Research on the errors of MCP in predicting wind speed and power generation in decentralized wind power
WANG Bin
Abstract：At present,measurement correlation prediction(MCP)method is widely used to obtain complete wind measurement data,but in the actual wind resource evaluation business of decentralized projects,it is difficult to find out the reliability of various MCP methods.More than 400 samples were randomly selected,and the effect of different synchronization durations,the correlation between different target stations and reference stations on the error of the MCP method were analyzed for the annual average wind speed and annual power generation,and the errors of six MCP methods were quantitatively given.The results show that LLS,VS and BSR algorithms perform better in the prediction of annual average wind speed,while WBL,VR,BSR and SS algorithms perform better in the prediction of annual power generation.BSR algorithm can both work well in the prediction of annual average wind speed and power generation.
Keywords：wind powerdecentralized projectsmeasure-correlate-predictannual average wind speed errorannual power generation error
Publication Date：2023-11-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 67-70 )