Power Load Logistic Curve-Forecasting Model Based on Improved Particle Swarm Optimization

doi:10.3696/j.issn.1672-6952.2011.02.017

Journal of Liaoning Petrochemical University ›› 2011, Vol. 31 ›› Issue (2): 62-64.DOI: 10.3696/j.issn.1672-6952.2011.02.017

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Power Load Logistic Curve-Forecasting Model Based on Improved Particle Swarm Optimization

LIU Guo-zhi¹，HE Peng-qing²

1.College of Sciences, Liaoning Shihua University, Fushun Liaoning 113001, P.R.China;
2.Liaoning Fushun Power Supply Company, Fushun Liaoning 113008, P.R.China

Received:2010-12-06 Published:2011-06-25 Online:2017-07-05

基于改进微粒群优化的电力负荷生长曲线预测模型

刘国志1,何鹏清2

1.辽宁石油化工大学理学院,辽宁抚顺113001;2.辽宁抚顺供电公司,辽宁抚顺113008

作者简介:刘国志(1962-),男,吉林德惠县,教授,硕士。
基金资助:
国家自然科学基金资助项目(50771052)。

Abstract

Abstract:

On the basis of the research results published in existing relevant references,the logistic curve methodis are further improved and a new power load logistic curve-forecasting model is proposed based on improved particle swarm optimization(IPSOLM). And the result of the Power load gray-forecasting model based on particle swarm optimization (PSOGM) compares with the result of the new power load forecasting model. The practical example indicates that the new model has the characteristic of better precision and wider application field.

Key words: Particle swarm optimization , Power load forecasting , Logistic curve , Parameter estimation , Grey model

摘要： 在现有文献研究的基础上,对生长曲线预测法作了进一步改进,提出了基于改进微粒群优化的电力
负荷生长曲线预测模型,通过在电力负荷实例中的应用,并与基于微粒群优化的电力负荷灰色预测模型进行了效果
比较,验证了基于改进微粒群优化的电力负荷生长曲线预测模型具有很好的预测精度和通用性。

关键词: 微粒群优化, 电力负荷预测 , 生长曲线 , 参数估计, , 灰色模型

LIU Guo-zhi，HE Peng-qing. Power Load Logistic Curve-Forecasting Model Based on Improved Particle Swarm Optimization[J]. Journal of Liaoning Petrochemical University, 2011, 31(2): 62-64.

刘国志,何鹏清. 基于改进微粒群优化的电力负荷生长曲线预测模型[J]. 辽宁石油化工大学学报, 2011, 31(2): 62-64.

Power Load Logistic Curve-Forecasting Model Based on Improved Particle Swarm Optimization

基于改进微粒群优化的电力负荷生长曲线预测模型

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