Teaching-learning-based optimization algorithm for multi-area economic dispatch

被引:91
作者
Basu, M. [1 ]
机构
[1] Jadavpur Univ, Dept Power Engn, Kolkata 700098, India
关键词
Multi-area economic dispatch; Tie line constraints; Teaching-learning-based optimization; TIE-LINE CONSTRAINTS; TRANSMISSION CAPACITY CONSTRAINTS; PARTICLE SWARM OPTIMIZATION; PRACTICAL APPROACH; GENETIC ALGORITHM; UNIT COMMITMENT; SYSTEMS; SEARCH;
D O I
10.1016/j.energy.2014.02.064
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents teaching learning-based optimization algorithm for solving MAED (multi-area economic dispatch) problem with tie line constraints considering transmission losses, multiple fuels, valve-point loading and prohibited operating zones. TLBO (teaching learning-based optimization) is one of the recently proposed population based algorithms which simulates the teaching learning process of the class room. It is a very simple and robust global optimization technique. The effectiveness of the proposed algorithm has been verified on three different test systems, both small and large, involving varying degree of complexity. Compared with differential evolution, evolutionary programming and real coded genetic algorithm, considering the quality of the solution obtained, the proposed algorithm seems to be a promising alternative approach for solving the MAED problems in practical power system. (c) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:21 / 28
页数:8
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