Existing pre-cooling strategies provide a means of shifting or reducing the peak demand and/or energy cost in residential buildings. However, majority of them are rule-based and therefore may not be optimal in terms of cost saving, leaving room for improvement. In this paper, an integer linear programming problem that accounts for the thermal properties of a specific home, HVAC system capacity, utility rate structure, and weather conditions and makes use of a home thermal model is formulated. This problem determines the HVAC on/off control signal that minimizes the 24-hour energy cost while maintaining thermal comfort and calculates the corresponding optimal indoor air temperature. The model is constructed using home thermal properties identified via data training in real-time. Through simulation, the energy performance of the proposed optimal pre-cooling strategy is investigated and compared with three rule-based operation strategies from the literature. It is found that the optimal strategy requires the least energy consumption without sacrificing thermal comfort. The superb energy performance of the optimal strategy is attributed to a longer runtime of the HVAC system in cool outdoor air conditions and to the elimination of deadband in HVAC operation, which is required by the rule-based strategies, to allow the indoor air temperature to stay near the thermal comfort upper bound as much as possible. In terms of energy cost, the rule-based operation strategies require $3.52, $1.90, and $2.79, respectively, while the optimal strategy only requires $1.52. These figures represent a saving of 56.82%, 20.00%, and 45.52%, respectively. The results suggest that the optimal strategy is indeed significantly more effective than the existing rule-based operation strategies.

现有的预冷策略提供了一种改变或减少住宅建筑中的高峰需求和/或能源成本的方法。但是，它们中的大多数都是基于规则的，因此在节省成本方面可能不是最佳的，因此还有改进的余地。在本文中，提出了一个整数线性规划问题，该问题考虑了特定房屋的热属性，HVAC系统容量，实用率结构和天气状况，并利用了房屋的热模型。此问题确定了HVAC开/关控制信号，该信号在保持热舒适性的同时将24小时能源成本降至最低，并计算出相应的最佳室内空气温度。该模型使用通过实时数据训练确定的家庭热属性来构建。通过模拟，研究了提出的最佳预冷策略的能量性能，并与文献中的三种基于规则的运行策略进行了比较。发现最佳策略需要最少的能量消耗而不牺牲热舒适性。最佳策略的出色能源性能归因于HVAC系统在凉爽的室外空气条件下运行时间更长，以及消除了HVAC运行中的死区，这是基于规则的策略所必需的，以允许室内空气温度达到尽可能保持在热舒适性上限附近。就能源成本而言，基于规则的运营策略分别需要3.52美元，1.90美元和2.79美元，而最优策略仅需要1.52美元。这些数字分别代表节省56.82％，20.00％和45.52％。