臺灣能源期刊發行
- 創刊日期:
102年11月30日
- 發行所:
經濟部能源署
- 發行人:
游振偉
- 地址:
台北市復興北路2號13樓
- 電話:
02-2772-1370
- 執行單位:
財團法人工業技術研究院
- 地址:
新竹縣竹東鎮中興路四段195號26館
- 服務專線:
03-5916006
- 服務信箱:
- 總編輯:
王漢英胡均立
- 顧問:
王運銘童遷祥王人謙
- 執行主編:
劉子衙陳志臣
- 編輯委員:
方良吉王錫福朱家齊李堅明李叢禎林師模馬鴻文陳希立廖芳玲廖肇寧劉文獻蕭志同顧洋(依筆畫順序排列)
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臺灣能源期刊論文全文
臺灣能源期刊第5卷第4期內容
出刊日期:December, 2018
- 題目
- 我國住宅部門電力消費關鍵影響因素分析
- Title
- Determinants of Electricity Consumption in Taiwan’s Residential Sector - A Decomposition Analysis
- 作者
- 黃韻勳
- Authors
- Yun-Hsun Huang
- 摘要
- 建築部門為全球最大的最終能源使用部門,而住宅部門約占全球建築部門能源耗用的75%,顯示若欲控制增溫在2度C內,須減緩住宅部門能源需求之成長。以臺灣而言,2017年住宅部門之電力消費為476.12億度,占全國總電力消費量的18.21%;此外,住宅部門為近五年來用電成長率最高的主要部門。為有效降低住宅部門電力消費,有必要確認出影響住宅部門電力消費的關鍵因素,以進一步釐清各項因素對電力消費量之影響程度。本文以歐盟ODYSSEE-MURE (Mesures d’Utilisation Rationnelle de I’Energie)的分解架構為基礎,並進一步結合對數平均數迪式指數分解法,建構我國住宅部門因素分解模式。此模式將我國住宅部門電力消費量之變動因素拆解出氣候效果、戶數變化效果、家電設備擁有效果、家電設備使用時間效果、節能效果、家戶面積變化效果等更多元之因素,分析2014~2017年間我國住宅部門電力消費變化量,藉以了解各項效果對電力消費量之影響程度。最後依據模式分析結果提出三點政策建議,以供住宅部門未來研擬節能政策之參考。
- 關鍵字
- 住宅部門,電力消費,因素分解,對數平均數迪式指數分解法
- Abatract
- The building sector is the biggest final energy user globally, and the residential sector absorbs most of the energy consumption of the building sector (around 75 percent). The residential sector has a consuderable role to keep global temperature within 2°C. In terms of Taiwan, the electricity consumption of the residential sector in 2017 was 47.612 billion kWh, accounting for 18.21% of total electricity consumption. In addition, the residential sector has the highest growth rate of electricity use in the past five years (2013~ 2017). It is therefore essential to understand the driving forces behind the changes in residential electricity consumption in Taiwan. Based on the decomposition structure of the energy consumption for households of EU ODYSSEE-MURE, this paper further combines Logarithmic Mean Divisia Index (LMDI) to formulate our decompostion analysis model. The model is then used to explore the impacts of six factors on electricity consumption from residential sector in Taiwan during 2014-2017. Electricity consumption can be decomposed into climatic effect, household effect, more appliances effect, usage time effect, energy savings effect and larger homes effect. Finally, three policy implications are proposed on the basis of our decomposition analysis results.
- Keywords
- Residential sector, Electricity consumption, Decomposition analysis, Logarithmic Mean Divisia Index