东海大桥风电场短期风速序列特性及其预报
Characteristics and forecast of short-term wind speed series in the Donghai Bridge wind farm
查看参考文献21篇
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文摘
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风能作为一种重要的可再生能源能源,能够减少环境污染,缓解能源短缺.为减轻风电并网所带来的不利影响,降低供电系统的运行成本,精确的短期风速预报则显得十分必要.本文基于对东海大桥风电场实测数据的分析,指出其短期风速序列具有波动集群效应与非对称效应,而波动反馈效应并不显著.并进而从物理角度对产生这一现象可能的原因进行了详细阐述.此外,为选取适用于东海大桥风电场的预报模型,我们以平均绝对误差(MAE)、平均绝对百分误差(MAPE)以及均方根误差(RMSE)这三个误差指标作为判别标准,定量对比了五个模型的预报精度.结果表明,无论是单步预报还是多步预报,ARMA-EGARCH模型与ARMA-EGARCH-M模型的预报能力十分接近,均优于其他模型,且这两个模型随着提前预报步数的增加,误差增长率较低. |
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其他语种文摘
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As a sort of worldwide renewable energy, wind energy can reduce environmental pollution and relieve the energy shortage. In order to reduce the adverse effect with the integration of wind energy into electricity grids and the operating cost of power supply system, it is becoming increasingly significant to acquire accurate short-term wind speed forecasts. In this paper, based on the analysis of the measured wind speed data in the Donghai Bridge wind farm, we suggest that the short-term wind speed series has volatility clustering effect and asymmetric effect, and the volatility feed-back effect is not significant. And then the possible causes for this phenomenon are elucidated in detail from the viewpoint of physics. In addition, in order to select the forecast model which is appropriate to the Donghai Bridge wind farm, we use these indexes of error: mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) as the criterion, and compare the prediction accuracy of the five models by quantitative analysis. The results show that ARMA-EGARCH model and ARMA-EGARCH-M model are very close to each other in both single-step and multi-step forecasting, and they are superior to other models. What’s more, with the increase of the number of advance forecasting steps, error growth rate of these two models is low. |
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来源
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中国科学. 物理学
, 力学, 天文学,2016,46(12):124713-1-124713-10 【核心库】
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DOI
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10.1360/SSPMA2016-00407
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关键词
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海上风电场
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短期风速预报
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时间序列分析
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波动集群效应
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波动反馈效应
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非对称效应
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地址
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中国科学院力学研究所, 中国科学院流固耦合系统力学重点实验室, 北京, 100190
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1674-7275 |
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学科
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能源与动力工程;电工技术 |
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基金
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国家自然科学基金
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国家自然科学基金国家杰出青年科学基金
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文献收藏号
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CSCD:5857923
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