研究生: |
郭千瑜 |
---|---|
論文名稱: |
智慧電網中以戶為單位之用電特徵分析 An Analysis of Household Electricity Meter Data in Smart Grid Systems |
指導教授: | 陳伶志 |
學位類別: |
碩士 Master |
系所名稱: |
資訊工程學系 Department of Computer Science and Information Engineering |
論文出版年: | 2013 |
畢業學年度: | 101 |
語文別: | 中文 |
論文頁數: | 63 |
中文關鍵詞: | 智慧型電表 、資料分析 、回看法 、支持向量回歸 、分群演算法 |
英文關鍵詞: | Smart Meter Data, Data Analysis, ε-LookBack-N, Support Vector Regression, Clustering |
論文種類: | 學術論文 |
相關次數: | 點閱:260 下載:18 |
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智慧電網及智慧型電表建置在全球快速發展,在台灣已有特定地區裝設智慧型電網,透過智慧型電表蒐集用戶電表量測資料。消費者的用電習慣各有不同,而影響消費者的用電習慣有許多因素,本研究將會針對溫度、樓層等因素作用電量分析,使消費者不但可以瞭解自身的用電習慣,並加以調整,以減少電費支出,還可節省電能消耗。除了電量分析外,預測用電量也可幫助電力業者適時調整發電量,改善浪費電力能源之現象。本研究使用三種用電預測方法,分別為回看法(ε-LookBack-N)、差分整合自回歸移動平均模型(Autoregressive Integrated Moving Average Model)和支持向量回歸(Support Vector Regression),我們將評估其適用性與準確度,並透過用電戶的用電特徵分群,進一步結合環境變因,研究用電戶用電度數的預測模型,並利用既有量測資料進行驗證。其預測模型可以幫助電力業者作用電預測,適時調整發電量,有效率的配送電能,以達到節能省碳之目的。
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