2013Electric DriveRequires access

Application and Research of Short-term Load Forecasting Management System for a Certain Power Network

Chen Su-hu

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Abstract

As one important content of electric benchmarking electric,power system short-term load forecasting,which playing an important part in power grid construction,is the key of planning generation and keeping balance between supply and demand for dispatching and control center. Based on power network short-term load forecasting management system in certain area,time series method,similar day method,Artificial Neural Network method,and a new forecast method was used to forecasts the daily load.According to the comparison of forecasting results of the above four methods,the causes of forecasting errors were analyzed and the research direction of short-term load forecasting was brought out.

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What this paper is about

As one important content of electric benchmarking electric,power system short-term load forecasting,which playing an important part in power grid construction,is the key of planning generation and keeping balance between supply and demand for dispatching and control center. Based on power network short-term load forecasting management system in certain area,time series method,similar day method,Artificial Neural Network method,and a new forecast method was used to forecasts the daily load.According to the comparison of forecasting results of the above four methods,the causes of forecasting errors were analyzed and the research direction of short-term load forecasting was brought out.

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Available abstract

As one important content of electric benchmarking electric,power system short-term load forecasting,which playing an important part in power grid construction,is the key of planning generation and keeping balance between supply and demand for dispatching and control center. Based on power network short-term load forecasting management system in certain area,time series method,similar day method,Artificial Neural Network method,and a new forecast method was used to forecasts the daily load.According to the comparison of forecasting results of the above four methods,the causes of forecasting errors were analyzed and the research direction of short-term load forecasting was brought out.

Key concepts: Benchmarking, Term (time), Electric power system, Artificial neural network, Computer science, Demand forecasting, Reliability engineering, Electric power

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