Convex Optimal Power Flow Based on Power Injection-based Equations and Its Application in Bipolar DC Distribution Network

TL;DR

This paper develops a convex optimal power flow model for bipolar DC distribution networks using power injection equations and second-order cone programming, enabling more accurate planning and operation analysis.

Contribution

It introduces a novel convex OPF model based on power injection equations and SOCP, specifically tailored for bipolar DC distribution networks.

Findings

Model effectively captures bipolar DCDN power characteristics.

Convex model improves solution accuracy and computational efficiency.

Case studies validate practical applicability in capacity planning and operation optimization.

Abstract

Optimal power flow (OPF) is a fundamental tool for analyzing the characteristics of bipolar DC distribution network (DCDN). However, existing OPF models face challenges in reflecting the power distribution and exchange of bipolar DCDN directly since its decision variables are voltage and current. This paper addresses this issue by establishing a convex OPF model that can be used for the planning and operation of bipolar DCDN. First, the power flow characteristics of bipolar DCDN are revealed through power injection-based equations, upon which the original OPF model is established. Next, the original OPF model undergoes a transformation into a convex OPF model based on second-order cone programming (SOCP) through variable substitution, secondorder cone relaxation, McCormick relaxation, and first-order Taylor expansion, respectively. Finally, the sequence bound tightening algorithm (STBA) is employed to tighten the boundaries of McCormick envelopes in each iteration to ensure the exactness of the convex OPF model. The effectiveness of this novel OPF model for bipolar DCDN is verified through two case studies, i.e., capacity configuration of distributed generation (DG) and operation optimization of bipolar DCDN.