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Research on Chaotic Theory and Its Application in Short-Term Electric Power Load Prediction

Author: YinLiJie
Tutor: ChenYanQiao
School: North China Electric Power University (Hebei)
Course: Control Theory and Control Engineering
Keywords: Chaos Time Series Power Load Forecasting Lyapunov exponent Weighted rank local
CLC: TM715
Type: Master's thesis
Year: 2009
Downloads: 147
Quote: 1
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Abstract


This paper reviews and analyzes the basic concepts of Chaos Theory , Research status and application of chaotic time sequence discrimination , the phase space reconstruction and its corresponding parameter selection method , Lyapunov exponent calculation method . This paper examines a model of the the chaotic trends combination of power daily load records . Since there is a clear trend toward daily load , daily load time series is decomposed into trend sequences and the remaining sequences . On the basis of the weighted one-rank local law introduces the concept of associate degree , and greatly improve the accuracy of the forecast ; adjacent rail line direction in order to reflect its evolution from the details of each phase point the cosine of the angle between the direction of evolution as part of the weights , so a more detailed description of the degree of correlation between the attractor trajectories ; Lyapunov exponent forecasting method and method of weighted order divergence analysis and research . Finally, the combination of chaos theory and neural network , after repeated recursive network training to obtain a satisfactory prediction results .

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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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