Abstract
Power system optimization, especially in the field of operation, has experienced essential changes in recent years regarding the introduction of the concept of the hybrid energy system (HES). As a result, the optimal power flow (OPF) problem, as the cornerstone of power system operation studies, has faced new challenges regarding the modeling of these complicated systems. In this article, the OPF in a HES is proposed using the hybrid particle swarm optimization-genetic algorithm (HPSO-GA) approach considering the fuel cost as the main objective and the emission cost as the primary objective function. As the mentioned objectives are counterintuitive, to obtain the optimal point, they should be considered simultaneously. To overcome this problem, the Pareto optimal front (POF) is applied and the multi-criteria technique for order performance by similarity to ideal solution (TOPSIS) is used simultaneously. The results of the simulation case study on an improved IEEE 14-bus standard system confirmed the performance of the proposed method against the mathematical method by applying MATLAB optimization.
Additional information
Notes on contributors
Navid Azadi
Navid Azadi was born in Ilam, Iran, in 1993. He received the B.Sc., and the M.Sc. degrees from Razi University, Kermanshah, Iran, in 2016, and 2019, all in Electrical Engineering. His research interests include power system optimization, operation, and control, smart grids, and multi- carrier energy system.
Hamdi Abdi
Hamdi Abdi was born in Paveh, Iran, in July 1973. He received the B.Sc. degree from Tabriz University, Tabriz, Iran, in 1995, and the M.Sc. and Ph.D. degrees from Tarbiat Modares University, Tehran, Iran, in 1999 and 2006, respectively, all in electrical engineering. He is currently a Full Professor in the Department of Electrical Engineering, Razi University, Kermanshah, Iran. His research interests include power system optimization, operation and planning, smart grids, demand response, multicarrier energy system, energy hub, load forecasting, and design of electrical and control systems for industrial plant.