Application of Swarm-Based Optimization Algorithms for Solving Dynamic Economic Load Dispatch Problem

Dynamic economic load dispatch is one of the most important roles of powergeneration’s operation and control. It determines the optimal controls of productionof generator units with predicted load demand over a certain period of time.Economic dispatch a minimum production cost is one of the most importantsubjects in the power network’s operation, which is a complicated nonlinearconstrained optimization problem. Since dynamic economic load dispatch wasintroduced, several intelligent methods have been used to solve this problem In thispaper, an Improved Particle Swarm Optimizer (IPSO) and Water Cycle optimizer(WCO), as swarm-based optimization algorithms, have been proposed to solvedynamic economic load dispatch problem and their results compare with each other.These algorithms are applied to a dynamic economic dispatch problem for 6-unitpower systems with a 24-h load demand ot each one hour time intervals. The goal ofthe research is categorized in two parts; first of all, introduction of application ofnew heuristic method for solving economic load dispatch problem and second,comparison between two swarm-based algorithms. Obtained results show that WCOis very fast and also reach to better results and minimum.

Keywords:

Dynamic Economic Load Dispatch , Improved Particle Swarm Algorithm , Power Loss , Water Cycle Algorithm