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Optimal pre-cooling time: A closed form analysis

机译:最佳的预冷时间:封闭式分析

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摘要

Energy costs from Heating, Ventilation and Air Conditioning (HVAC) systems can be greater than 50% of the total operational expenditure of a commercial building. Demand side strategies such as pre-cooling and supply side strategies such as using renewable energy resources (e.g. solar panels) have the potential to reduce the operating energy costs. Several optimization frameworks have been proposed that use these strategies in an efficient manner. However, incorporating the dynamics of HVAC in an optimization framework often renders the framework computationally intractable - due to the inherent non-linearities - for large buildings. In this paper, we focus on the demand side strategy and develop a closed form expression for the optimal pre-cooling time assuming a 1R, 1C model of a building. Using simulations, we demonstrate that the optimal pre-cooling time obtained from the closed form expression matches the one from the optimization framework. Furthermore, we show that the expression - when used in conjunction with existing HVACoptimization frameworks to determine the optimal schedule of set-point temperatures - reduces the computation time of the optimization by two orders of magnitude, without loss of optimality.
机译:供暖,通风和空调(HVAC)系统产生的能源成本可能超过商业建筑总运营支出的50%。需求方策略(例如预冷)和供应方策略(例如使用可再生能源(例如,太阳能电池板))具有降低运营能源成本的潜力。已经提出了几种优化框架,它们可以有效地使用这些策略。但是,将HVAC的动力学合并到优化框架中,由于固有的非线性,通常会使该框架在计算上难以处理,因为它们具有大型建筑物的固有非线性。在本文中,我们着重于需求侧策略,并在假设建筑物为1R,1C模型的情况下针对最佳预冷时间开发了一种封闭形式的表达式。通过仿真,我们证明了从闭合形式表达式获得的最佳预冷时间与优化框架中的最优预冷却时间相匹配。此外,我们表明,当表达式与现有的HVACoptimization框架一起用于确定设定点温度的最佳计划时,可以将优化的计算时间减少两个数量级,而不会损失最优性。

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