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Research for Short-term Load Forecasting Based on District Power Grid

Author: LiuJiaXue
Tutor: YangHuPing
School: Nanchang University
Course: Proceedings of the
Keywords: Short - term load forecasting Artificial Neural Networks Cascade Neural Network Model Gray model
CLC: TM715
Type: Master's thesis
Year: 2006
Downloads: 167
Quote: 1
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Abstract


Short-term power load forecasting is essential operation of the power system operation , the result of the load forecasting is to arrange power generation plan , determine the spare capacity on the basis of the results accurate or not , have an important impact on the security and economy of the system running . Therefore , how to improve the accuracy of short - term load forecasting has always been one of the people committed to the research direction . At present , many domestic and foreign literature on the power system short-term load forecasting , but because of the uncertainty of many factors that affect the load and the load , making short - term load forecasting has not been very satisfactory solution . This paper describes the concept and significance of short-term load forecasting , then introduces the research status quo of the current short - term load forecasting , and analysis of the advantages and disadvantages of several existing load forecasting method . Secondly, the neural network theory , a brief description of the two forward network carried out a detailed analysis , also discussed the differences between these two networks . In this paper, the load characteristics of the regional power grid research conducted in-depth analysis and discussion . Specific grid study the impact of changes in the electrical load some factors that can be measured , and a detailed analysis of the specific impact of the relationship between the various factors and load characteristics . In this paper, based on in-depth analysis of the load characteristics and the neural network to establish a prediction model based on BP network and RBF network cascade neural network (CNN) . Model the sub- network processing , respectively, can be measured factors and historical load value of load forecasting . Reasonably quantified and normalized in the implementation of the model , on a variety of factors and input a process . Finally, this model is applied to the routine daily load forecast . The numerical results of the model analysis showed that the cascade model predictions to achieve a satisfactory accuracy , and practical value . For the holidays load forecasting , this paper proposed a separate solution . Longer than the poor information modeling gray model based on the the holidays load of characteristics . And improved gray model used for the holidays load forecasting . Calculation examples show that the predicted results with high accuracy, and to prove the feasibility of applying the model .

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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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