Solving Economic Dispatch using Artificial Eco System-based Optimization

被引:15
作者
Bhattacharjee, Kuntal [1 ]
Shah, Kathan [1 ]
Soni, Jatin [1 ]
机构
[1] Nirma Univ, Inst Technol, Dept Elect Engn, Ahmadabad 382481, Gujarat, India
关键词
artificial eco system; generation scheduling; prohibited operating zone; valve point loading; economic load dispatch; electrical power system optimization; CHEMICAL-REACTION OPTIMIZATION; LEARNING-BASED OPTIMIZATION; LOAD DISPATCH; SEARCH ALGORITHM; MUTATION;
D O I
10.1080/15325008.2021.2013995
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Economic Load Dispatch (ELD) is the most inherent necessity in power system operation to minimize the cost as well as the accomplishment of load demand abundantly. The main purpose of ELD is to satisfy load demand with the minimization of cost. Distinct techniques have been used for resolving the ELD problem. This paper introduces a robust and effective technique named Artificial Eco System Optimization (AEO) Algorithm to solve ELD. AEO is a population-based optimizer stimulated by the flow of energy into the Earth's ecosystem. This algorithm shows three distinct functions of living organisms, including production, consumption, and decomposition. By accomplishing three operator producer, consumer, and decomposer whole algorithm works and balances between the exploitation and the exploration phases of the technique. For solving the ELD problem, AEO has been implemented on multiple test systems with an account of different restrictions and AEO has given better results than different several novels, previous and hybrid optimization techniques. The outcomes confirm the robustness, expediency, effectiveness, and efficacy of AEO in terms of computational time and vicinity to the global optimum solution.
引用
收藏
页码:1034 / 1051
页数:18
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