Optimal power flow with UPFC using self-adaptive differential evolutionary technique under security constraints

Abstract

The self-adaptive differential evolutionary (SADE) algorithm is developed for controlling and maintaining the power flow using Unified Power Flow Controller (UPFC) under practical security constraints (SCs). The two important tuning parameters of Differential Evolutionary Algorithm (DEA) are so developed that they become automatically adaptive throughout the whole iteration. The UPFC is modeled considering losses of the converters, transmission loss in UPFC and losses of the coupling transformers. The mathematical modeling of the cost function is developed considering practical SCs. The proposed algorithm and other evolutionary algorithms are applied on the IEEE standard and ill-conditioned test systems. With and without UPFC, the power flow and line losses are observed for the three sets of user-defined active and reactive power. Comparing other evolutionary techniques, best results are obtained for the proposed SADE algorithm. Using UPFC, power flow is enhanced and maintained at the specified set-value. Line losses are also reduced.