氣候因素、所得和人口特徵對電力需求之影響-台北市為例;Climate factors, Income and Demographic causes of electricity demand in Taipei City

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题名:	氣候因素、所得和人口特徵對電力需求之影響-台北市為例;Climate factors, Income and Demographic causes of electricity demand in Taipei City
作者:	林子婷;Lin, Tzu-Ting
贡献者:	產業經濟研究所
关键词:	電力需求;縱橫資料;固定效果模型;Electricity Demand;Panel Data;Fixed effect model
日期:	2017-07-10
上传时间:	2017-10-27 13:58:28 (UTC+8)
出版者:	國立中央大學
摘要:	日新月異的時代，能源的供需問題一直是我們需要關注，電力對民眾來說是不可或缺的，也是經濟發展的動力，因此本研究加入地理資訊系統(QGIS)測量氣候因素、所得和人口特徵變數對住宅用電量作探討。研究範圍為2014年至2016年夏季(6、7、8、9月)台北市村里的縱橫資料(Panel Data)，使用最小平方法(Ordinary Least Squares)及固定效果模型(Fixed effect model)進行分析。研究結果顯示：(1)熱天日數是主要影響台北市村里用電量因素。(2)以平均每戶每月所得固定效果之實證模型中來探討所得為顯著負向影響。(3)當解釋變數加入人口特徵變數探討時，每人每月平均所得條件下，人口密度為負向不顯著，而每戶每月平均所得條件下，人口密度為負向顯著，表示有規模經濟，而所得為每戶每月平均所得解釋能力比每人每月平均所得解釋能力好。(4)村里戶數為顯著正向影響，表示台北市住宅結構改變，以單身居住者居多。(5)人口特徵變數中65歲以上中老年人顯著正向影響用電量。 ;With the progress of the times, we need to focus on energy supply and demand problem. Electricity is indispensable of modern life, but also promotes economic development. As a result, use geographic information systems (QGIS) to measure climate factors, income and demographic variables on residential electricity consumption as an investigation. For this purpose, we use Ordinary Least Squares and Fixed effect model to estimate demand equation with this analysis of panel data of village during the period 2014-2016 in Taipei City. The empirical results show that：(1)The Heating Degree Days is significantly related to electricity consumption in Taipei City.(2) Average monthly income per household in the empirical model of fixed effects results for income is a significantly negative impact.(3)When joins the demographic characteristic variable, under the condition of average monthly income per person, population density is negative and insignificant. While the average monthly income per household conditions, population density is negative and significant, indicating the economies of scale. (4) The positive and significant influence on the number of household indicates the changes of residential structure-mostly live singles (5) Elderly above 65 years old is positively and significantly related to electricity consumption.
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