# Assessing temporal complementarity between three variable energy sources by means of correlation and compromise programming

## TL;DR

This paper introduces a new method combining correlation and compromise programming to quantify the temporal complementarity of wind, solar, and hydro energy sources, aiding renewable integration.

## Contribution

It presents a novel approach for assessing total and partial temporal energetic complementarity among three renewable sources using established mathematical techniques.

## Key findings

- Timescale selection significantly affects complementarity assessment.
- Method effectively captures partial and total complementarity.
- Application to Polish data demonstrates practical utility.

## Abstract

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. However, the weather-dependent nature of renewable energy sources often hinders their integration to national grids. Combining different sources to profit from 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. The method is employed to study the complementarity of wind, solar and hydro resources on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the total temporal complementarity.