Hybridization of particle Swarm Optimization with Bat Algorithm for optimal reactive power dispatch

• Main Author: Agbugba, Emmanuel Emenike
• Other Authors: Wang, Zenghui
• Format: Others
• Language: en
• Published: 2018
• Subjects: Hybridization; Hybrid Particle Swarm Optimization (HPSOBA); Modified Hybrid Particle Swarm Optimization (MHPSOBA); Optimal Power Flow (OPF); Optimal Reactive Power Dispatch (ORPD); Particle Swarm Optimization (PSO); Bat Algorithm (BA); Active power loss minimization; Benchmark functions; Distributed Generation (DG); Conventional optimization technique; Evolutionary optimization technique; Artificial intelligence; Equality constraints; Inequality constraints; Penalty function; 620.00151; Mathematical optimization; Swarm intelligence; Engineering mathematics > Data processing; MATLAB; Computer-aided engineering
• Online Access: Agbugba, Emmanuel Emenike (2017) Hybridization of particle Swarm Optimization with Bat Algorithm for optimal reactive power dispatch, University of South Africa, Pretoria, <http://hdl.handle.net/10500/23630>; http://hdl.handle.net/10500/23630

This research presents a Hybrid Particle Swarm Optimization with Bat Algorithm (HPSOBA) based approach to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this project is minimization of the active power transmission losses by optimally setting the control variables within their limits and at the same time making sure that the equality and inequality constraints are not violated. Particle Swarm Optimization (PSO) and Bat Algorithm (BA) algorithms which are nature-inspired algorithms have become potential options to solving very difficult optimization problems like ORPD. Although PSO requires high computational time, it converges quickly; while BA requires less computational time and has the ability of switching automatically from exploration to exploitation when the optimality is imminent. This research integrated the respective advantages of PSO and BA algorithms to form a hybrid tool denoted as HPSOBA algorithm. HPSOBA combines the fast convergence ability of PSO with the less computation time ability of BA algorithm to get a better optimal solution by incorporating the BA’s frequency into the PSO velocity equation in order to control the pace. The HPSOBA, PSO and BA algorithms were implemented using MATLAB programming language and tested on three (3) benchmark test functions (Griewank, Rastrigin and Schwefel) and on IEEE 30- and 118-bus test systems to solve for ORPD without DG unit. A modified IEEE 30-bus test system was further used to validate the proposed hybrid algorithm to solve for optimal placement of DG unit for active power transmission line loss minimization. By comparison, HPSOBA algorithm results proved to be superior to those of the PSO and BA methods. In order to check if there will be a further improvement on the performance of the HPSOBA, the HPSOBA was further modified by embedding three new modifications to form a modified Hybrid approach denoted as MHPSOBA. This MHPSOBA was validated using IEEE 30-bus test system to solve ORPD problem and the results show that the HPSOBA algorithm outperforms the modified version (MHPSOBA). === Electrical and Mining Engineering === M. Tech. (Electrical Engineering)