臺灣博碩士論文加值系統

現今時常在工廠與商辦等區域針對空調設備裝設數位電表來記錄能源的使用情形、環境因素感測器紀錄室內環境參數。在這些大量數據的情況下，以往的能源分析辦法僅能計算出理論效率，無法明確給予有效建議；本篇論文嘗試將雲端平台與資料包絡線分析(Development of Data Envelopment Analysis ,DEA)作結合，使用中華電信iEN於雲端節能平台所收錄之能源數據來進行資料包絡線分析的數學模型開發，我們針對能源與環境參數去進行效率評估，期望以較低的空調耗電量能產生較低室內溫度及室內溼度、較高室外溫度及室外濕度。經由Python程式語言及DEA等軟體工具進行數據處理，利用Python程式語言抓取氣象局室外環境參數(室外溫度、室外濕度)；利用DEA分別對空調耗電量與室內溫度、室內溼度、室外溫度、室外濕度進行分析，進而產生資料包絡線圖、效率前緣點與效率後緣點。
資料包絡線圖可得知室內溫度、室內溼度、室外溫度、室外濕度之資料點集中區間及技術效率高之區間，這個步驟可讓使用者大略知道能源的使用流向及技術效率高低概略情況。我們利用效率前緣點與效率後緣點與環境參數繪畫數據三維散佈圖，最後使用本研究開發之DEA視角轉換法我們可得知空調系統之最大耗電因素為那些環境因素造成，可明確告知使用者如何進行改善，進而得到最大節能效益。

Nowadays, digital meters are installed in factories and commercial offices to record the use of energy, and environmental factor sensors record indoor environmental parameters. Under these circumstances which are large amounts of data, past energy analysis methods can only calculate theoretical efficiency and cannot clearly give effective recommendations. In this paper, a mathematical model is developed for development of Data Envelopment Analysis using the energy data collected by the Chunghwa Telecom iEN, we make efficiency assessments based on energy and environmental parameters, desiring lower indoor air temperature and indoor humidity, higher outdoor temperature and outdoor humidity with lower air-conditioning power consumption；Software tools such as Python programming language and development of Data Envelopment Analysis for data processing, Using the Python programming language to capture the outdoor environment parameters of the Taiwan Central Weather Bureau (outdoor temperature, outdoor humidity)；Analysis of air-conditioning power consumption and indoor temperature, indoor humidity, outdoor temperature, and outdoor humidity using Data Envelope Analysis, producing data envelope diagram、efficiency front and efficiency trailing points.
Data envelope diagram can be used to find the data point concentration range and technical efficiency range of indoor temperature, indoor humidity, outdoor temperature, and outdoor humidity. This step allows the user to know circumstances of the direction of energy use and the level of technical efficiency. We use three-dimensional scatter plots of the efficiency front edge and efficiency trailing points and environmental parameters. Finally, using the DEA perspective conversion method developed by this research, we can know that the largest power consumption factor of the air conditioning system is caused by those environmental factors. Users can be clearly informed how to make improvements, and then get the maximum energy efficiency.

摘要i
ABSTRACTii
致謝iv
目錄v
表目錄vii
圖目錄viii
第一章 導論- 1 -
1.1前言- 1 -
1.2研究背景與動機- 3 -
1.3文獻回顧- 6 -
1.4研究目的- 10 -
第二章 研究方法與理論- 11 -
2.1能源管理系統- 11 -
2.2雲端運算技術- 12 -
2.2.1雲端運算的型態- 13 -
2.2.2雲端運算模型- 14 -
2.3程式語言- 15 -
2.3.1 R程式語言- 16 -
2.3.2 Python程式語言- 17 -
2.3.3 資料庫管理系統- 17 -
2.4數據分析- 20 -
2.4.1效率評估方法- 20 -
2.4.2資料包絡分析法- 22 -
第三章 實驗方法與步驟- 23 -
3.1案場現況- 23 -
3.1.1案場施工概述- 24 -
3.1.2雲端能源管理系統- 28 -
3.2實驗系統架構- 29 -
3.2.1系統背景- 29 -
3.2.2系統架構- 29 -
3.3實驗流程分析- 30 -
3.4資料前處理- 31 -
3.4.1擷取用電數據- 32 -
3.4.2 網路抓取外在環境因素- 33 -
3.4.3用電數據修正- 34 -
3.5資料包絡線分析- 35 -
3.5.1 資料包絡線分析輸入與輸出之選取- 35 -
3.5.2 程式撰寫與數據分析- 37 -
第四章 實驗結果與討論- 41 -
4.1能源數據與空調設定溫度之對比- 41 -
4.2空調用電分析- 43 -
4.2.1資料包絡線分析- 43 -
4.2.2技術效率分析- 45 -
第五章 結論與建議- 55 -
5.1結論- 55 -
5.2未來展望- 56 -
參考文獻- 57 -

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