Research on Power Prediction of Runoff Small Hydropower Cluster Based on Fusion Modeling. Issue 1 (1st December 2022)

• Record Type: Journal Article
• Authors: Zhang, Feng; Zhang, Yi; Qiu, Yutao; Wu, Xiaogang; Tao, Yufeng; Ji, Qingfeng; Xie, Xiahui
• Is Part Of: Journal of physics. Volume 2409 Issue 1(2022)
• Publication Date: 2022-12-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2409/1/012011
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The characteristics of the runoff hydropower station are to generate power completely according to the natural runoff, and the output and power generation change with the change of the natural flow. The cluster power prediction of the runoff hydropower station is conducive to improving the safety of the power grid operation and improving the utilization rate of hydropower. This paper analyzes the operation characteristics of runoff hydropower stations, summarizes the prediction direction of mainstream runoff hydropower, analyzes the characteristics of the hydrological prediction model represented by the Xin'an River model, and puts forward a study on the power prediction technology of runoff small hydropower cluster based on fusion modeling. Based on the detailed analysis of watershed runoff characteristics, a prediction model based on multi-watershed observation characteristics is proposed, which combines the traditional hydrological model with the LSTM model to form a combined prediction model suitable for runoff hydropower. The method is universal and innovative.