Abstract: This article presents an efficient approach for solving economic load dispatch (ELD) problems in different test power systems using a novel seeker optimization algorithm (SOA) In the SOA, the act of human searching capability and understanding are exploited for the purpose of optimization. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. In this paper, four test systems of the ELD problems are solved by adopting the SOA. A comparison of obtained simulation results by adopting the SOA is carried out with those published in the recent literatures. It is revealed from comparison that the optimization efficacy of the SOA over the prevailing optimization techniques for the solution of the multimodal, non-differentiable, highly non-linear, and constrained ELD problems is promising. Keywords: Economic load dispatch; multiple fuel options; seeker optimization algorithm; transmission loss; valve point loading The prime objective of the ELD problem is to minimize the total generation cost in power system (with an aim to deliver power to the end user at minimal cost) for a given load demand with due regard to the system equality and inequality constraints [1] . To date, various investigations on ELD problems have been undertaken as better solutions would result in more saving in the operating cost. Several classical methods, such as the lambda iteration (LI) method and gradient method have been applied to solve the ELD problems. But unfortunately, these methods are not feasible in practical power systems owing to the non-linear characteristics of the generators and non-smooth cost functions. Consequently, many powerful mathematical optimization techniques that are fast and reliable, such as non-linear programming and dynamic programming have been employed to solve the ELD problems. But due to the non-differential and non-convex characteristics of the cost functions, these methods are also unable to locate the global optima. Among the artificial intelligence methods, Hopfield neural networks [2] have been applied to solve the non-linear ELD problems, but these methods suffer from excessive numerical iterations, resulting in huge computations. Complex constrained ELD problems have been solved by many population-based optimization techniques in recent years. Some of the population-based optimization methods are genetic algorithm (GA) [3]
An approach named novel seeker optimization algorithm REF was developed to solve ELD problems.
Solution of Economic Load Dispatch Problems by a Novel Seeker Optimization Algorithm
International Journal on Electrical Engineering and Informatics
Engineering