This paper introduces a novel algorithm to solve the generation expansion planning problem in interconnected electricity markets. Starting from an individual investor’s perspective, a stable Nash-equilibrium is determined by iteratively adjusting the investment decisions of all players. Both, generation technologies and storage units using arbitrage trading can be considered as investment options. The new method also allows for consideration of capacity remuneration mechanisms and technological learning.
In an illustrative case study, the developed algorithm is embedded into the agent-based simulation model PowerACE and applied to a multi-country long-term scenario analysis. Results show high investment incentives in countries using a capacity remuneration mechanism as well as related cross-border effects in other countries that rely on an energy-only market design. These findings confirm the suitability of the methodology for long-term analyses of interconnected electricity markets.