Research On Electric Power Demand And Economic Growth

Electricity is the symbol of modern industrial civilization and is also the basic inputof production and necessity of ordinary livings. With the development of economy theelectric industry plays more and more important role in national economy. In 2003 withper GDP up 1000 dollar and market-oriented reform of power sector in China, the stablesupply of electricity to boost the development of economy is of imminent significance.Therefore the research on the relation between electricity consumption and economygrowth is of primary theoretic and policy interest. In this dissertation on the backgroundof electricity demand and economic growth in China, a thorough study is undertakenfrom three perspectives, which is theoretic method, empirical analysis and forecastapplication. The main research objects and results are:1. In the first place co-integration theory is applied to examine the Grangercausality between electricity consumption and economic development in the timedomain. The research indicates that there exists co-integration between them and there isunilateral Granger cause running from electricity consumption to economic development.Then Granger causality theory in frequency domain is applied to examine the cyclecomponents of them, with the results that there is unilateral Granger from electricity toeconomy and also coincides with the frequency of business cycle in China. The resultsthat there is co-integration and co-feature between electricity consumption and economydevelopment are of important policy implication for electric sector in China.2. The relation between electricity consumption and economic growth fromperspective of economic growth stage is studied. The qualitative judgment criterionbetween industrial electricity demand and the stage of industrialization is proposed.Then econometric analysis on power energy intensity is undertaken to provide guide fortrend of future energy intensity.3. Electricity demand models based on co-integration theory are studied. A noveldynamic prediction model for integrated series based on Granger causality is proposed.The vector error correction model based on co-integration theory is expanded in twoperspectives: the first being considering explicitly co-movement of cointegrated seriesin VECM and the second considering regime switching such as structure change anddissymmetry in business cycle in VECM and are applied in power demand forecasting.The case studies indicate the application effect of these two models.4. Rough Sets (RS) based uncertainty decision rules mining is applied in powerenergy economics. The basic methods and application algorithms of RS are discussedand particularly two cases for power energy intensity and energy consumption growthrate in China are studied.5. From perspective of methodology, the research on the relationship betweenelectricity consumption and economic growth is described: (1) Intelligent Engineering,the foundation of the study, is discussed and proved by Model Theory. Also algebras forsub-space calculation are defined preliminarily. (2) Based on domain and expertknowledge and inspired by computer automatic model selecting algorithm (PcGets),power econometric model identification process is studied. The combination ofeconometric analysis based "model mining" and logic based rough set "rules mining" isstudied. Intelligent Engineering describes both processes.