An action-oriented, data science-driven approach to make the most of the wind and solar power complementarity

Solar and wind power play a main role in the transition toward decarbonized electricity systems, being at the core of climate change mitigation strategies. However, their integration in the energy mix is highly compromised due to the intermittency of their production, at the expense of weather and climate variability. To face the challenge, here we present research about actionable strategies for wind and solar photovoltaic facilities deployment that exploit their complementarity in order to reduce the volatility of their combined production at its minimum. The developed methodology is based on data science techniques and has been implemented in an open-access step-wise model called CLIMAX. It first clusters regions with homogeneous temporal variability of the resources (from long, gridded climate datasets), and then determines the optimal shares of each technology over such regions under a variety of customizable restrictions and conditions. In a simplistic application of the model, aimed at illustrating its performance, we set the goal of narrowing the monthly deviations of the total wind-plus-solar electricity production from a given curve (here, the mean annual cycle of the total production) across five European regions. The results showed that the optimal siting of the power units identified by CLIMAX reduces the standard deviation of the monthly anomalies of the total wind-plus-solar power generation by up to 20% without loss in the mean capacity factor as compared to a base scenario with an evenly spatial distribution of the installations, in both cases considering current shares of each technology. This reduction further improves (up to 60% in specific regions) if the total shares of each technology also participates in the optimization game. Therefore, despite the experimental and pilot nature of this CLIMAX application, these results prove the ability of CLIMAX to provide practical guidance to energy policy decision-makers for the design of the next-generation renewable energy scenarios.