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Research of the Power Load Forecasting and Optimization Based on GIS
Author: LiuLiHui
Tutor: TangGuoWei
School: Daqing Petroleum Institute
Course: Applied Computer Technology
Keywords: Geographic Information Systems Fuzzy Logic RBF Neural Network Spatial Load Forecasting
CLC: TM715
Type: Master's thesis
Year: 2009
Downloads: 101
Quote: 0
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Abstract
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The space load forecasting distribution network planning basis . In the distribution system planning , not only to predict the amount of the load , but also to predict the position of the load , and only in determining the load spatial distribution on the basis of the distribution grid the cloth point and the wiring plan . The use of GIS (Geographic Information System, GIS) spatial information distribution , distribution network space for short-term load forecast method . This article extraction and analysis capabilities , powerful spatial data using geographic information systems to collect data for the distribution grid space load forecasting demand , extraction and analysis required for the original data . Spatial load forecasting algorithm -depth study , the application of fuzzy logic theory constructed with the actual pattern of the grid space load forecasting , integration of the advantages of the artificial neural network , taking into account the actual situation , the RBF neural network to adjust fuzzy sets , and training fuzzy rules , making load forecasting is able to adapt to the development of the city . The detailed algorithm proposed distribution network spatial load forecasting based on geographic information system . GIS system, the power supply area is divided into a number consistent with the size of the cell , cell score using fuzzy reasoning , by RBF network distribution of land use , come to the land-use decisions , ultimately , the calculated cell load forecasting value . In this paper, the step with the grid space load forecasting in practical engineering has been validated , show that the method is effective , especially for calculating the limited resources .
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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Theory and Analysis > Power system planning
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