Epsilon Archive for Student Projects

Abstract

Renewable energy auctions have become a prominent policy instrument in recent years. A central issue with these auctions is that a significant number of participating projects end up not being realized. This thesis proposes a novel subsidy structure, the Moving Average Feed-in Premia, aiming to reduce revenue uncertainty of renewable energy projects and improve auction realization rates. By tying the selling price of produced electricity to a moving average price instead of the more volatile spot price, revenue uncertainty is reduced without increasing policy costs in the long run.
This thesis adds to the literature by quantifying the impact revenue uncertainty has on renewable energy outcomes. It fills a clear research gap as no previous literature has studied electricity price uncertainty within the context of renewable energy auctions. Using real option theory, non-realization of auction-winning projects is rationalised, and the role of revenue uncertainty in auction outcomes is identified. The developed model is simulated using three real-world cases based on German and Italian auction data, comparing outcomes under standard feed-in premia and moving average feed-in premia. The findings suggest that reducing revenue volatility by tying the selling price to a moving average can significantly improve auction realization rates and lead to an overall reduction in project abandonment.