Neighborhood Search Operator Tuned Differential Evolution for Solving Non Convex Economic Dispatch Problem

Abstract

This article addresses a novel and effective algorithm for solving the economic load dispatch (ELD) problem of generating units. Generator constraints, such as valve point loading, ramp rate limits and prohibited operating zones are taken into account in the problem formulation of ELD. The cost function of the generating units exhibits nonconvex characteristics, as valve-point effects are modeled and included as rectified sinusoid components in its conventional formulation. The paper investigates the application of neighborhood search operator (NSO) to tune Differential Evolution (DE) algorithm for solving ELD problem considering non-smooth characteristics (NSELD). The objective of the presented method is to perform a neighborhood search for each population member and to accelerate towards finding the global solution. The method is also allowed to explore the search space for new promising areas by replacing weak solutions with randomly selected individuals. The idea of neighborhood search increases the exploitation ability, whereas the replacement feature improves the exploration ability of the technique. To demonstrate its efficiency and feasibility, the NSO tuned DE is applied to solve NSELD problem of power systems with 6 and 13 units. The simulation results obtained from the NSO tuned DE was compared to those from previous literature in terms of solution quality and computational efficiency. It is shown that, the proposed technique for non-convex ELD problem generates quality solutions reliably.