浙江电力

2024, v.43;No.340(08) 20-27

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兼顾风-光-荷不确定性与相关性的配电网多目标重构方法
A multi-objective reconfiguration method for distribution networks considering the wind-photovoltaic-load uncertainty and correlation

李晏君,何雨微,盛方,许嘉轩,王伟曦,许恩超,项翔
LI Yanjun,HE Yuwei,SHENG Fang,XU Jiaxuan,WANG Weixi,XU Enchao,XIANG Xiang

摘要(Abstract):

随着新型电力系统的推进,分布式电源大规模并网给配电网优化运行带来了挑战。对此,提出了兼顾风-光-荷不确定性与相关性的配电网多目标重构方法。应用Copula理论构建相关性模型并通过Spearman秩相关系数获得风速-辐照度-负荷相关性样本;引入复杂网络理论,给出计及风电、光伏出力间歇性的网络脆弱度;以满足一定置信水平下网损、网络脆弱度最低及操作开关次数最少为目标,建立基于机会约束规划考虑风-光-荷出力不确定性的多目标协同优化重构模型,给出参数自适应算法对该模型予以求解。通过算例验证了所提方法兼顾了有效性及可用性。
With the advancement of new-type power systems, the large-scale integration of distributed generation(DG) poses challenges to the optimal operation of distribution networks. In response, a multi-objective reconfiguration method for distribution networks is proposed, which takes account of the wind-photovoltaic-load uncertainty and correlation. The Copula theory is applied to construct a correlation model, and wind speed-irradiance-load correlation samples are obtained through Spearman's rank correlation coefficient. By introducing complex network theory, the paper addresses the network vulnerability considering the intermittency of wind and photovoltaic output powers.To minimize network losses, network vulnerability, and switching times of switchgears at a certain confidence level, a multi-objective coordinated optimization reconfiguration model considering the uncertainty of wind, solar, and load output is established based on chance-constrained programming, and a parameter adaptive algorithm is applied to solve the model. Case studies verify that the proposed method can balance effectiveness and usability.

关键词(KeyWords): 多目标重构;相关性;不确定性;Copula理论;网络脆弱度
multi-objective reconfiguration;correlation;uncertainty;Copula theory;network vulnerability

Abstract:

Keywords:

基金项目(Foundation): 国家电网有限公司科技项目(5700-202419238A-1-1-ZN)

作者(Author): 李晏君,何雨微,盛方,许嘉轩,王伟曦,许恩超,项翔
LI Yanjun,HE Yuwei,SHENG Fang,XU Jiaxuan,WANG Weixi,XU Enchao,XIANG Xiang

DOI: 10.19585/j.zjdl.202408003

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