Economic Load Dispatch—A Comparative Study on Heuristic Optimization Techniques With an Improved Coordinated Aggregation-Based PSO

Abstract

Abstract-In this paper an improved coordinated aggregation-based particle swarm optimization (ICA-PSO) algorithm is introduced for solving the optimal economic load dispatch (ELD) problem in power systems. In the ICA-PSO algorithm each particle in the swarm retains a memory of its best position ever encountered, and is attracted only by other particles with better achievements than its own with the exception of the particle with the best achievement, which moves randomly. Moreover, the population size is increased adaptively, the number of search intervals for the particles is selected adaptively and the particles search the decision space with accuracy up to two digit points resulting in the improved convergence of the process. The ICA-PSO algorithm is tested on a number of power systems, including the systems with 6, 13, 15, and 40 generating units, the island power system of Crete in Greece and the Hellenic bulk power system, and is compared with other state-of-the-art heuristic optimization techniques (HOTs), demonstrating improved performance over them.

Power search algorithm (PSA) for combined economic-emission dispatch problems considering valve point effects in economic load dispatch

“…A novel scheme of coding was developed for solving ELD problems with help of hybrid algorithm with simulated annealing (SA) and PSO [2]. A separate memory space was allocated for the best particle in the improved coordinated-aggregation-based PSO [3] algorithm. For solving the economic dispatch (ED) problem combined with VPL, a novel PSO [4] combined with the direct search method was advised.…”

An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects

“…The stopping criterion is set to 500. The result obtained from SQPSO is compared with some methods in the literature including IFEP [1], GA_PS_SQP [22], PC-PSO [23], SOH_PSO [23], NPSO [24] ,NPSO_LRS [24], PSO-GM [25], CBPSO_RVM [25], ICA-PSO [26], ACO [5], APSO(2) [27], HDE [28], ST-HDE [28] and IQPSO [29]. In addition, in order to compare the performance of the crossover operation in [18] with the proposed selective probability operator.…”

Fuzzy controlled parallel PSO to solving large practical economic dispatch

“…For better results and to get faster convergence, conventional PSO methods have been modified. In recent years various combined techniques have been studied to achieve this objective, these include [2]:…”