The state-of-the-art energy management for the heating, ventilation and air conditioning (HVAC) system uses a static clothing model that calculates the occupant’s clothing insulation as a fixed value based on outdoor air temperature measured at a particular time of the day. However, the static clothing model can hardly capture the occupant’s intra-day clothing behaviors, leading to inaccurate thermal comfort assessment and unrealistic HVAC energy management. This paper proposes a novel HVAC energy management scheme to optimally schedule the thermostat setpoints of HVAC and to provide recommendations on occupants’ optimal hourly clothing decisions through a predicted mean vote model, while considering uncertainties in the outside temperature. The proposed HVAC energy management scheme is solved by applying an approximate dynamic programming approach. Further, a model predictive control framework with a long short-term memory based forecaster is developed for more realistic simulations. We study the HVAC schedules in a residential home with summer and winter time of use electricity tariffs for both male and female occupants. Compared with non-optimized cases, proof-of-concept simulation results demonstrate that the proposed scheme can achieve a 53.8% and a 29.8% cost saving in a summer-male scenario and a winter-female scenario, respectively.

供暖，通风和空调（HVAC）系统的最新能源管理使用静态服装模型，该模型根据一天中特定时间测量的室外空气温度将乘员的服装隔热度计算为固定值。但是，静态服装模型几乎无法捕获乘员的日间服装行为，从而导致不正确的热舒适性评估和不切实际的HVAC能源管理。本文提出了一种新颖的HVAC能源管理方案，以优化调度HVAC的恒温器设定点，并通过预测的平均投票模型，同时考虑外部温度的不确定性，为居住者的最佳每小时服装决策提供建议。拟议的HVAC能源管理方案通过应用近似动态规划方法得以解决。此外，具有更长的基于短期记忆的预测器的模型预测控制框架被开发用于更现实的仿真。我们研究了带有夏季和冬季使用时间的男女用电费的住宅房屋中的HVAC时间表。与未优化的情况相比，概念验证的仿真结果表明，该方案在夏季男性和冬季女性的情况下分别可以节省53.8％和29.8％的成本。我们研究了带有夏季和冬季使用时间的男女用电费的住宅房屋中的HVAC时间表。与未优化的情况相比，概念验证的仿真结果表明，该方案在夏季男性和冬季女性的情况下分别可以节省53.8％和29.8％的成本。我们研究了带有夏季和冬季使用时间的男女用电费的住宅房屋中的HVAC时间表。与未优化的情况相比，概念验证的仿真结果表明，该方案在夏季男性和冬季女性的情况下分别可以节省53.8％和29.8％的成本。