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Research For Power System Short-Term Load Forecasting

Posted on:2005-11-09Degree:MasterType:Thesis
Country:ChinaCandidate:Q Y HuFull Text:PDF
GTID:2132360152955243Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Power system short-term load forecasting(STLF) is an important task of power utilities ,So great attention has always been paid on methods of STLF. Load forecasting is related to operation security and economical dispatching of power system , which is used to arrange the equipments dispatching and repairing .Also it can advance the stability of power system and save generation costs. With the development of area power market in China, STLF will play an important role in the operation of power market.In the first step ,this paper analyses the constituents and characteristics of the electrical load, and the difference of several present STLF methods. The basic theory of ANN for load forecasting are emphysized, and a forecasting model for an actual power system is presented in this paper to forecast the load. In the second step,the model devides the load into a few main parts: basic load, difference of temperature and weather , different daytype(working day and holdiday). So improved BP Network of three layers are used to set up the model. The factors which effect the load are the samples, and through self-training and study to finish the model. This paper uses three-BP ANN to set up a load forecast model, above factors are used as data samples. Though the self-training and self-study of the network, and in the process oftraining and study continuously introduces (BP method) to revise the weight value of ANN. Thus improved the model of load forecast. After the end, the repairing of lines and equipments in power system is also considered in this paper, and because of that, the exactly result are concluded.In practical,above forecasting method is proved to be prefect and its forecast accuracy is very well too, which satisfy the operation requirements of power system and economical dispatching,save the costs of purchasing and improve the efficiency of operators, and keep the security of power system.
Keywords/Search Tags:Short-Term Load Forecasting, Artificial Netural Network, BP Arithmetic
PDF Full Text Request
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