Optimal Placement and Control of Unified Power Flow Control devices using Evolutionary Computing and Sequential Quadratic Programming

A crucial factor effecting modern power systems today is power flow control. An effective means for controlling and improving power flow is by installing fast reacting devices such as a unified power flow controller (UPFC). For maximum positive impact of this device on the power grid, it should be installed at an optimal location and employ an optimal realtime control algorithm. This paper proposes the combination of an evolutionary algorithm (EA) to find the optimal location and sequential quadratic programming (SQP) to optimize the UPFC control settings. Simulations are conducted using the classic IEEE 118 bus test system. For comparison purposes, results for the combination of a greedy placement heuristic (H) and the SQP control algorithm are provided as well. The EA+SQP combination is shown to outperform the H+SQP approach