Popyt na energię elektryczną w regionie Wielkopolski

• Autorzy: Rafał Kasperowicz
• Języki publikacji: PL

Abstrakty

Energia elektryczna stanowi kluczowy zasób produkcyjny nowoczesnej gospodarki, jest towarem specyficznym, związanym z sieciami. Zatem nie można mówić, że przedmiotem obrotu gospodarczego jest jedynie energia elektryczna, lecz pakiet usług związany z jej dostarczeniem. Strategiczne znaczenie dla gospodarki oraz brak możliwości magazynowania energii elektrycznej powoduje, że niezwykle poważny staje się problem doboru właściwej wielkości produkcji energii elektrycznej. Zatem synchronizacja wielkości popytu i podaży przed "wpuszczeniem" prądu w sieć stanowi najistotniejszy problem ekonomiczny, przed którym stoją producenci energii. W niniejszym artykule zaprezentowano model popytu na energię elektryczną gospodarstw domowych z regionu Wielkopolski służący do prognozy krótkookresowej (1-2 miesiące). Prezentowane modelowanie ekonometryczne popytu odbywa się przy wykorzystaniu odpowiednio przygotowanych szeregów czasowych. (fragment tekstu)

EN

In this paper the author uses the leading indicator method to analyse the pattern of household electricity demand in Wielkopolska. Due to the special nature of electricity - its "unstoreability", electricity supply and demand have to be in equilibrium at any time. This feature of electric energy causes a serious problem of estimation proper amount of electric energy which has to be supplied by producers. This paper contains an econometric analysis of household electricity demand. The method of leading indicators mentioned in this paper seems to be very efficient for forecasting. The results obtained by the author suggest good efficiency of the estimated model. The model is useful for one or two months ahead forecasts. Another very important facet of household electricity demand is the choice of explanatory variables. Those presented in this paper (electricity price, earnings) come from official data, however research should include more variables (such as price of alternative energy sources, temperature, etc.). Although the above mentioned forecasting methods have some drawbacks, they seem to be efficient enough for companies involved in electricity production and distribution business. The author suggests that the analysis of electricity demand should undergo further research. (original abstract)

Słowa kluczowe

PL

Energia elektryczna; Popyt; Konsumpcja energii; Zużycie energii; Zapotrzebowanie na energię

EN

Electric power; Demand; Energy consumption; Energy use; Energy demand

• Czasopismo: Studia Doktorantów / Akademia Ekonomiczna w Poznaniu
• Rocznik: 2006
• Numer: nr 2
• Strony: 139--148

Twórcy

autor

Rafał Kasperowicz

Bibliografia

• Baxter M., King R.G, Measuring Business Cycles: Approximate Band-Pass Filters for Macroeconomic Time Series, Review of Economics and Statistics, 1999
• Beenstock M., Goldin E., Nabot D., The Demand for Electricity in Israel, Energy Economics, 1999
• Bennett A., Closed-End Country Found Discounds and Systematic UK and US Market Movements: Co-integration and Error Corrected Granger Causality Tests, Massey University, 2002
• Diebold Francis X., The Past, Present, and Future of Macroeconomic Forecasting, University of Pennsylvania, NBER and Federal Reserve Bank of Philadelphia, 1997
• Engle R.F., Granger C.W.J., Hallman J.J., Merging Short- and Long-run Forecasts: An Application of Seasonal Cointegration to Monthly Electricity Sales Forecasting, Journal of Econometrics, 1989
• Engle R.F., Granger C.W.J., Ramanathan R., Short-Run Forecasts of Electricity oads and Peaks, International Journal of Forecasting 1997
• Evans M.K., Practical Business Forecasting, Blackwell Publishers, 2003, p. 212-215
• Granger, C.W.J., Some Properties of Time Series Data and Their Use in Econometric Model Specification, Journal of Econometrics 1981
• Hawdon D., Al-Azzam A., Estimating the Demand for Energy in Jordan: a Stosk-Watson Dynamic OLS (DOLS) Approach, University of Surrey, UK
• King R.G., Rebelo S.T., Resuscitating Real Business Cycles, NBER Working Paper 2000
• King R.G., Plosser C.I., Stock J.H., Watson M.W., Stochastic Trends and Economic Fluctuations, American Economic Review 1991
• Leth-Petersen S., Micro Econometric Modeling of Household Energy Use: Testing for Dependence between Demand for Electricity and Natural Gas, The Energy Journal 2002
• Marcellino M., Leading Indicators: What Have We Learned? IEP-Bocconi University
• Mills T.C., Modeling Trends and Cycles in Economic Time Series, Loughborough University, 2003
• Oxley L., Fatai K., Scrimgeour F.G., Modeling and Forecasting the Demand for Electrycity in New Zeland: A Comparision of Alternative Approaches, The Energy Journal 2003
• Prescott, E.C., Theory Ahead of Business Cycle Measurement, Quarterly Review, Federal Reserve Bank of Minneapolis, 1986
• Stock, J.H. Watson M.W., A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience, NBER Working Paper, 1992
• Torben Mark Pedersen, Alternative Linear and Non-Linear Detrending Techniques: A Comparative Analysis Based on Euro-Zone Data, Copenhagen: Minystry of Economic and Business Affairs, 2002
• Zarnowitz V., Braun P., Major Macroeconomic Variables and Leading Indicators: Some Estimates of Their Interrelations, 1886-1982, NBER Working Paper, 1989