本論文提出透過設定溫度的控制來達成在暖通空調上有效的能源消耗管理，其中我們還有考慮到室內熱動態模型和使用者滿意度模型。首先，在數據收集方面上，我們有在實驗室中設置好電度錶來收集每個時間區間暖通空調的能源消耗資料，並且設計了線上問卷表與定期發送此問卷表以收集使用者在滿意度上的回饋資料，接著我們將收集到的數據做分析，我們使用線性回歸的方式來建構出室內溫度和暖通空調能耗在時間上的變化模型，而邏輯回歸這方法是被我們用來建成使用者滿意度的模型。我們提出一個策略可以在未來L時間區間內達到最小化暖通空調能耗加上正規化使用者不滿意度的設定溫度控制，最後，在我們提出的方法其結果中可以明顯顯示出優於其他策略像是都固定設定溫度的方法。

This thesis addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems through set-point temperature control, taking into consideration both the indoor thermodynamic model and user satisfaction. In terms of data collection, power meters are setup in the lab to gather the HVAC energy consumption in each time slot, and an online form is designed and sent out regularly to gather user feedback regarding their satisfaction. In terms of data analysis, linear regression is used to model temporal variations in both indoor temperature and HVAC energy consumption, whereas logistic regression is used to model user satisfaction. The proposed set-point temperature control is determined by minimizing the HVAC energy consumption in the future $L$ time slots plus a regularization on the user dissatisfaction. Our proposed scheme is shown to significantly outperform the default strategy where the set-point temperature is often fixed over time.

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