Metrics and indices used for the evaluation of energetic complementarity—a review

Quantification, the human practice of assigning numerical values to something, allows us to produce standardized measurements that enable mathematical calculations and assessments based on statistics and hypothesis testing. In the research field of energetic complementarity, metrics and indices allow readers to get a preliminary understanding of the relationship between variables or serve as a base for comparing different data series of one or more renewable sources or regimes at various locations and at different timescales. This chapter provides an overview and formulation of the main metrics and indices employed in the literature for conducting energetic complementarity studies. The reviewed studies show that correlation coefficients (especially Pearson's, Spearman's, and Kendall's) are the most common metric in these studies, mostly because they'd indicate if two time-series exhibit similarity or complementarity characteristics at different timescales. Moreover, as the comprehension of this subject has increased, researchers have employed or proposed other metrics and indices to evaluate additional complementarity features, such as the reliability of generation or the aggregated behavior of more than two variable renewable sources.