Authors: Susanta Dutta; Provas Kumar Roy; Debashis Nandi
Addresses: Department of Electrical Engineering, Dr. B.C. Roy Engineering College, Durgapur, West Bengal, India ' Department of Electrical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, West Bengal, India ' Department of Information Technology, National Institute of Technology, Durgapur, West Bengal, India
Abstract: Evolutionary algorithms (EAs) are well-known optimisation approaches to deal with nonlinear and complex problems. However, most of these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. This paper presents a fast, efficient and relatively new krill herd algorithm (KHA) to find optimal location of unified power flow controller (UPFC) for solving the optimal power flow (OPF) problem taking nonlinearities of valve-point effects into consideration. The proposed algorithm is tested on standard IEEE 30-bus system incorporating single and multiple UPFC devices for two different load conditions. The simulation results of the proposed KHA method are compared with other well popular artificial intelligent techniques namely, particle swarm optimisation (PSO), differential evolution (DE), genetic algorithm (GA) and biogeography-based optimisation (BBO). The solutions obtained by the proposed KHA algorithm are quite encouraging and it is found that the proposed KHA-based approach is able to provide better solution than other evolutionary optimisation techniques in terms of cost, computation time and convergence.
Keywords: krill herd algorithm; KHA; evolutionary optimisation; unified power flow controller; UPFC; optimal power flow; OPF; FACTS; valve point effect.
International Journal of Power and Energy Conversion, 2018 Vol.9 No.3, pp.254 - 284
Received: 30 Jun 2015
Accepted: 26 Oct 2015
Published online: 12 Dec 2017 *