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| 2种风电功率预测模型的比较 | |
| 引用本文： | 时庆华,高山,陈昊.2种风电功率预测模型的比较[J].电力技术经济,2011,23(6):31-35. |
| 作者姓名： | 时庆华 高山 陈昊 |
| 作者单位： | 1. 山东省电力公司日照莒县供电公司,山东日照,276500 2. 东南大学,江苏南京,210096 3. 东南大学,江苏南京210096;南京供电公司,江苏南京210008 |
| 摘 要： | 采用ARMA模型对风电功率进行了预测，并由ARMA方程推导出卡尔曼滤波状态方程和测量方程，从而将预测问题转化到状态空间，并利用卡尔曼滤波法预测了风电功率，比较了2种方法的预测效果。实例表明，卡尔曼滤波法能够提高风电功率的预测精度，并在一定程度上解决了时间序列分析法的预测时延问题，对电力系统的安全、稳定、经济运行以及提高运行效益具有重要意义。 |
| 关 键 词： | 风力发电 功率预测 ARMA 卡尔曼滤波 |
Comparison Study on Two Wind Power Forecasting Models |
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| SHI Qinghua , GAO Shan , CHEN Hao.Comparison Study on Two Wind Power Forecasting Models[J].Electric Power Technologic Economics,2011,23(6):31-35. | |
| Authors: | SHI Qinghua GAO Shan CHEN Hao |
| Affiliation: | SHI Qinghua1,GAO Shan2,CHEN Hao2,3(1.Rizhao Juxian Power Supply Company,Shandong Electric Power Corporation,Rizhao 276500,China,2.Southeast University,Nanjing 210096,3.Jiangsu Nanjing Power Supply Company,Nanjing 210008,China) |
| Abstract: | Wind power forecasting is very important to wind farm planning and stable operation of the power system.In this paper,wind power is firstly estimated by means of the ARMA(Autoregressive Moving Average) model as built,and then the Kalman filter state equation and measurement equation are derived from the ARMA model to transform the forecast into state space,and finally wind power is forecasted with the Kalman filter method.A comparison on the forecasting performance between the ARMA model and the Kalman filt... |
| Keywords: | wind power power forecast ARMA Kalman filter |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
