Two-Stage Optimal Location Allocations of DPFC Considering Wind and Load Uncertainty

Abstract

Distributed power flow controller (DPFC) has a considerable potential to regulate the power flow and generator rescheduling continuously. This study presents a novel two-stage stochastic model for optimal location allocations of the DPFC coupled with the interactions of DPFC to search for the optimal solutions. The Benders decomposition is utilized to reformulate the two-stage problem into the master problem and the subproblem. The optimal solution can be easily obtained with the master problem and subproblem iteratively. The relaxed DC power flow with a DPFC in the master problem accelerates the efficiency of optimal locations under a base condition. Slack variables are incorporated in the subproblem to check the feasibility of relaxed AC power flow. The optimal compensation levels of DPFC at different load/wind scenarios are optimized in the subproblem. The IEEE 118 bus system is conducted to verify the performance of the proposed procedure. The DPFC has positive impacts on unit costs, voltage performance, wind absorption, and power losses. Detailed simulation results illustrate the effect of the proposed approach.