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计及柔性负荷调节能力的有源配电网动态优化方法
引用本文:刘永梅,王金丽,杨红磊,李运硕,谢伟.计及柔性负荷调节能力的有源配电网动态优化方法[J].高电压技术,2021,47(1):73-80.
作者姓名:刘永梅  王金丽  杨红磊  李运硕  谢伟
作者单位:中国电力科学研究院有限公司,北京100192;国网上海能源互联网研究院有限公司,北京100192;中国电力科学研究院有限公司,北京100192;国网上海市电力公司,上海200122
基金项目:国家重点研发计划(2017YFB0902800)。
摘    要:为了解决复杂配电网的优化运行问题,提出了一种配电网综合运行优化方法。首先,通过量测数据获取配电网运行状态,当配电网出现电压异常或过载时,通过粒子群算法调整分布式电源出力值和柔性负荷值,优化配电网运行状态;检测配电网是否恢复正常,若配电网运行指标未恢复正常,进一步对配电网的网络拓扑进行重构优化,继而进一步调整分布式电源出力值和柔性负荷值,优化配电网运行状态。IEEE 33节点和实际85节点配电网两个算例结果表明,优化方法可降低配电网网损量39.9%,同时提高分布式电源出力29.4%,并使得配电网的柔性负荷补偿成本降低50%,激励负荷成本值降低14.8%。该方法充分利用了柔性负荷的调节能力,实现了供需互动。

关 键 词:动态优化  粒子群算法  分布式电源出力  柔性负荷  网络重构

Dynamic Optimal Method of Distribution Network in Consideration of Flexible Load Adjustment Capability
LIU Yongmei,WANG Jinli,YANG Honglei,LI Yunshuo,XIE Wei.Dynamic Optimal Method of Distribution Network in Consideration of Flexible Load Adjustment Capability[J].High Voltage Engineering,2021,47(1):73-80.
Authors:LIU Yongmei  WANG Jinli  YANG Honglei  LI Yunshuo  XIE Wei
Affiliation:(China Electric Power Research Institute,Beijing 100192,China;State Grid Shanghai Energy Interconnection Research Institute,Beijing 100192,China;State Grid Shanghai Municipal Electric Power Company,Shanghai 200122,China)
Abstract:A comprehensive operation optimization method of distribution network is proposed to solve the optimization problem of complex distribution network. Firstly, the operation status of distribution network is obtained by measuring data. When the voltage of distribution network is abnormal or overloaded, the output value and flexible load value of distributed generation are adjusted by the particle swarm optimization algorithm to optimize the operation state of distribution network;whether the distribution network returns to normal is detected;if the operation index of distribution network is not restored to normal, the network topology of distribution network is further reconstructed and optimized. The output value and flexible load value of distributed generation are further adjusted to optimize the operation state of distribution network. Two examples of IEEE 33 bus distribution network and 85 bus distribution network show that the optimization method can reduce the loss of distribution network by 39.9%, and increase the output of distributed generation by 29.4%. The flexible load compensation cost and incentive load cost of distribution network can be reduced by 50% and 14.8%, respectively. This method makes full use of the regulation ability of flexible load and realizes the interaction between supply and demand.
Keywords:dynamic optimization  particle swarm algorithm  distributed generation output  flexible load  network reconfiguration
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