臺灣博碩士論文加值系統

為了有效的使具有多個小型空調用戶達到節能成效，本論文提出「PMV模糊控制器」與「PMV模糊預測控制器」等控制方法，並結合美國冷凍空調協會(American Society of Heating, Refrigerating and Air-Conditioning Engineers, ASHRAE)所制定PMV(Predicted Mean Vote)為室內空間環境之舒適度指標。並依據小規模CDM(Clean Development Mechanism)計劃所提出監測計畫，以及設計出特定用戶端之專案計畫及控制策略，以證明其節能減碳之成果與效益。由於在區域內之中小型商業用戶，負載空調系統部分為多台組成，如果以人為調整空調溫度設定而進行節能控制，很難達到預期成效，且效率不高，因此，以「PMV模糊控制器」之控制方法依需節能度數與環境舒適度而進行卸載調整，但如改以「PMV模糊預測控制器」進行控制，使得用戶能有效將用電度數達到所設定之目標值，且可將室內環境舒適度控制在理想區域範圍內，進而到節能減碳之成效。

In order to make the small users save air conditioning energy more effectively, this paper proposed a design of controlling energy-saving of air-conditioning shedding. This design is based on ”PMV fuzzy controller” and “PMV Predictive Fuzzy Controller” method, and latter two used Predicted Mean Vote(PMV) as comfort level index of interior space environment which is established by ASHRAE Standard 55. To demonstrate the results of carbon reduction and efficiency, Small-scale Clean Development Mechanism(CDM) is used to present monitoring plan and design a specific client''s project plan and control strategy.
Owing to regional small and medium-sized business users, the air-conditioning load system is consisted of more than one component. It’s difficult to achieve the prospective results by adjusting air conditioning temperature individually to control the restriction of power consumption degree. Therefore, ”PMV fuzzy controller” method. Is used to adjust comfort and shedding, which is according to required energy and the environment , and "PMV prediction fuzzy controller" method is used to stabilize the environment if it’s needed. It can keep power consumption degree lower than objective value control indoor environment in an ideal and comfort range to achieve the effectiveness of carbon reduction.

摘　要 i
ABSTRACT ii
誌謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 前言 1
1.2 研究動機及目的 3
1.3 文獻探討 5
1.4 論文規劃 7
第二章 清潔發展機制(CDM) 9
2.1簡介 9
2.2基線排放量測 10
2.3排放減量設計 10
2.4排放減量驗證 11
第三章 節能管理系統 13
3.1簡介 13
3.2節能管理系統架構與規劃 15
3.2.1空調節能控制器 15
3.2.2資料處理器系統 17
3.2.3控制中心 21
3.2.3.1資料庫設計 22
3.2.3.2網頁設計 23
第四章 小型空調系統與控制技術 24
4.1簡介 24
4.2 PMV原理 25
4.3 PMV模糊控制器 27
4.4 PMV模糊預測控制器 31
4.4.1單台空調負載控制 33
4.4.2多台空調負載控制 41
第五章 驗證CDM方法學 51
5.1 簡介 51
5.2 量測方法 51
5.3 驗證方法 52
5.4 小規模CDM計劃範例 53
第六章 實驗成果與分析 55
6.1 簡介 55
6.2 模糊控制實驗 55
6.2.1 PMV模糊控制器 59
6.2.2 PMV模糊預測控制器 63
6.2.2.1單台模糊預測控制 63
6.2.2.2多台模糊預測控制 74
6.2.3節省碳排放量 101
6.2.4實驗總結 102
第七章結論 103
7.1結論 103
7.2未來展望 104
參考文獻 106

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