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Nonlinear Prediction Of The Power Demand And Research Of The Assets Management Information System For The Power Supply Company

Posted on:2009-02-26Degree:DoctorType:Dissertation
Country:ChinaCandidate:X LiuFull Text:PDF
GTID:1119360272485655Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Power industry is the elementary industry of the national economical system, and whether the electricity supply can meet the demand of the economic development and the progress of the people's living standard is a key problem to sustainability of the whole world. A high quality and accurate of the power demand prediction is the prerequisite of the sustainable development between the power industry and national economy. The detailed research work is as follows:First, based on the analysis of the society and economical status in Tianjin, the thesis discussed the power supply and demand, electric network and source of power, status-of-equipment of electric network and the open questions. Next using the support vector machine theory, we predicted the short period(half year)demand of the power in Tianjin.The thesis used four different methods to predict the mid and long term power demand: we predicted the power demand of the residents first with the stochastic gradient regression method; and predicted the power demand of the third industry with multivariate adaptive spline regression; then we predicted the power demand of the first industry with fuzzy artificial neutral network, and the power demand of the second industry with stepwise regression method. Last, we got the mid-long term power demand of Tianjin.To the many problems exist in the assets management of the power supply company, the thesis first redefined the minimum statistical unit of the power company's assets, and improved the management of the investment of the power company with introduction the scientific investment decision method such as second-level fuzzy integrated diagnosis and multi-objective decision. Then based on the analysis of the characters of the professional work in power company, we development the management system of the power company assets with 4GL language and object-oriented technology.By analyzing the development environment of the power industry, the thesis discussed macro development status of the national and Tianjin power industry, and then put forward the development strategy of the Tianjin Electronic Power Company.
Keywords/Search Tags:Power demand, Prediction, Support vector machine, Stochastic gradient, Development strategy
PDF Full Text Request
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