Phasing out support schemes for renewables in neighbouring countries: An agent-based model with investment preferences.

[Display omitted] • We simulate renewables pathways under different support phase-out scenarios. • We extend an investment algorithm by preferences and calibrated returns. • Our improved algorithm incorporates more heterogeneity resulting in stronger effects. • Further auction support is necessary for most capacity targets in the case countries. • Countries should coordinate policy changes due to cross-border effects. Support schemes have been central to the expansion of renewable electricity globally and in the European Union. As technologies mature, individual member states may decide to phase out these policies. While previous research has shown that such policy changes affect investors' decisions, we investigate how they affect pathways and electricity prices by simulating investment decisions in an agent-based model in two case countries. This paper contributes and applies an adapted investment decision algorithm that incorporates empirically observed technology and return preferences and is calibrated by return observations. The new algorithm yields more refined and stronger effects compared to its predecessor. Results show that the phase-out of auctions in Germany and the Netherlands slows down their deployment of renewable capacity by up to ∼60% and ∼35%, respectively. With the exception of photovoltaics and onshore wind projects in the Netherlands, the targeted capacities can only be reached by continuing support in both countries. Furthermore, ending support in a large country like Germany leads to higher electricity prices and fosters a market-driven but insufficient capacity expansion in smaller neighbours like the Netherlands. As the electricity grids in many countries are strongly interconnected, such cross-border effects are of international relevance. Our findings suggest that continued auctions may be necessary and that countries should coordinate policy changes to stay on track for meeting their renewables targets. [ABSTRACT FROM AUTHOR]