions to improve the configuration efficiency. The effectiveness and correctness of the method is verified through the simulation results of IEEE 33-node system. |
| Key words: distributed generation network reconfiguration integrated optimization comprehensive cost improved quantum evolution algorithm |
