Assessing temporal complementarity between three variable energy sources through correlation and compromise programming

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. Nevertheless, the weather-dependent nature and variability of renewable energy sources often hinders their integration to national grids. The combination of different sources to profit from their beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity, as well as allowing for a linear assessment of complementarity. The method is employed to study the complementarity of wind, solar and hydropower generation on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the estimated value of the total temporal complementarity index. (C) 2019 Elsevier Ltd. All rights reserved.