摘要(英) |
Power investment in Taiwan is increasingly difficult, it is a crucial issue to forecast precise electricity consumption and to avoid the waste of construction of power and electricity generation. In this thesis, time series analysis methods were applied to discuss the power consumption of the influencing factors in both residence and small stores in every urban area in Taiwan. OLS model was established by using lighting sales data from January 2007 to December 2012. Also the stationary of time series data and serial correlation were considered to correct the OLS model. Finally, we compare the power consumption of the influencing factors and relationships and significant, to discuss the impact of various factors on the electricity consumption effect.
The conclusion of this thesis shows that the increase of population is minor to electricity consumption. The main factor affecting the power consumption is temperature. Among four regional, average temperature rise 1 ℃ average monthly increase of about 3.5 degrees lighting electricity, and the largest increase is in Taipei. Three tariff adjustments in the last six years seems to be little effect. The effect of summer tariff between June and September is not obvious as well. Finally, the thesis recommends to suppress power consumption, can be increased by increasing tariffs or class energy tax, but also to increase the area for the summer tariffs and price discrimination according to user fees and environmental dimension carbon reduction. |
參考文獻 |
一、中文文獻
〔1〕台灣電力公司,「統計手冊」,民國96~101年。
〔2〕台灣電力公司,「長期負載預測報告(101年至115年)」,民國101年2月。
〔3〕王仁俊、陳建富、張翊峰、鄭偉志、鄭雪君、柯仲謙,「台灣三大都會區住商街廓用電密度之研究」,行政院國家科學委員會專題研究計畫,2008.10。
〔4〕王京明,「臺灣地區住宅與商業部門能源消費調查與研究」,中華經濟研究院,1995.6。
〔5〕吳家銓,「台灣家庭夏天用電需求分析」,中央大學,碩士論文,民國98年。
〔6〕林憲德、趙又嬋、遊雅婷,「公寓大廈住宅公共用電解析」,建築學報,67期,169-180頁,2009.03。
〔7〕林憲德、王仁俊、沈如龍、陳建富、邱清泉,「台南市住宅區街廓透天住宅用電解析」,都市與計劃,31卷3期(TSSCI),2004。
〔8〕郭柏巖,「住宅耗電實測解析與評估系統之研究」,成功大學,博士論文,民國94年。
〔9〕黃漢泉、蘇俊源,「台中市旅館建築電力消費量之研究」,建築學報,37期,21-34頁,2001.6。
〔10〕賈繼德,「台灣電力需求預測模型之探討—ARIMA模型及迴歸模型」,東吳大學,碩士論文,民國98年。
〔11〕應立志、潘美秋,「 迴歸分析與灰色理論在尖峰負載預測能力之比較 」,僑光學報,23 期,27-41頁,2004.06 。
〔12〕楊奕農,「時間序列分析 經濟與財務上之應用」,雙葉書廊。
二、外文文獻
〔1〕Beenstock, M., E. Goldin and D. Nabot (1999), “the Demand for Electricity in Isreal” Energy Economics,Vol 21 ,168-183,1999.4.
〔2〕Cottrell,A. and J. Riccardo,” Gretl User’s Guide”, Allin Cottrell Department of Economics Wake Forest University, 2013.
〔3〕Ghosh, S, “Univariate Time-Series Forecasting of Monthly Peak Demand of Electricity in Northern India”, International Journal of Indian Culture and Business Management, Vol 1,466-474, 2008.4.
〔4〕Kamwerschen, D.R.and D.V. Porter (2004), ”The Demand for Residential, Industrial and Total Electricity, 1973-1998”,Energy Economics,Vol 26, 87-100, 2004.1.
〔5〕M.Y.Cho,J.C.Hwang and C.S.Chen,(1995),”Customer short term load forecasting by ARIMA transfer function model,”Energy management and power delivery,Proceeding of EMPD’95 international conference on,Vol 1,317-322, 1995.11.
〔6〕Filippini,M.(2011),” Short and long-run time-of-useprice elasticities in Swiss residential electricity demand”, Energy Policy,Vol 39, 5811-5817, 2011.10
〔7〕Smith,M.(2000),”Modeling And Short-Term Forecasting Of New South Wales Electricity System Load”,Journal of Business and Economic Statistics,Vol.18, 465-478, 2000.4.
〔8〕Wooldridge, J. M. “ Introductory Econometrics: A Modern Approach, 4th Edition”,South-Western Cengage Learning.
〔9〕Zachariadis, T.and N. Pashourtidou, (2007),”An Empirical Analysis of Electricity Consumption in Cyprus,” Energy Economics, Vol 29 ,183-198, 2007.3.
三、網站資料
〔1〕中央氣象局氣候統計每月氣象,http://www.cwb.gov.tw/V7/climate/monthlyData/mD.htm。
〔2〕台灣電力公司資訊揭露電價專區,每月住宅及小商店實際用電情形,http://info.taipower.com.tw/info53/main/main6.html。
〔3〕內政部統計處統計月報,各鄉鎮市區人口,http://sowf.moi.gov.tw/stat/month/list.htm。 |