A Novel Dynamic Mind Evolutionary Algorithm for Unit Economic Dispatch Problem

Abstract:

Economic Dispatch (ED) is one of the optimization issues for improving the economic benefit of power plants. According to the framework of Mind Evolutionary Algorithm, we proposed a new developed Dynamic Mind Evolutionary Algorithm (DMEA) to solve the ED problem. Specifically, the economic model in power plants was built firstly. Secondly, an individual evaluation function is presented. Thirdly, simplex method was used to search the extreme value of each sub-group. Then, sub-groups are separated at the step similartaxis operator, while the sub-groups with the same extreme value are assembled at the step dissimilation operator, so that the extreme value of each local space can be found efficiently. Ultimately, it can avoid repeated search for the same space due to the record of the searched area. Including DMEA, three different methods were compared under the same illustration. The simulation results demonstrate the effect of DMEA.

• Periodical: Applied Mechanics and Materials (Volumes 347-350)
• Pages: 2329-2334
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.347-350.2329
• Online since: August 2013
• Authors: Ping Fei Zhu, Lan Xiang Wang, Yu Kai Li, Yu Yang Lai
• Keywords: Dynamic Mind Evolutionary Algorithm, Economic Dispatch, Power Plant

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