Binary Bat Search Algorithm for Unit Commitment Problem in Power system

2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) Pub Date : 2017-12-01 DOI:10.1109/WIECON-ECE.2017.8468909

Nidhi, Srikanth Reddy, R. Kumar, B. K. Panigrahi

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引用次数: 5

Abstract

The unit commitment operation in power systems is a complex, non-linear, constrained optimization problem. The commitment and de-commitment decision presents a binary problem which needs discrete/binary optimization approaches. This paper presents a binary bat search algorithm (BBSA) to solve unit commitment (UC) problem. The bat search algorithm belongs to a meta heuristic class of optimization approaches inspired by natural echolocation behavior of bats. In order to solve binary UC problem, the real valued bat search process is mapped to binary search space using sigmoidal transformation function. The BBSA is then applied to test system with 10 thermal units. The effectiveness of the BBSA is verified against system dimension using test systems upto 100 units. Extensive numerical experiments are performed to test the effectiveness of BBSA and statistical analysis of simulation results are presented. The simulation results are presented, discussed and compared to various existing classical and heuristic approaches. The same demonstrate the superior performance of BBSA approach in solving UC problem.

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电力系统机组投运问题的二进制蝙蝠搜索算法

电力系统机组投入运行是一个复杂的非线性约束优化问题。承诺和取消承诺决策是一个二元问题，需要采用离散/二元优化方法。提出了一种解决机组承诺问题的二进制蝙蝠搜索算法(BBSA)。蝙蝠搜索算法是一类受蝙蝠自然回声定位行为启发的元启发式优化方法。为了解决二进制UC问题，利用s型变换函数将实值蝙蝠搜索过程映射到二进制搜索空间。然后将BBSA应用于具有10个热单元的测试系统。使用多达100个单元的测试系统来验证BBSA的有效性。通过大量的数值实验验证了该方法的有效性，并对仿真结果进行了统计分析。给出了仿真结果，并与现有的各种经典方法和启发式方法进行了讨论和比较。同样证明了BBSA方法在解决UC问题上的优越性能。

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2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)

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