An adaptive hybrid optimization algorithm for multi objective OPF with FACTS device

Abstract

This paper presents a Hybrid Particle Swarm Optimization with Differential Perturbed Velocity with adaptive acceleration coefficient (APSO-DV) to reduce generator fuel cost in Optimal Power Flow (OPF) control with a powerful Flexible Alternating Current Transmission Systems (FACTS) device such as Unified power Flow Controller (UPFC). The APSO-DV algorithm employs a strongly coupled differential operator acquired from differential evolution with adaptive acceleration coefficient in velocity update function of PSO. The purpose of UPFC is to control both the real and reactive power flows through transmission lines along with conventional equipment to reduce the operating cost. The strategic location of UPFC is found using Fuzzy approach by taking voltage magnitudes and voltage stability index (L-Index) as input parameters where L-Index is a real number which gives fair and consistent results for stability among different methods of voltage stability analysis. The feasibility of the proposed method has been tested on IEEE-30 bus system with three different objective functions that reflects fuel cost minimization, Power loss minimization and the combination of total fuel cost and system power loss. The test results show the effectiveness of robustness of the proposed approach and provides superior results compared with the existing results in the literature.