Review of mapping analysis and complementarity between solar and wind energy sources

This review aims to identify the available methodologies, data, and techniques for mapping the potential of solar and wind energy and its complementarity and to provide significant research and patents regarding these issues. The review shows that the mapping methodologies vary in space and time, going from a global scale to a microscale. Studies use observed data, such as land-based monitoring stations, upper-air stations, wind towers, and satellite data. Additionally, they use meteorological modeling, such as analysis and reanalysis from global models, and mesoscale and microscale models. The complementarity analysis uses mainly correlation techniques such as Pearson's, Spearman, or Kendall's correlation. However, some studies pointed out that these techniques are unsuitable for analyzing wind and solar time series. This brings additional research and methods to assess and evaluate the complementarity between energy sources, reinforcing that there is no standard or common methodology to perform complementarity analyses. The patent survey has shown that most patents are regarding power plant components, configuration, energy storage in hybrid systems, computational fluid dynamics, and artificial intelligence techniques for improving power plant operation. A case study was established to illustrate the methodology of mapping the solar and wind potential and their complementarity.