Location optimization of wind and solar power plants in Northwest Europe

Abstract

In light of climate change mitigation, the European Union and its member states aim to increase their share of renewable energy in the energy system. Some of these resources, such as wind turbines and solar PV panels produce Variable Renewable Electricity (VRE). Due to its intermittent nature VRE can pose a problem to this system. Numerous research has looked into addressing the variability by strategically placing VRE technologies in a large geographical area so that their variance is decreased or their correlation with the electricity demand is increased. This thesis uses portfolio theory to further investigate how VRE technologies can better be integrated in the electricity system by maximizing the covariance between VRE production and electricity demand. Northwest Europe is chosen as a case study area and the temporal scope was set at 2030. In addition, Demand Response (DR) is added to the optimization to further investigate maximizing this covariance. An unconstrained, constrained and constrained DR scenario are created. The results show that the unconstrained scenario exhibit the highest covariance across all scenarios and the maximum covariance portfolio of this scenario has an increase of 55 % compared to the maximum return portfolio. However, the variance of the unconstrained scenarios is also higher. The correlation coefficient between VRE production and demand is also calculated. By using DR, a maximum correlation of 0.29 is attained. This demonstrates that while the unconstrained covariance analysis yields the highest return and covariance, the constrained scenarios exhibits lower variance and higher correlation. The results indicate that maximizing the covariance might not be the best optimization technique to determine the most optimal integration of VRE technologies in the energy system as maximizing correlation or minimizing variance is potentially better. Nevertheless, DR contributes to both maximizing the covariance and correlation. Furthermore, the results show that attention should be given to what extend and where VRE assets should be installed from an energy system point of view, because they can alter the variance of production, production itself, as well as the covariance and correlation between production and demand.