人類廣泛使用化石燃料導致全球暖化與氣候變遷問題日益嚴重，為了應對上述問題，國際社會提出了2050淨零排放的目標，其中臺灣也積極制定了2050淨零排放策略。住宅部門的電力消耗在總電力消耗中占比較大，尤其是照明和空調系統的能耗更是如此。因此，本文旨在研發一個智慧節能之室內用電調控系統，以照明和空調為主要控制目標，同時達到室內照度和舒適度的要求，並將能源消耗降至最低，所提方法有助於實現淨零生活的目標。該系統結合日光響應調光系統(Daylight responsive dimming system, DRDS)和天氣資料，利用最佳化演算法控制燈具的亮度以及電致變色玻璃的透光度，提供舒適且節能的室內環境。
本文提出一套結合粒子群演算法(Particle Swarm Optimization, PSO)之智慧節能室內用電調控系統。實際以照度計量測場域內燈具與日光對各照度點之影響，進而達成室內目標照度最佳化，實測結果顯示照度誤差皆小於5 %。本文使用PSO演算法計算出最佳調光命令，並結合天氣條件計算出電致變色玻璃電壓命令，使室內達到設定之照度及舒適度目標。本文針對三種不同測試情境進行模擬，結果顯示所提系統不但可達成照度及舒適度目標，且最多可減少空調能耗36.87 W，降低燈具能耗高達51 %，達到提高能源效益及環境可持續性之雙重目標。

Human reliance on fossil fuels has led to the increasingly severe issues of global warming and climate change. To address these problems, the international community has set a goal of achieving net-zero emissions by 2050, and Taiwan has actively formulated its own 2050 net-zero emissions strategy. The residential sector accounts for a significant portion of power consumption, particularly in lighting and air conditioning systems. Therefore, this study aims to develop an intelligent energy-saving indoor electrical control system that focuses on lighting and air conditioning, while meeting indoor illumination and comfort requirements and minimizing energy consumption. The proposed system combines a daylight-responsive dimming system (DRDS) with weather data and utilizes an optimization algorithm to control the brightness of lighting fixtures and the transmittance of electrochromic glass, providing a comfortable and energy-efficient indoor environment.
This thesis proposes an intelligent energy-saving indoor electrical control system that incorporates a particle swarm optimization (PSO) algorithm. The dimming levels and the influence of daylight at various points are measured using illuminance meters to achieve optimal indoor illumination. The experimental results show that the illuminance error is less than 5 %. The PSO algorithm is used to calculate the optimal dimming commands, and the voltage commands for electrochromic glass are determined based on weather conditions, thereby achieving the desired indoor illumination and comfort goals. The proposed system is simulated under three different test scenarios, and the results demonstrate that it not only achieves the illumination and comfort objectives but also reduces air conditioning energy consumption by up to 36.87 W and lighting fixture energy consumption by as much as 51 %. Thus, it accomplishes the dual goals of improving energy efficiency and environmental sustainability.

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