Evaluation of MCP Correlation Algorithms Applied to Wind Data Series

Authors

  • A. Moreira MEGAJOULE S.A. Rua do Divino Salvador de Moreira, 255; 4470-105 Maia (Portugal) Author
  • T. Rocha INESC TEC, Centre for Power and Energy Systems Rua Dr. Roberto Frias, 4200-465 Porto (Portugal) Author
  • J. Mendonça SIIS, Instituto Politécnico do Porto, R. Dr. Roberto Frias, 4200-465 Porto (Portugal) Author
  • R. Pilão CIETI, Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 341; 4200-072 Porto (Portugal) Author
  • P. Pinto MEGAJOULE S.A. Rua do Divino Salvador de Moreira, 255; 4470-105 Maia (Portugal) Author

DOI:

https://doi.org/10.52152/4060

Keywords:

MCP, correlation algorithms, local measurement station, wind regime, reanalysis data series

Abstract

This work aimed to develop methodologies for analysing statistical correlations among wind data series using various Measure-Correlate-Predict (MCP) methods, with the goal of selecting the most suitable method for extrapolating long-term data with minimal associated uncertainty. It was analysed the minimum time required for a wind measurement campaign when applying this methodology. Fifteen local wind measurement stations were selected. The long-term wind data reanalysis series that exhibited the strongest correlation with the measured wind data at each station was then chosen. Multiple tests were conducted with different simultaneous periods between the measured data series and the long-term series. Fifteen correlation algorithms were tested for each concurrent period. The performance of each model was evaluated using the RMSE (Root Mean Square Error) and MBE (Mean Bias Error) associated with each MCP. Analysis of the errors identified measurement periods with the lowest associated error ranging from 1 to 5 years and a single-factor ANOVA analysis was conducted. Finally, t-significance tests were performed. The study concluded that the Neural Network was the most effective MCP method. Additionally, it was determined that the minimum number of years required for a local measurement campaign should be between 2 and 3 years.

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Published

2024-08-12

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Articles