This paper will research the relationship between the Beijing industrial structure and the sustainable development through the 3EDSS which provides an all-round, multi-level international index data inquiry, statistics, analysis and computation function and grey correlation analysis theory, analysis the degree of association between each industry and GDP, energy consumption elasticity coefficient, sulfur dioxide emissions of Beijing, thus putting forward some suggestions for Beijing to the sustainable development and industrial structure optimization.
At present, China is in a critical period of energy restructuring. Renewable energy industry bear to ensure national energy security and achieve the historic task of energy for sustainable development. To speed up technological innovation of renewable energy industry has been a priority. Conducting systematic research of renewable energy technologies selected, not only can grasp the advantages of renewable energy resources, a clear direction of development of industrial technology, but also to enrich and improve the industrial technology innovation management theory and methods to make a positive contribution. This paper established a renewable three-dimensional evaluation model of industrial technology development (technology needs dimension, technology dimension and the supply of integrated environmental dimensions) ,and took Beijing as an example to calculate the Beijing photovoltaic, wind power, biomass and small hydro renewable energy generation technology evaluation results.
With the growing tension of the energy resources, energy risk has become the core of common concern. In this paper, the definition and the cause of energy risk analysis, combined with the analytic hierarchy process (AHP) construct the comprehensive risk-based energy industry index system. According to the viewpoint of information theory, the entropy method to calculate the objective factors, to measure the information content of the Beijing Energy Risk indicators inexact. By visual comparison of each indicator entropy, research the impact of various indicators of system.
With the increasing risk in electric power bureaus, warning risk of enterprise operating ability in advance is an important work. However it is very difficult to establish stable functions to describe the mapping relationship between operating ability and associated causal influences. Hence, early warning of the operating ability is harder. In this paper, an early warning model based on BP neural network is designed and put forward to forecast the risk of operating ability of an electric power bureau. In addition, illustration by the experiment is given. The stable and accurate analysis result of the experiment shows that this early warning model is applicable to forecast the risk of operating ability of electric power bureaus.
Based on the depth analysis of the related literature and the present situation of energy consumption of Beijing’s carbon emissions, through the MATLAB programming on the Lagrange interpolation algorithm, the paper predicts the carbon emissions from energy consumption in Beijing’s economic growth. According to the relevant historical and predicted data, the paper examines the process of Carbon Emission Trend of energy consumption in Beijing. The results show that: Beijing carbon emissions showed "Y=X3" type growth. Combining the current situation, the paper analyzes the results, and finally provides decision support to the government, to promote the relationship between economic growth and energy consumption of carbon emissions in Beijing city into the inverted "U" trend.
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