ATC-Based Scenario Decomposition Algorithm for Optimal Power Flow of Distribution Networks Considering High Photovoltaic Penetration

TL;DR

This paper introduces an ATC-based scenario decomposition algorithm for stochastic optimal power flow in distribution networks with high photovoltaic penetration, improving computational efficiency and scalability.

Contribution

It develops a novel ATC-based decomposition method that effectively solves large-scale stochastic OPF problems with high PV integration, overcoming dimensionality challenges.

Findings

Algorithm achieves global optimal solutions efficiently.

Parallel solving of subproblems enhances computational speed.

Method is validated on IEEE 33-bus and larger systems.

Abstract

This paper focuses on the analytical target cascading (ATC) based scenario decomposition method which applies to the stochastic OPF problem of distribution networks with high photovoltaic penetration. The original two-stage stochastic OPF model is decomposed into a master problem in the upper level and multiple subproblems in the lower level. This decomposition makes subproblems easier to be solved and can also effectively overcome the curse of dimensionality in the traditional scenario-based model. The global optimal solution can be obtained by only transferring some necessary coupling information between the upper and lower levels. Moreover, all the subproblems in the lower level can be solved in a parallel manner which improves the computational efficiency, in particular, for cases with a larger number of scenarios. Case studies on the IEEE 33-bus system and various larger systems verify the effectiveness and adaptability of the proposed algorithm.