The Forecast Of Energy Demand Based On Combination Model And Policy Research In Liaoning Province

Energy is the support and power of the development of national economy, and it is an important material foundation for society bustling. China, as the country in which the economic and social development is the most rapid, energy is widely used in various fields such as industry, transportation, construction and the lives of residents. The energy consumption in China is mainly coal. The rapid economic development also causes serious environmental pollution.Liaoning Province is an important old industrial base in our country, it is rich in resources, but it is also a major energy consumer Province. In recent years, the total energy consumption continued to grow, leading to the contradiction between supply and demand more and more prominent. Meanwhile, energy structure in Liaoning is single, environmental pollution is serious. The increasing energy gap is a major bottleneck constraining the economic development of Liaoning Province. Therefore, how to achieve the concordant and sustainable development of environment, economy, and nature, and setting the strategic approach for energy development, are the primary solution to the revitalization of Northeast China old industrial bases. According to the stated objectives in "the12th Five-Year Plan" of Liaoning Province, the energy consumption per unit of GDP is expected to be reduced by17%.The realization of this goal depends largely on the scientific forecast of the energy demand of Liaoning Province, and on this basis to formulate a rational energy development strategy.At present, on the study of energy demand forecast, most of domestic scholars take the whole country as the object of study, but rarely take the region (province or city) as the research object. To the question of the increasing gap between energy supply and demand in Liaoning Province, this paper try to analyze and research the energy demand in the next few years in Liaoning Province.Domestic and foreign scholars generally agreed that if only use a single model to predict energy demand, then prediction accuracy is low, and can not fully reveal the complex characteristics of the energy demand system. Therefore, this paper choose a combination model of exponential smoothing method, gray prediction model and artificial neural network model, that is, take exponential smoothing, gray model and neural network model through a weighted combination, obtain the results. In this way, this paper not only taking into account the impact of factors on the energy demand, but also can consider the predictive ability of traditional prediction model. So it has a certain sense of innovation.This paper applies a method of qualitative and quantitative analysis, forecast the energy demand of Liaoning Province during the "12th Five-Year ", and put forward policy proposal.The first chapter begins with a brief introduction of the current situation of energy in China and Liaoning Province, and it proposes the establishment of high precision energy demand forecasting model is of great significance for the development of energy development strategies. Then summarizes the research literatures on energy demand forecast at home and abroad. Finally, proposes the main research content and methods as well as innovation and deficiencies.The second chapter studies the current situation of the energy consumption in Liaoning Province as well as the gap between supply and demand. Take energy structure of consumption, three industrial structure and industrial energy consumption, intensity of energy consumption, energy contradiction in Liaoning Province as basis, the historical change trend and present situation of energy consumption have been analyzed. In the analysis, a large of data has been collected. By comparison of data, it reflects the real situation and the existent problem of energy supply and demand in Liaoning Province, revealing the need of energy-saving.The third chapter constructs the index system of energy demand influencing factors. With the Cointegration model and Granger causality tests, this chapter analyzes the long-term relationship between the energy consumption of Liaoning Province and the economic growth. On this basis, with the Multiple regression method, building a regression equation between total energy consumption and economic growth, population, the structure of energy consumption, industrial structure, technological progress, the level of consumption, and the urbanization rate in Liaoning Province. The result reveals the main factors and degree of influence of Liaoning Province’s energy needs, providing a basis for developing energy-saving measures and proposing relevant policy.The forth chapter constructs the exponential smoothing model, the gray prediction model, the artificial neural network model, and their combination model to predict the energy demand of Liaoning Province.The fifth chapter uses the exponential smoothing model, gray forecasting model, artificial neural network model, and their combination model to predict the energy demand in Liaoning Province during the "12th Five-Year" period, and predicts whether the energy-saving target proposed in the "12th Five-Year Plan" in Liaoning Province could be achieved, exploring the energy demand seriousness of the situation in Liaoning Province, further illustrates the need for energy conservation.The sixth chapter proposes energy saving countermeasures and summarizes the conclusions of this paper.Through the calculation and analysis, it proves that exist a significant linear relationship between the demand of energy and actual GDP, the proportion of tertiary industry, population and intensity of energy consumption in Liaoning Province. Compared with other single models, the combination forecasting model has higher prediction accuracy. Then it predicts the total energy demand during the "12th Five-Year" period in Liaoning Province using the combination forecasting model. The result reveals that during the "12th Five-Year" period, energy intensity in Liaoning Province will reduce by15.41%compared to2010, there is a large gap compared the target of17%.Therefore Liaoning Province should increase energy conservation efforts, develop a good energy strategy and put it into practice.