University of Mohaghegh Ardabili Journal of Operation and Automation in Power Engineering 2322-4576 5 1 2017 06 01 Solving Multi-objective Optimal Power Flow Using Modified GA and PSO Based on Hybrid Algorithm حل سیستم چند هدفه پخش بار بهینه با الگوریتم ژنتیک اصلاح شده و توده ذرات بر اساس الگوریتم ترکیبی 51 60 548 10.22098/joape.2017.548 EN R. Effatnejad Depatment of Electrical Engineering, Karaj Branch,Islamic Azad University H. Aliyari Faculty of Electrical and Biomedical Engineering Qazvin Branch, Islamic Azad University M. Savaghebi Department of Electrical Engineering, Karaj branch, Islamic Azad University, Journal Article 2016 07 10 <em>The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage stability and voltage profile, considering environmental issues. Therefore, the OPF problem is a nonlinear optimization problem consisting of continuous and discontinuous variables. To solve it, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and a new hybrid algorithm combining modified Particle Swarm Optimization (PSO) and Genetic algorithm (GA) methods are proposed. In this method, each of the algorithms is performed in its procedure and generates the primary population; then, the populations are ordered and from among them, populations with the highest propriety function are selected. The first population that guesses will enter the two algorithms’ procedures for generating the new population. Note that the inputs of the two algorithms are the same; then, generates a new population. Now, there are three groups of populations: one created by modified GA, one created by modified PSO, and the other is the first initial population, and then sorted with the described sorting method.</em> https://joape.uma.ac.ir/article_548_7a3002387aa78c9311357017a7169b5e.pdf