Methods Of Electric Load Forecasting Based On Energy-saving And Emission Reduction

In recent years, the economics in China has been growing rapidly; great achievements have been made in many kinds of constructions to the country. But at the same time the contradiction between economic development and environment has become acuter and the public's reactions to the environmental problems have been more and more strongly. Right now ESAER (Energy Saving and Emission Reduction) has actually become the key task of the national economic works, and the power industry will hold the prominent position in the ESAER. At present the major measures executing ESAER in power industry are focusing mainly on the generation-side. However, ESAER will bring great impact on all sides of electric industry with no doubt. So the researches of load forecasting methods in the context of ESAER have great practical significance for network planning, operation and other aspects of power system.On the basic of full knowledge of ESAER in China and East China, after the inspiration are gained from the developing history of the power industry of Japan, the new features of power consumption in East China(EC) in the context of ESAER are analyzed.Meanwhile, in order to consider the impact of ESAER directly in the power consumption forecasting model, learning form the economic Solow model, the slow power consumption forecasting Solow model is created, in which GDP of EC is used to represent the EC's economic development, the industrial portion of total GDP in EC and power intensity are used to represent the implementation of ESAER in EC. Then the total power consumption growth in EC is broken down into the growth caused by economic development, the growth caused by industrial structural adjustment and as well as the growth caused by the implementation of ESAER. After each part of power consumption is forecasted, the whole power consumption can be calculated.In order to consider the differences between EC's four provinces and one city in economic development, industrialization, industrial restructuring and the implementation of ESAER, based on panel data theory, this paper also created panel data model, in which the GDP of each province and city is used to represent the economic development of each province, the industrial structure of each province and R&D expenditures of each province are used to represent the implementation of ESAER in each province and city. In combination of provincial and municipal economic development, industrialization process in the actual situation, the power consumption of each province is forecasted, then the power consumption in whole EC can be forecasted.End of this article, the correlation analyzing method and fuzzy theory are used to forecast the power consumption in EC during "Twelfth five-years". Then the integrated hierarchical model is used to process the forecasting results of correlation method and fuzzy method to get the forecasting results without considering ESAER. Afterwards in this article build Solow model and panel data model are used to forecast the power consumption in EC, which is considered as forecasting results with considering ESAER. At last, three types of forecasting model predicted results are compared and ESAER's impact on the power consumption in the future are also analyzed. Comparing results show that Solow model and panel data model can be effective in taking the impact of ESAER into account, which shows a beneficial exploration under in new situation.