Abstract Improper operation of a multi-chiller plant would significantly increase associated electric consumption. This paper introduces a new model to determine the optimal loading point of the chillers. To do so, optimal dispatching of multi-chiller plant is expressed as an optimization problem and associated constraints are all together accommodated in the process of optimization. The problem is tackled by a new version of a metaheuristics approach. The proposed approach is entitled as augmented group search optimization (AGSO) algorithm, which is devised to avoid drawbacks of conventional group search optimization algorithm such as trapping in the local minima. The effectiveness and robustness of the proposed approach in comparison with available methods are studied through three well-known test cases. Numerical results demonstrate that AGSO with its strong exploration capability achieves a lower energy consumption than that of recently published methods with higher convergence speed.

中文翻译：

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多机组冷负荷优化调度的增强群搜索优化算法

摘要 多冷水机组运行不当会显着增加相关的电力消耗。本文介绍了一种确定冷水机组最佳负载点的新模型。为此，多冷水机组的优化调度被表示为一个优化问题，并且在优化过程中将相关的约束条件一起考虑在内。新版本的元启发式方法解决了这个问题。所提出的方法被称为增强群搜索优化 (AGSO) 算法，该算法旨在避免传统群搜索优化算法的缺点，例如陷入局部最小值。通过三个众所周知的测试案例研究了所提出的方法与可用方法相比的有效性和鲁棒性。