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The Research of Short-term Load Forecasting Technology in Electric Power Load Management System

Author: TianXiao
Tutor: GuDeYing
School: Northeastern University
Course: Control Theory and Control Engineering
Keywords: Power Load Management Short - term load forecasting Neural Networks Error back propagation algorithm Particle Swarm Optimization
CLC: TM715
Type: Master's thesis
Year: 2008
Downloads: 94
Quote: 0
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Abstract


The short-term load forecasting electricity load management system is one of the important issues in the study of modern power system operation . Power system short-term load forecasting results to study the problem of power system planning , power system economic operation scheduling automated basis . Practice has proved that , in today 's increasingly complex power system development , traditional load forecasting technology has become increasingly difficult to meet the electricity sector is increasingly high load forecasting accuracy requirements , so the application of intelligent algorithm for power system short-term load forecasting , improve the accuracy and stability of the load forecasting , has very important significance . This paper outlines the background and short-term load forecasting of power system load management procedures and the status quo , then the composition of the power system load management system , with an emphasis on the BP artificial neural network in short term load forecasting . Exist for the most commonly used in the BP neural network algorithm , slow convergence and easy to fall into local minima problems , this paper an improved algorithm to optimize the neural network , the power load forecasting . Application Dezhou, historical load data to establish short-term load forecasting system test validation , compared with the traditional BP neural network can be seen that the neural network prediction model established in this paper based on particle swarm optimization (PSO) algorithm can improve the prediction accuracy of the prediction performance is better than good nonlinear mapping ability of neural network - based load forecasting , and further developed and applied to forecast good prospects for actual online .

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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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