Application of improved particle swarm optimization in economic dispatch of power systems

• Main Author: Gninkeu Tchapda, Ghislain Yanick
• Other Authors: Wang, Z.
• Format: Others
• Language: en
• Published: 2018
• Subjects: Particle swarm optimization; Economic dispatch; Swarm intelligence; Genetic algorithm; Evolutionary algorithm; Bat algorithm; Cuckoo search algorithm; Power systems; Levy flight; Random search; Thermal power plant; 621.31; Genetic algorithms; Electric power systems
• Online Access: Gninkeu Tchapda, Ghislain Yanick (2018) Application of improved particle swarm optimization in economic dispatch of power systems, University of South Africa, Pretoria, <http://hdl.handle.net/10500/24428>; http://hdl.handle.net/10500/24428

Economic dispatch is an important optimization challenge in power systems. It helps to find the optimal output power of a number of generating units that satisfy the system load demand at the cheapest cost, considering equality and inequality constraints. Many nature inspired algorithms have been broadly applied to tackle it such as particle swarm optimization. In this dissertation, two improved particle swarm optimization techniques are proposed to solve economic dispatch problems. The first is a hybrid technique with Bat algorithm. Particle swarm optimization as the main optimizer integrates bat algorithm in order to boost its velocity and to adjust the improved solution. The second proposed approach is based on Cuckoo operations. Cuckoo search algorithm is a robust and powerful technique to solve optimization problems. The study investigates the effect of levy flight and random search operation in Cuckoo search in order to ameliorate the performance of the particle swarm optimization algorithm. The two improved particle swarm algorithms are firstly tested on a range of 10 standard benchmark functions and then applied to five different cases of economic dispatch problems comprising 6, 13, 15, 40 and 140 generating units. === Electrical and Mining Engineering === M. Tech. (Electrical Engineering)