A novel metric for evaluating hydro-wind-solar energy complementarity

Accurately assessing complementarity is a foundational work to the hydro-wind-solar hybrid energy system planning and dispatching. However, the existing complementary assessment indexes such as Pearson, Kendall, Spearman coefficient, or other improved indexes, suffer from limitations such as being applicable only to two-dimensional objects, failing to simultaneously capture the fluctuating trend correlations thought the whole evaluation periods and the ramp correlations in the adjacent time periods, and ignoring the impact of the fluctuation amplitudes. To address these issues, we propose a novel complementary assessment metric based on vine structure and rank correlation analysis. Vine structure enables the inclusion of multidimensional assessment object and rank correlation analysis takes into account both the fluctuating trend correlations thought the whole evaluation periods and the ramp correlations in the adjacent time periods. Meanwhile, the introduction of the discount factor allows fluctuation amplitudes impact to be included in the evaluation system. Comparisons based on several typical scenarios verify that the proposed metric can reflect the complementarity between data series more accurately. Subsequently, taking a national-level hydro-wind-solar hybrid energy base in China as the case study, result shows: (1) hydro-wind-solar shows different complementarity at different time scales and significantly better on monthly scales than on annually, daily and hourly time scales; (2) the optimal ratio of wind-solar installed capacity is determined by combining multiple time scales based on the proposed metric.