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Solution quality improvement in chiller loading optimization.

Author(s) : GEEM Z. W.

Type of article: Article

Summary

In order to reduce greenhouse gas emission, we can energy-efficiently operate a multiple chiller system using optimization techniques. So far, various optimization techniques have been proposed to the optimal chiller loading problem. Most of those techniques are meta-heuristic algorithms such as genetic algorithm, simulated annealing, and particle swarm optimization. However, this study applied a gradient-based method, named generalized reduced gradient, and then obtains better results when compared with other approaches. When two additional approaches (hybridization between metaheuristic algorithm and gradient-based algorithm; and reformulation of optimization structure by adding a binary variable which denotes chiller’s operating status) were introduced, generalized reduced gradient found even better solutions. [Reprinted with permission from Elsevier. Copyright, 2011].

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