Mori, Hiroyuki (Nakano Campus, Meiji University), Ito, Akio (Meiji University), Chiang, Hsiao Dong (Cornell Univ)

A Discrete Predator-Prey Brain Storm Optimization Technique for Optimal Allocation of Micro-PMUs in Distribution System State Estimation

Scheduled for presentation during the Invited Session "Optimal operation and control in smart grids" (ThuS2T2), Thursday, July 11, 2024, 12:30−12:50, Grand Amphitheater

12th IFAC Symposium on Control of Power & Energy Systems, July 10-12, 2024, Rabat, Morocco

This information is tentative and subject to change. Compiled on January 17, 2025

Abstract

This paper proposes a practical method for determining the optimal allocation of micro-Phasor Measurement Units (μPMUs) for distribution system state estimation (DSSE). The proposed method formulates the state estimation based on the nest structure of DistFlow, which is used for power flow calculation in distribution systems due to the redundancy of less than 1. The use of μPMUs can significantly improve the accuracy of estimates. However, Distribution System Operators (DSOs) need to consider optimization constraints before deciding on the optimal location of μPMUs. To tackle this issue, this paper proposes the use of DPPBSO (Discrete Predator-Prey Brain Storm Optimization) of Evolutionary Computation (EC) to optimize the location of μPMUs. PPBSO is an extension method that applies the Predator-Prey strategy to Brain Storm Optimization (BSO), and DPPSO is the discrete version of PPBSO used in solving combinatorial optimization problems. The Predator-Prey strategy is critical in improving the solution candidates by intensifying and diversifying solution searches in EC. Simulation results demonstrate the effectiveness of the proposed method in the IEEE 69-node distribution system.