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

期刊

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 94, 期 -, 页码 1192-1216

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2018.05.071

关键词

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

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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.

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