Skip to main navigation Skip to search Skip to main content

Analysing the potential of integrating wind and solar power in Europe using spatial optimisation under various scenarios

  • William Zappa*
  • , Machteld van den Broek
  • *Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

The integration of more variable renewable energy sources (vRES) like wind and solar photovoltaics (PV) is expected to play a significant role in reducing carbon dioxide emissions from the power sector. However, unlike conventional thermal generators, the generation patterns of vRES are spatially dependent, and the spatial distributions of wind and PV capacity can help or hinder their integration into the power system. After reviewing existing approaches for spatially distributing vRES, we present a new method to optimise the mix and spatial distribution of wind and PV capacity in Europe based on minimising residual demand. We test the potential of this method by modelling several scenarios exploring the effects of vRES penetration, alternative demand profiles, access to wind sites located far offshore, and alternative PV configurations. Assuming a copper-plate Europe without storage, we find an optimum vRES penetration rate of 82% from minimising residual demand, with an optimum capacity mix of 74% wind and 26% PV. We find that expanding offshore wind capacity in the North Sea is a ‘no regret’ option, though correlated generation patterns with onshore wind farms in neighbouring countries at high vRES penetration rates may lead to significant surplus generation. The presented method can be used to build detailed vRES spatial distributions and generation profiles for power system modelling studies, incorporating different optimisation objectives, spatial and technological constraints. However, even under the ideal case of a copper-plate Europe, we find that neither peak residual demand nor total residual demand can be significantly reduced through the spatial optimisation of vRES.

Original languageEnglish
Pages (from-to)1192-1216
Number of pages25
JournalRenewable and Sustainable Energy Reviews
Volume94
DOIs
Publication statusPublished - 2018

Funding

The authors would like to thank Gerard Sleijpen from the Mathematical Institute at Utrecht University for his expertise, and the JRC for providing access to their EV charging profile database. The CDDA data used in this paper included copyrighted data from the Estonian Environmental Register (02/03/2015) and Finnish Environment Institute (2015). Load data was provided by ENTSO-E. The UK building footprint data contained OS data © Crown copyright and database right 2016. This research did not receive any funding from agencies in the public, commercial, or not-for-profit sectors. Appendix A

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Optimisation
  • Power system
  • Solar photovoltaic
  • Spatial distribution
  • Variable renewable energy
  • Wind power

Fingerprint

Dive into the research topics of 'Analysing the potential of integrating wind and solar power in Europe using spatial optimisation under various scenarios'. Together they form a unique fingerprint.

Cite this