| 决策树和粒子群算法在日前电价预测中的应用 |
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| 引用本文： | 张红旭,姚建刚,杨洪. 决策树和粒子群算法在日前电价预测中的应用[J]. 电力系统及其自动化学报, 2009, 21(3) |
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| 作者姓名： | 张红旭 姚建刚 杨洪 |
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| 作者单位： | 湖南大学电气与信息工程学院,长沙,410082 |
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| 摘 要： | 由于日前24点电价特性差异较大,采用单一模型很难描述,提出了一种基于相似点的日前电价预测新方法.将数据空间按时点划分成子24个子空间,并定量考虑对电价造成影响的相关因素,利用改进决策树技术对子空间的历史数据进行自动聚类,再通过粒子群算法训练各相关因素的最优权值,大大增加了选择相似点的可信度,仿真结果表明该方法能有效提高预测精度.
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| 关 键 词： | 电力市场 电价预测 改进决策树技术 粒子群算法 |
Day-Ahead Electricity Price Forecasting Using Decision Tree and Particle Swarm Optimization |
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| ZHANG Hong-xu,YAO Jian-gang,YANG Hong. Day-Ahead Electricity Price Forecasting Using Decision Tree and Particle Swarm Optimization[J]. Proceedings of the CSU-EPSA, 2009, 21(3) |
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| Authors: | ZHANG Hong-xu YAO Jian-gang YANG Hong |
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| Affiliation: | College of Electrical and Information Engineering;Hunan University;Changsha 410082;China |
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| Abstract: | The features of electricity prices differ greatly in day-ahead 24 points in time,and it is hard to describe the features by a single model,so a new algorithm to forecast day-ahead electricity price is proposed.In accordance with points in time the data space is divided into 24 sub-spaces and the factors related to electricity price are quantitatively considered.The data in sub-space are automatically clustered by means of improved decision tree,and then the best connection weight of every factor is trained ... |
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| Keywords: | electricity market electricity price forecasting improved decision tree particle swarm optimization(PSO) |
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