Based On The Coupling Of The Population, Industry, Energy Demand For Energy Research In Shanghai

Energy is the driving force of modern civilization. The sustainable economic and social development of Shanghai cannot be separated from a stable and effective energy supply. For determining energy plan and energy management, the analysis of energy demand in Shanghai has an irreplaceable role for the economic and social systems. Energy demand analysis is to fine the key factors or elements and the relationship between them, to determine the future demand for energy. However, Shanghai is in a critical period of building a moderately prosperous society, a rapid increase in demand for energy, often consumed much higher than the established amount of planning. Therefore, the accurate and reliable analysis of energy demand is the primary task.The thesis will be based on the coupling analysis between population, industry and energy in Shanghai. The relationship between population and energy manifested in the energy consumption of residential and passenger transport. Near the medium term, Secondary industry, especially high energy-consuming industries will continue to be the major component of energy demand. Therefore, this paper will be based on the specific investigation of the population and industrial characteristics to the overall energy demand analysis, including econometric regression analysis and scenario analysis based on detailed terminal departments.From the macroscopic measurement, the thesis gives the driven factors of energy consumption and the driven degree of population scale for energy consumption. From the microscopic measurement, the thesis builds the scenario analysis form the bottom to the up. As the important parameters of scenario analysis, the thesis builds the modified economic optimum population model. In addition, the thesis builds the saturation of the logistic curve to fit the path of the energy-intensive products. The thesis based on the long-term perspective to find the macro mechanism and micro foundation, to grasp the inherent laws of population scale, economic scale, industrial structure and energy demand, to track the dynamic trend of population development, economic growth, industrial restructuring and energy demand.The main conclusions are as follows:Firstly, as the support module of the coupling analysis of population, industry and energy, the empirical study of modified economic optimum population model shows that moderate economic population in the next two decades will experience a "S "dynamic process:steady--slight increase--accelerate growth--slower growth. In order to maintain the cointegration and dynamic synergy of population scale and industry structure, population remain stable at23million in the"12th Five-Year" period, maintain a slight rise increasing to23.52million in the "13th Five-Year" period, have a rapid growth to25.28million in the "14th Five-Year" period, have a slowdown increase to26.92million in the"15th Five-Year"Secondly, the econometric analysis of population Industry and Energy based on coupling system shows that the population size, economic size, industrial structure, are the three major driving forces of the energy consumption in Shanghai. Shanghai energy consumption is dynamic, driven by population, economic scale, industry structure significantly. Secondary industry energy consumption is dynamic, driven by industrial structure significantly. Tertiary industry energy consumption is dynamic, driven by population significantly. Residential energy consumption is also dynamic, driven by population significantly. The next two decades, the total energy demand and the energy demand of tertiary industry and resident need to considerate population scale as variable.Thirdly, based on the coupling analysis, the thesis identifies the baseline scenario, the economic optimum population based on the baseline scenario, the high energy consumption scenarios and the energy-saving scenarios. The total scenarios showed a continuous increase but the slowing increase speed. Shanghai energy demand in the baseline scenario grows at an average annual rate of nearly3percent, reaching200million tons of standard coal. In the economic optimum population based on the baseline scenario, energy demand grows at average annual rate of2.8percent, reaching195million tons of standard coal, producing "moderate population saving effect" of4.59million tons of standard coal. In high energy consumption scenario, energy demand grows at average annual rate of3.7percent, reaching230million tons of standard coal, producing "extensive energy effect" of31.53million tons of standard coal. In energy saving scenarios, energy demand grows at average annual rate of2.3percent, reaching175million tons of standard coal, producing "intensive energy effect" of25million tons of standard coal.The scenario analysis results may generate uncertainty in energy demand due to the uncertainty of the parameter selection. As time progresses, the uncertainty of the energy demand grows higher and higher. The thesis needs to strengthen the reliability of data analysis, reducing the uncertainty of the results.