基于广义Benders分解的分布式光伏接入容量规划方法
An integration capacity planning method for distributed photovoltaic sources based on generalized Benders decomposition
陈卓 1郭寅远 1温彦军 2马留军 2王留涛 2吉小鹏3
作者信息
- 1. 许昌开普检测研究院股份有限公司,河南 许昌 461000
- 2. 江苏金智科技股份有限公司,南京 210000
- 3. 南京信息工程大学 电子与信息工程学院,南京 210044
- 折叠
摘要
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%.
Abstract
In response to the challenges of large-scale integration of distributed photovoltaic(PV)sources into dis-tribution networks,an integration capacity planning method for distributed photovoltaic sources based on general-ized 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 sam-pling(LHS)and scenario evaluation indicators,typical load-resource correlation scenarios are constructed.Build-ing 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 pro-posed 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
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Key words
C-Vine Copula/data-driven sequential selection method/GBD/main problem of photovoltaic source planning/sub-problem of distribution network operation引用本文复制引用
基金项目
国家重点研发计划(2018YFB2100100)
出版年
2024
国家科技期刊平台
NSTL
万方数据