中国电机工程学报2025，Vol.45Issue(19)：7552-7564,中插27-中插32,19.DOI:10.13334/j.0258-8013.pcsee.240784
基于非确定性关联场景聚类与线性约束的交直流混合配电网源网统一联合规划
Unified Joint Planning for Generations and Networks of Hybrid AC/DC Distribution Based on Uncertain Correlated Scene Clustering and Linear Constraints
摘要
Abstract
The hybrid AC/DC topologies have become inevitable for future distribution networks to efficiently deal with multiple types of distributed generations(DGs)and loads integrated into the grid.How to realize the planning and solution of hybrid AC/DC distribution networks has become an urgent problem.Therefore,an uncertain correlated scene clustering and linear constraints-based unified joint planning model for generations and networks of hybrid AC/DC distribution networks is proposed.The set of uncertainty-related scenarios for multiple types of DGs and loads is established by considering the correlation between different types of DGs and loads,and an improved K-means is used to achieve scene clustering.A unified characterization method including the grid structures and DG allocations is proposed for hybrid AC/DC distribution networks.On this basis,a unified Kirchhoff's power flow constraint model for the distribution network is constructed which is linearly transformed by the Big-M method.Finally,the Gurobi solver is used to solve the unified joint planning for DGs and networks of hybrid AC/DC distribution networks with the goal of optimal economy.The effectiveness and superiority of the proposed planning model has been verified on a 13-bus distribution network and an area-interconnected distribution network.关键词
交直流混合配电网/联合规划/统一结构表征/关联场景聚类/基尔霍夫线性约束/IWO-K-means算法/Big-M法Key words
hybrid AC/DC distribution network/joint planning/unified structure characterization/correlated scene clustering/Kirchhoff linear constraint/IWO-K-means algorithm/Big-M method分类
信息技术与安全科学引用本文复制引用
成龙,李国庆,郑佳锐,王振浩..基于非确定性关联场景聚类与线性约束的交直流混合配电网源网统一联合规划[J].中国电机工程学报,2025,45(19):7552-7564,中插27-中插32,19.基金项目
国家自然科学基金项目(U2066208) （U2066208）
东北电力大学博士科研启动基金项目(BSJXM-2025101).Project Supported by National Natural Science Foundation of China(U2066208) （BSJXM-2025101）
Doctoral Research Start-up Foundation of Northeast Electric Power University(BSJXM-2025101). （BSJXM-2025101）
