Energy And Economic Development 英语论文.doc

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1、Energy And Economic Development Economy and management academy ,Class 911,Harbin Engineering UniversityMarch 20,2011Abstract Energy is a vital input for social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also

2、 increasing. Formulation of an energy model will help in the proper allocation of widely available renewable energy sources such as solar, wind, bioenergy and small hydropower in meeting the future energy demand in China. During the last decade several new concepts of energy planning and management

3、such as decentralized planning, energy conservation through improved technologies, waste recycling, integrated energy planning, introduction of renewable energy sources and energy forecasting have emerged. In this paper an attempt has been made to understand and review the various emerging issues re

4、lated to the energy modeling. The different types of models such as energy planning models, energy supplydemand models, forecasting models, renewable energy models, emission reduction models, optimization models have been reviewed and presented. Also, models based on neural network and fuzzy theory

5、have been reviewed and discussed. The review paper on energy modeling will help the energy planners, researchers and policy makers widely.Key words: energy economic development energy planning modelsArticle Outline1.Energy introduction2.Energy planning models3.Energy supplydemand models4.Forecasting

6、 models5.Energy models based on neural networks6.ConclusionReferences1.Energy introduction In most of the developing countries, the energy problems to be addressed are countering the high dependence on traditional sources of energy which supply more than 90% of total energy used causing rapid defore

7、station, decreasing soil fertility, etc. Thus a large amount of information is required to describe their relationships, and several tools are necessary to analyze different issues and to achieve a variety of results that are needed for the planning process. Apart from the phenomenal growth in popul

8、ation, the marvels of modern technology have enhanced the aspirations of the people for an improved quality of life. One of the indices of improved quality of life is the per capita energy consumption, which has been rising steadily for the last few decades. The net result of this has been that the

9、demand for energy has multiplied manifold and it can be no longer satisfied by the traditional inefficient energy technology using a few local resources only.2. Energy planning models Researchers and scientists had tried developing integrated energy models linking both commercial and renewable energ

10、y sources. A brief review of these integrated energy system models has been presented here.Financial feasibility analysis of box type solar cookers had been discussed by Kumar et al. (1996) in India using cost functions and expressions for some financial performance indicators had been derived. Able

11、-Thomas (1996) had discussed the benefits and needs for renewable energy technology transfer to developing countries. Also, the author discussed the different models or channels of renewable energy technology transfer for successful dissemination in developing countries. Models for energy conservati

12、on to be used in energy audits had been presented by Abdelhak Khemiri-Enit and Mohamed Annabi-Cenaffif (1996). An energy planning model had been developed using multiple objective programming (MOP) technique for a small, medium and large farms in Punjab, a state in India. The model is having five ob

13、jectives namely, minimization of energy input, maximization of gross returns, minimization of capital borrowing, minimization of labor hiring and minimization of risk for availability of energy inputs (Surendra Singh , 1996).3.Energy supplydemand models The different types of energy supply models, e

14、nergy demand models and energy supplydemand models had been reviewed in this literature in a detailed manner.The nature and length of the impact that prices and economic activity have on the demand for motor gasoline and distillate fuel oil in the United States had been discussed. Also, a general ap

15、proach had been implemented to aid any energy analyst in gaining insights into the modeling activity (Noel D. Uri and Saad A. Hassanein, 1985) An integrated supply and demand energy planning model for the state of Illinois had been described by Charles and Mark (1987) 72. John D. Sterman et al. had

16、formulated the energy supply model for the estimation of petroleum resources in the United States.The econometric methods provide an approach for modeling supply processes where time delays, lags and capital formation are important.4.Forecasting models Energy forecasting models have been formulated

17、using different variables such as population, income, price, growth factors and technology. The models had been reviewed to determine the energy distribution patterns. The forecasting models have been categorized into two groups, namely commercial energy models and renewable energy models. Commercia

18、l energy models, Renewable energy models, Solar energy models, Wind energy models, Biomass and bioenergy models are some of the energy model in the future. The modeling of the diffusion of energy consuming durables had been studied using various growth curve models (Ang and Ng, 1992). The energy dis

19、tribution patterns resulted from these models had been compared and taken for the study. The ecological foundations of the cultural model and its applications in energy research have been discussed along with some of the analytic consequences of this approach. A forecasting regression model had been

20、 developed for the electrical energy consumption in Eastern Saudi Arabia (Ahmed Z. Al-Garni et al., 1994), as a function of weather data, global solar radiation and population. Five years of data had been used to formulate the energy consumption model. Stepping-regression technique was adopted for t

21、he variable selection. The problem of co-linearity between the regressors had been investigated by using standard statistical procedures and the model adequacy is determined from a residual analysis technique.5.Energy models based on neural networks Intelligent solutions, based on artificial intelli

22、gence (AI) technologies to solve complicated practical problems in various sectors are becoming more and more nowadays. AI-based systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. Fuzzy theo

23、ry has been applied to the logistical optimization of the supply and demand sectors in order to assess the relative importance or degree of association between the supply and demand determinants (Sanders et al., 1993). The economic, environmental and technical concerns are the main objectives includ

24、ed in the model. Atsu S.S. Dorvio et al. (2002) used artificial neural network methods to estimate solar radiation by first estimating the clearness index, radial basis functions (RBF) and multi-layer perception (MLP) methods. 6.Conclusion The different energy models have been reviewed globally. The

25、 following important factors in the energy utilization such as gross income, gross output, profit, energy quantity, GNP/energy ratio, energy performance, energy production have been considered as the objective function of linear programming models. As far as utilization of renewable energy concerned

26、, the prime factors like life span of the system, reliability, intermittent supply, site selection, investment and social acceptance have to be analyzed. It has also been suggested that the neural networks can be used in the energy forecasting and the fuzzy logic for energy allocation of the country

27、.Consulting documents1 P.T. Landsberg, A simple model for solar energy economics in the UK, Energy 2 (1977)2 M.O. Stern, A policy-impact model for the supply of depletable resources with applications to crude oil, Energy 2 (1977)3 S. Fawkes, Soft-systems model of energy management and checklists for energy managers, Appl Energy 27 (1987)4 G.J.Y. Hsu, P.S. Leung and C.T.K. Ching, A multiobjective programming and interindustry model for energy-economic planning in Taiwan, Energy Syst Policy 11 (1987)5 J.P. Weyant, Policy modeling: an overview, Energy 15 (1990)