Forecast of Energy Demand for Chongqing City
|Keywords||Energy demand ARIMA Regression Analysis Grey Theory Forecast and Analysis|
Energy is an important material foundation for social development, with the rapid growth of China's GDP, the whole society is growing demand for energy. Develop scientific and rational energy development strategy can effectively ensure the socio-economic stability and orderly development. The correct energy development strategy can not be separated from the energy demand forecast and analysis. Therefore, the energy demand and forecasts as well as the accuracy of the results will have a significant impact on China's economic development. Since Chongqing became a municipality, the socio-economic development has made remarkable achievements, has entered the industrial development of the medium-term. This round of development cycle is in a high-energy stage, the surge in demand for energy, frequent power cuts \. In this paper, the energy demand in Chongqing as the object of study dedicated to the study of energy demand model. Chongqing coal consumption as empirical comparative analysis through a variety of models to arrive at the most appropriate Chongqing Energy Demand Forecasting Model. The research results can provide basis for decision making Chongqing establishing reasonable energy development, strategic planning, optimizing energy structure, promote sustainable development. Research methods proposed in the paper can also be applied to energy demand analysis and energy demand forecasts. The paper is divided into six chapters. The first chapter is an introduction. The second chapter is Chongqing Energy Consumption Situation Analysis. In view of the complexity of the system features energy demand, first introduced the concept of energy and energy demand, and for the study of Chongqing City, Chongqing Energy Consumption Situation analysis to identify the main problems in the energy consumption. The third chapter is the analysis of energy consumption on the basis of the status quo in front, use the ARIMA model to model the energy consumption in Chongqing. The fourth chapter introduces the modeling of regression and ARMA combination models Chongqing energy demand. The fifth chapter introduces the comparison of the predicted results of the gray model Chongqing energy demand modeling and three models. By comparing the study found that: the combination of non-linear regression and time series model for the optimal prediction model, and use the model to forecast demand for coal resources in Chongqing from 2006 to 2008. The sixth chapter of conclusions and recommendations. Summarizes the paper work done and the results achieved and the problems in the energy consumption of Chongqing proposed corrective measures and recommendations.