使用無線感測網路及電動百葉窗之室內日光最佳化

Abstract

控制科技的進步不僅可以使人們的生活便利，更可以進一步協調使用者與環境的互動。近年來能源成本高漲，但使用者對於科技的需求卻沒有簡少，所以節能與智慧化的研究是相當前瞻而且有迫切須要的發展方向。本論文首創以無線感測網路監測建築室內日光分佈。硬體的內容是建置完整的日光監測平台：包含無線照度感測網路以及電動百葉窗，透過電腦及周邊監控模組與控制器，控制百葉窗的狀態以及蒐集室內日光分布的資料，其最終的目的乃是用以提升環境內使用者的需求與減少人工照明電能，以達到環境智慧化與節能。本研究平台的軟體部份是由JAVA撰寫，可執行的功能有：由電腦端設定百葉窗的放下長度及角度、顯示及儲存百葉窗的狀態及無線照度感測器的值。本論文提出一個室內日光預測與最佳化的架構，利用蒐集到的資料建立「回歸模型」，即感測器照度值對應於百葉窗狀態的映射函數，並利用回歸模型及室外的日光條件，推測出百葉窗的角度與長度狀態及日光條件所對應「室內日光分布」。最後，利用JAVA呼叫MATLAB指令以預測在使用者偏好照度下之最佳的百葉窗狀態並控制百葉窗，然後演算法藉由調整百葉窗狀態，進行回授控制室內單感測點的照度，並觀察紀錄結果，以評估日光最佳化之結果。

Control technologies could not only make the daily life convenient, but also harmonize the interaction between users and the environment. In recent years, the price of energy resources has been soaring, but the demand for energy is ever increasing. Therefore, to reduce energy consumption and make machines more intelligent is an important and prospective research direction. This thesis establishes a daylight monitoring platform to monitor and optimize indoor daylight distribution. The hardware of the daylight monitoring platform consists of wireless light sensor network and motored blinds. It controls the blinds` states through a computer, peripheral modules and controllers and collects daylight data by wireless light sensors. The software of this platform is written in JAVA. The software functions include setting, sensing and recording the blind lay-down length and the blind tilt angle, monitoring and recording the daylight data. This thesis proposes a daylight prediction and optimization configuration. It uses the collected daylight data for establishing a regression model for daylight sensor reading and the blind state. This configuration also uses outdoor daylight condition and the regression model for estimating indoor daylight response. Finally, it calls MATLAB optimization function by the JAVA program for computing the optimal blind state, and controls the blind to the optimal state. After that, the algorithm feedback controls illumination of the sensing point in the room by adjusting blinds` state. The sensor feedback control results are recorded for assessing optimization results.