学术论文

      基于相空间重构的风电功率波动特性分析及其对预测误差影响

      Volatility of Wind Power Sequence and Its Influence on Prediction Error Based on Phase Space Reconstruction

      摘要:
      精确的风电功率预测是保证含大规模风电电力系统安全稳定运行的重要基础.为提高风电功率预测精度,已开展了诸多研究,新的预测方法不断涌现.但任何方法都无法保证无差预报,究其原因,风电功率的预测精度不但和预测方法有关,还与风电功率波动特性有关.该文阐述了评价风电功率波动特性的必要性;在相空间重构基础上,利用递归图和递归率对风电功率时间序列波动特性分别进行了定性和定量的刻画,以表征风电功率波动新模态产生的机率;分析了不同空间尺度下递归率的变化规律,建立了分析风电功率时间序列波动特性与预测误差关系的方法,最后给出了利用递归率为风电场管理机构确定切实可行且公平的预测精度考核指标提供依据的方法.文章算例说明了方法的有效性.
      Abstract:
      The accurate prediction of wind power is important to guarantee the security and stability of any power system containing a large contribution from wind energy. To improve the accuracy of predictions of wind power generation, many new prediction methods have emerged. However, the accuracy of wind power prediction is not only related to the prediction methods, but also associated with the volatility of wind power. Regardless of the method adopted, it is not possible to guarantee accurate and error-free prediction. The necessity of the volatility in the wind power sequence was explained. To depict the probability of the occurrence of a new volatility mode, based on phase space reconstruction, a recurrence plot, and the recurrence rate was proposed to qualitatively and quantitatively depict the volatility. The changing rules of the recurrence plot and recurrence rate at different spatial scales were discussed. Based on this, a method to analyze the relationship between the volatility of a wind power sequence and prediction error was established. Finally a fair method for evaluating predictions accuracy was provided based on the recurrence rate. The study further illustrates the effectiveness of the method.
      作者: 杨茂 齐玥
      Author: YANG Mao QI Yue
      作者单位: 现代电力系统仿真控制与绿色电能新技术吉林省重点实验室(东北电力大学),吉林省吉林市,132012
      刊 名: 中国电机工程学报 ISTICEIPKU
      年,卷(期): 2015, 35(24)
      分类号: TM614
      在线出版日期: 2016年2月25日
      基金项目: 国家重点基础研究发展计划项目(973 计划),国家自然科学基金项目,吉林省产业技术与专项开发项目(2014Y124). The National Basic Research Program of China (973 Program),Project Supported by National Natural Science Foundation of China,Industrial Technology Research and Development for Special Project of Jilin Province