A fuzzy adaptive chaotic ant swarm optimization for economic dispatch

• Published in: International journal of electrical power & energy systems Vol. 34; no. 1; pp. 154 - 160
• Main Authors: Cai, Jiejin, Li, Qiong, Li, Lixiang, Peng, Haipeng, Yang, Yixian
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 2012; Elsevier
• Subjects: Algorithms; Applied sciences; Chaos theory; Dynamical systems; Dynamics; Economic dispatch; Electric power generation; Electrical engineering. Electrical power engineering; Electrical power engineering; Evolutionary algorithm; Exact sciences and technology; Formicidae; Fuzzy; Fuzzy adaptive chaotic ant swarm optimization; Fuzzy logic; Miscellaneous; Operation. Load control. Reliability; Optimization; Power networks and lines; Power system; Power system; Fuzzy adaptive chaotic ant swarm optimization; Economic dispatch; Evolutionary algorithm; Chaos; Performance evaluation; Dispatching problem; Fuzzy system; Optimization method; Fuzzy adaptive chaotic ant swarm; Thermal power; Electrical network; optimization; System simulation; Economic aspect; Economic impact; Effectiveness factor
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2011.09.020

► A FCASO algorithm is developed for solving the ED problems. ► The FCASO algorithm embeds a fuzzy system to dynamically tune the parameters of CASO. ► The application of the proposed method demonstrates its effectiveness to the ED problems. This paper developed a fuzzy adaptive chaotic ant swarm optimization (FCASO) algorithm for solving the economic dispatch (ED) problems of thermal generators in power systems. The FCASO algorithm introduces a fuzzy system to dynamically tune the characteristic parameters ψ d and r i of chaotic swarm optimization (CASO). The proposed method was applied to two cases of power systems. The simulation results demonstrate the applicability and effectiveness of the proposed algorithm to the practical ED problem.