Research On Mid-Long Term Load Analyzing And Forecasting Based On Econometrics

Load forecast is an important domain in power system research. It's also one of the important tasks for the departments of power system such as dispatching, planning and programming. The precision of load forecast has a direct effect on the security, economical efficiency, and quality of power supply of power system operation. Therefore, people attach importance to the research of load forecast all the while. Besides, along with the improvement of people's standard of living, the increase of the electricity quantity of the society, load forecast is more and more important in power system. So the requirements of its veracity, celerity and intelligentization are more rigorous.It's difficult to do exact quantitative research for mid-long term forecasting because there are excessive factors, and different regions have different actualities. There's a close correlation between the electricity demand of a region and its economic status. So it has an important effect on improving the precision of mid-long term load forecast to gain a mastery of the connection between electric power and economy and analyze economy reasonably. This paper used the theories and methods of econometrics, trying to grasp the effect on electricity demand taken by economic factors clearly and search after the models which have more practical preconditions, and have more powerful realistic meanings.The main achievements involve the following aspects:1) The actuality of load forecast was analyzed, and some important methods of load forecast were introduced.2) Research on econometrics and the econometric models used in this paper was made.3) A new method for mid-long term load forecast modeling based on gray econometric model was presented. Gray system model taking effects in traditional econometric model, the fitting effect of traditional model is better, and the forecasting accuracy is improved.4) Panel data model was made by using the data of electricity quantity and gross domestic product of different cities. Analyzation and comparation among different cities were made quantitatively. The effect on electricity demand made by business cycle was analyzed by using dummy variables.5) The theory about cointegration was used to analyze the long term connection between the electricity quantity and gross domestic product.