基於多目標粒子群演算法之辦公室智能照明系統｜國立臺灣科技大學博碩士論文系統

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研究生：	陳毅峰 Yi-Feng Chen
論文名稱：	基於多目標粒子群演算法之辦公室智能照明系統 Intelligent Lighting System for Offices Based on Multi-objective Particle Swarm Optimization
指導教授：	劉益華 Yi-Hua Liu
口試委員:	羅一峰 Yi-Feng Luo 鄧人豪 Ren-Hao Deng 王順忠 Shun-Chung Wang
學位類別：	碩士 Master
系所名稱：	電資學院 - 電機工程系 Department of Electrical Engineering
論文出版年：	2023
畢業學年度：	111
語文別：	中文
論文頁數：	63
中文關鍵詞：	日光響應調光系統、室內照明、Zigbee 、IoT 、多目標演算法
外文關鍵詞：	Daylight response dimming system, Indoor lighting, particle swarm optimization, Zigbee, IoT, particle swarm optimization
相關次數：	點閱：366 下載：7
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室內照明系統是結合自然光源和人造光源，在特定空間內進行全面規劃之方法，其目標在於創造理想的情境，同時兼顧節能與最佳效能。隨著 LED 燈具成為主流照明選擇以及物聯網技術的普及，照明設計領域一直在持續發展。此外搭配日光響應調光系統(Daylight Responsive Dimming Systems, DRDS)更能讓整體照明節能比提升。
本研究旨為開發一種同時考慮燈具消耗與環境光源因素的自動調光系統，其為一基於多目標演算法之室內最佳化自動調光系統。該系統考慮燈具消耗功率和環境光源因素，並利用照度計進行實時測量與調節。而本系統主要使用速度約束多目標粒子群演算法(SpeedConstrained Multi-objective Particle Swarm Optimization, SMPSO)作為本文主要演算法架構，並且將其與傳統日光響應調光系統與僅考慮照度需求之單目標粒子群演算法(Particle Swarm Optimization, PSO)進行比較。透過實驗，本文驗證了速度約束多目標粒子群演算法能夠有效地找到最佳的照明設定，其可達到使用者所需的照度，同時兼顧照明效果和能源效率。本研究主要貢獻在於實現一種兼顧高效能、低功耗的室內自動調光系統。

Indoor lighting systems involve the integration of natural and artificial
light sources within a specific space, aiming to create an ideal environment
while ensuring energy efficiency and optimal performance. With LED
lighting becoming the mainstream choice and the widespread adoption of
internet of things (IoT) technologies, the field of lighting design has been
continuously evolving. Moreover, integrating daylight responsive
dimming systems (DRDS) with lighting design can further enhance overall
energy savings.
This study aims to develop an automatic dimming system that
simultaneously considers fixture consumption and environmental light
sources. The proposed system is based on a multi-objective algorithm for
indoor lighting optimization. It takes into account fixture power
consumption and environmental light sources, utilizing light sensors for
real-time measurement. The primary algorithm framework employed in
this system is the speed-constrained multi-objective particle swarm
optimization (SMPSO), which is compared with traditional DRDS
dimming systems and single-objective particle swarm optimization (PSO)
that considers only illumination requirements. Through experiments, the
study verifies that the SMPSO algorithm effectively identifies the optimal
dimming commands that meet user-defined illumination requirements while
considering both lighting effects and energy efficiency. The main
contribution of this research lies in the realization of an indoor automatic
dimming system that achieves high performance and low power
consumption.

目錄
摘要...................................................................................................................... i
Abstract ............................................................................................................... ii
致謝....................................................................................................................iii
圖目錄................................................................................................................ vi
表目錄..............................................................................................................viii
第一章 緒論 ................................................................................................... 1
1.1 研究動機與目的.................................................................................. 2
1.2 文獻回顧.............................................................................................. 5
1.3 論文架構.............................................................................................. 5
第二章 調光系統架構 ................................................................................... 6
2.1 系統硬體架構...................................................................................... 6
2.1.1 照度數據蒐集架構........................................................................ 8
2.1.2 照度感測器介紹............................................................................ 9
2.1.3 照度感測器介紹.......................................................................... 10
2.2 運算核心介紹.................................................................................... 10
2.3 點燈系統硬體架構介紹.................................................................... 11
2.3.1 燈具介紹...................................................................................... 12
2.3.2 閘道器介紹.................................................................................. 13
2.3.3 燈具控制指令.............................................................................. 13
2.3.4 燈具控制指令.............................................................................. 13
第三章 多目標最佳化演算法介紹 ............................................................. 15
3.1 SMPSO 演算法說明.......................................................................... 15
3.1.1 速度更新與位置更新.................................................................. 16
3.1.2 變異.............................................................................................. 18
3.2 SMPSO 演算法應用.......................................................................... 19
v
第四章 實驗方法與結果 ............................................................................. 22
4.1 實驗設計............................................................................................ 22
4.1.1 目標函數定義.............................................................................. 23
4.1.2 實際運算...................................................................................... 28
4.2 實驗結果............................................................................................ 33
4.2.1 照度準確率.................................................................................. 34
4.2.2 模擬照度數值與能源節省之比較.............................................. 36
第五章 結論與未來展望 ............................................................................. 49
5.1 結論.................................................................................................... 49
5.2 未來展望............................................................................................ 49
參考文獻........................................................................................................... 51

                                

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