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Research On The Forecasting Of Shenzhen Power Demand

Posted on:2017-09-28Degree:MasterType:Thesis
Country:ChinaCandidate:K ChengFull Text:PDF
GTID:2322330536953013Subject:Engineering
Abstract/Summary:PDF Full Text Request
Since the reform and opening up,Shenzhen economy has experienced rapid development.As power consumption and electric load shows a rapid growth trend,Power supply and demand balance has become an important aspect of the power market to support the development of social economy.Shenzhen lags behind economic development to a certain extent in the power and power grid planning before 2008,and there is a contradiction between supply and demand.In recently years,with the slowdown in economic growth and structural transformation of the economy,the power demand in Shenzhen has showed a slow growth and strengthening the demand management and stimulating the demand for electricity has become the main strategy.Therefore,power demand prediction,as the basic work to adapt to the requirements of the market economy,ensure return on investment of power enterprises and improve operating efficiency,has an important impact on network planning,power marketing strategy formulation and decision-making of power enterprises.This paper introduces the social and economic characteristics of Shenzhen,and analyzes how temperature and key national economic indicators influences electricity demand through datamining.Based on business expansion data,which can sensitively reflect customer demand,this paper proposes power demand index concept,to predict power demand developing trend in future.Using time series model,co-integration model and hybrid prediction mode.This paper predicts Shenzhen overall power demand,different districts and industries demand,which can provide data basis for power enterprises to make better power supply and grid planning in near future and better support the steady transformation of the city and operation and management of enterprise.
Keywords/Search Tags:Power Demand, Data Mining, Demand Prediction
PDF Full Text Request
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