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首页> 外文期刊>Applied thermal engineering: Design, processes, equipment, economics >Economic dispatch of chiller plant by improved ripple bee swarm optimization algorithm for saving energy
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Economic dispatch of chiller plant by improved ripple bee swarm optimization algorithm for saving energy

机译:改进的波纹蜂群优化算法在冷水机组经济调度中的应用

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This paper presents an improved ripple bee swarm optimization (IRBSO) algorithm to solve the problem of the economic dispatch of chiller plants (EDCP). Using the characteristics of biological communities, different movement models are adopted to search within the feasible solution space. This paper uses nonlinear ripple weight factors and self-adaption repulsion factor to improve the BSO and proposes the influence of parameters on the IRBSO method to more effectively search the feasible space. For all bee swarms, the efficiency of searching movement in the solution space improves, and the capacity of information discovery and mining increases. This paper utilizes the test cases to verify the proposed IRBSO, including EDCP problems for a single day and a single week. Compared with other methods, the results of the proposed IRBSO exhibit higher accuracy and stability, making it suitable for the operation planning of multiple chiller systems. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种改进的波纹蜂群优化算法(IRBSO),以解决冷水机组经济调度(EDCP)的问题。利用生物群落的特征,在可行解空间内采用不同的运动模型进行搜索。本文利用非线性纹波权重因子和自适应斥力因子来改进BSO,并提出了参数对IRBSO方法的影响,以更有效地搜索可行空间。对于所有蜂群,在解决方案空间中搜索运动的效率都得到了提高,信息发现和挖掘的能力也得到了提高。本文利用测试案例来验证提议的IRBSO,包括一天和一周内的EDCP问题。与其他方法相比,所提出的IRBSO的结果显示出更高的准确性和稳定性,使其适合于多台冷却器系统的运行计划。 (C)2016 Elsevier Ltd.保留所有权利。

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