陈卓,郭寅远,温彦军,马留军,王留涛,吉小鹏
CHEN Zhuo,GUO Yinyuan,WEN Yanjun,MA Liujun,WANG Liutao,JI Xiaopeng

• 1:许昌开普检测研究院股份有限公司
• 2:江苏金智科技股份有限公司
• 3:南京信息工程大学电子与信息工程学院

摘要(Abstract)：

针对目前分布式光伏电源大规模接入配电网中带来的问题，提出了基于广义Benders分解的分布式光伏接入容量规划方法。采用数据驱动顺序选择方法确定C-Vine Copula模型中变量的最优顺序，结合拉丁超立方采样方法和场景评估指标，构建典型负荷-资源相关性场景。在生成的典型场景的基础上，建立了基于广义Benders分解的光伏接入规划模型。该模型分为光伏规划主问题与配电网运行子问题，采用线性规划与最优潮流的方法进行求解。在IEEE 33节点系统网架开展算例分析，结果表明，提出的典型场景生成方法比传统方法的资源误差与负荷误差减少50%以上；规划模型求解所需的计算量减小为原来的11%，计算时间缩短为原来的9%。
In response to the challenges of large-scale integration of distributed photovoltaic(PV) sources into distribution networks, an integration capacity planning method for distributed photovoltaic sources based on generalized Benders decomposition(GBD) is proposed. The approach utilizes a data-driven sequential selection method to determine the optimal sequence of variables in the C-Vine Copula model. In combination with Latin hypercube sampling(LHS) and scenario evaluation indicators, typical load-resource correlation scenarios are constructed. Building upon these generated typical scenarios, the paper has established a photovoltaic source integration planning model based on the GBD. This model comprises a main problem for photovoltaic source planning and a sub-problem for distribution network operation, solved using linear programming and optimal power flow methods, respectively.Case studies are conducted on the grid framework of the IEEE 33-bus system. The results demonstrate that the proposed method for generating typical scenarios reduces resource and load errors by over 50% compared to traditional methods. Moreover, the computational complexity of the planning model is reduced by 11%, and the computation time is shortened by 9% compared to previous approaches.

关键词(KeyWords)： C-Vine Copula;数据驱动顺序选择;广义Benders分解;光伏规划主问题;配电网运行子问题
C-Vine Copula;data-driven sequential selection method;GBD;main problem of photovoltaic source planning;sub-problem of distribution network operation

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划（2018YFB2100100）

作者(Author): 陈卓,郭寅远,温彦军,马留军,王留涛,吉小鹏
CHEN Zhuo,GUO Yinyuan,WEN Yanjun,MA Liujun,WANG Liutao,JI Xiaopeng

DOI: 10.19585/j.zjdl.202406004

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