Photovoltaic Super-Short Term Power Prediction Based On BP-ANN Generalization Neural Network Technology Research

摘要：

　　The research is mainly based on BP-ANN neural network method,through direct and indirect data collection to predict the photovoltaic super-short term power generation,discussed the influence and effection about the generalization of the BP-ANN neural network model,which is to predict the photovoltaic super-short term power generation.Combined with the actual operation situation,analyzed and compared the system operation results.The actual results show that data has the same trend with the super-short term prediction results,the root mean square error and mean absolute error are small,the prediction accuracy reached 96.71% and has high application value.

关键词： Photovoltaic power generation Photovoltaic power prediction method BP-ANN neural networks Photovoltaic power prediction model

作者: Shang Xinxin Chen Qijuan Han Zifen Qian Xiaodong

作者单位: School ofPower & Mechanical Engineering of Wuhan University, Hubei, China, 430072 School ofPower & Mechanical Engineering of Wuhan University, Hubei, China, 430072 ;Power Company dis NARI Group Corporation, Nanjing, China 210061

会议类型: 国际会议

会议名称: 2013 3rd International Symposium on Chemical Engineering and Material Properties(2013第三届化学工程和材料性能国际研讨会)(ISCEMP 2013)

会议地点: 三亚

会议语种:英文

页码: 194-197

在线出版日期: 2013-06-22（万方平台首次上网日期，不代表论文的发表时间）