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A supervisory control strategy for building cooling water systems for practical and real time applications

机译:用于实际和实时应用的建筑冷却水系统的监督控制策略

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This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.
机译:本文提出了一种基于模型的监督控制策略,用于在线控制建筑中央冷却水系统以提高其能源效率。监督控制策略在考虑到中央冷却水系统的特性和相互作用以及实际应用的要求和约束的基础上,寻求最小的能量输入以为建筑物提供足够的冷却能量。简化的半物理冷却器和冷却塔模型用于预测系统的能源性能和环境质量,以及系统对控制设置更改的响应。开发了一种混合优化技术,即基于PMES(性能图和穷举搜索)的方法,并利用它来寻求优化问题的最佳解决方案。通过与遗传算法(GA)作为优化工具的基于模型的监督控制策略进行比较,评估了基于模型的监督控制策略在高层商业办公楼的中央冷却水系统上的控制性能和能源性能。 ,以及基于性能图的接近最优控制策略以及冷却水系统的其他常规控制策略,无论是从能效,控制精度,计算成本等方面,结果都表明该策略比其他方法更具能源效率和计算成本效益在线实际应用的方法。

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