基于改进Benders分解的配电网扩展规划机会约束优化方法

为了解决已有配电系统规划中非线性潮流模型建模问题和不确定性优化效率问题,本文提出了基于双线性Benders分解的配电网扩展规划机会约束优化方法。首先通过在规划投资层面和运行优化层面进行分阶段,构建了两阶段随机混合整数二阶锥规划模型;然后为了避免极端场景下导致的高昂投资成本,进一步扩展了传统的Benders分解方法,设计了基于双线性Benders分解的机会约束优化方法。通过三个算例系统验证了本文所提出方法的卓越的优化性能。

Chance-constrained optimization method for distribution network expansion planning based on modified Benders decomposition

In order to solve the problem of nonlinear power flow model modeling and uncertain optimization efficiency in existing distribution system planning, a chance constrained optimization method for distribution network expansion planning based on bilinear Benders decomposition was proposed in this paper. Firstly, a two-stage stochastic mixed integer second-order cone programming model was constructed by stages at the planning investment level and operation optimization level; Then, in order to avoid the high investment cost caused by extreme scenarios, the traditional Benders decomposition method is further extended, and a chance constrained optimization method based on bilinear Benders decomposition was designed. The excellent optimization performance of the proposed method was verified by three examples.