| 摘要: |
| 风电功率预测对于风电场制定电力调度计划和维修计划具有十分重要的意义,利用改进小波包处理混频信息的能力，将风电功率分解成多个频率的子序列；再利用遗传神经网络组合模型分别对各子序列进行预测，且利用改进小波包对各子序列预测结果进行了重构得到实际的预测值；最后以安徽省某地区风电场风功率数据为依据验证模型，由仿真结果分析可见组合算法取得了良好的预测效果。 |
| 关键词: 风电功率 改进小波包 组合预测 遗传算法 |
| DOI： |
| 分类号: |
| 基金项目: |
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| Short term Wind Power Forecasting Based on Improved Wavelet Packet Algorithm |
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LI Ling chun, GAO Lai xin, WANG Xian bing
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| Abstract: |
| Wind power prediction is crucial for wind power plan to plan power dispatch and maintenance. This paper decomposes wind power sequence a series of frequency subsequences, making use of the capability of the improved wavelet packet on processing mixing information, then forecasts each subsequence by the combination model of genetic algorithm neural network, and finally get the forecasting outputs by reconstructing the forecasting results with wavelet packet algorithm. A wind power plant in Anhui is chosen to validate the feasibility of the proposed model. The simulation results indicate that this combination algorithm achieves good forecasting effect. |
| Key words: wind power improved wavelet packet combination forecasting GA (genetic algorithm) |
