摘要
随着风电渗透率的持续增长,风电功率预测的研究和应用变得非常重要,它将提高电网的安全性、稳定性和接纳能力。文中分别对基于风速预测和基于功率预测的两种风功率预测方法进行了分析,并建立了自适应神经模糊推理系统(adaptive neuro-fuzzy inference system,ANFIS)预测模型。利用吉林省西部某风电场的实测数据,基于ANFIS预测模型采用两种预测方法进行实时多步滚动预测,并与基于线性回归法、滑动平均法和持续法的风电功率实时多步滚动预测得到的预测结果进行比较,结果表明前者的预测精度更高,说明了ANFIS预测模型的有效性,并发现基于功率预测的ANFIS预测方法的精度要高于基于风速预测的ANFIS预测方法。
With the continuous growth of wind power penetration, the study and application of wind power predictionwhich could improve security, stability and receptiveness of the power grids is of great importance. This paper analy-zes two kinds of prediction methods： one is based on wind speed prediction; the other is based on wind power predic-tion. Then, the ANFIS （adaptive neuro-fuzzy inference system） prediction model is established. Taking the real datafrom a wind farm in the west of Jilin province to do the real-time multi-step rolling wind power prediction under twokinds of methods based on ANFIS, and the results of it are compared with the results of the linear regression method,the moving average method and the persistence method. It is shown that the prediction accuracy of the ANFIS methodis higher and the effectiveness of ANFIS method can be proved. Furthermore, it also illustrates that the prediction ac-curacy of ANFIS method based on wind power prediction is better than ANFIS method based on wind speed predic-tion.
出处
《电测与仪表》
北大核心
2016年第19期22-26,共5页
Electrical Measurement & Instrumentation
基金
国家重点基础研究发展计划项目(973计划)(2013CB228201)
国家自然科学基金资助项目(51307017)
吉林省产业技术研究与开发项目(2014Y124)
