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| 短期风电功率预测方法 | |
| 引用本文： | 李俊豪,李玲玲,王成山. 短期风电功率预测方法[J]. 低压电器, 2013, 0(5): 29-32,53 |
| 作者姓名： | 李俊豪 李玲玲 王成山 |
| 作者单位： | 1. 河北工业大学电磁场与电器可靠性省部共建重点实验室,天津,300130 2. 河北工业大学电磁场与电器可靠性省部共建重点实验室,天津300130;天津大学电气与自动化工程学院,天津300072 3. 天津大学电气与自动化工程学院,天津,300072 |
| 基金项目： | 河北省建设科技研究计划项目，河北省科技支撑计划项目 |
| 摘 要： | 提出了以混沌相空间重构为基础的混沌时间序列预测方法。为提高预测模型的预测精度和泛化能力，利用C-C方法对相空间重构参数的优化进行了综合计算。预测模型采用加权一阶局域法，以某风电场的风电功率数据进行训练和预测。实际算例表明，该综合方法具有很好的预测精度和实用性。 |
| 关 键 词： | 风电 相空间重构 C-C方法 一阶局域法 功率预测 |
Short-Term Wind Power Prediction Method |
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| LI Junhao , LI Lingling , WANG Chengshan. Short-Term Wind Power Prediction Method[J]. Low Voltage Apparatus, 2013, 0(5): 29-32,53 | |
| Authors: | LI Junhao LI Lingling WANG Chengshan |
| Affiliation: | 1. Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology,Tianjin 300130, China; 2. School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China) |
| Abstract: | Integration of large-scale wind-farm in power grid will impact grid planning, construction, operation and energy quality. Wind power prediction can help reduce the quantity of spinning reserve and improve the reliability of grid operation. This paper proposed a method of chaotic time series prediction based on chaotic theory. Optimal parameters for phase space reconstruction were integrated and computed to improve the model prediction performance. The forecasting model used weighted one-order local model. The data from a wind farm of Neimenggu province were used to test the approach. The case study results verify that the method can effectively improve the wind power prediction accuracy. |
| Keywords: | wind power phase space reconstruction C-C method one order local method power prediction |
| 本文献已被 维普 万方数据 等数据库收录！ | |