Incumbent’s Bane or Gain? Renewable Support and Strategic Behavior in Electricity Markets

Abstract

Incumbent firms play a decisive role in the success of renewable support policies. Their investments in renewables as well as their operational strategies for their conventional CO 2 emitting technologies affect the transition to a sustainable energy system. We use a game theoretical framework to analyze incumbents' reactions to different renewable support policies, namely feed-in tariff (FIT), feed-in premium (FIP), and auction-based policies. We show that a regulator should choose a support scheme based on concerns about either market power or emission abatement: in FIP-based policies, the incumbent's strategic behavior leads to lower CO 2 emissions, but a higher market price compared to FIT-based policies. Furthermore, for FIP-based policies, the regulator might want to incentivize incumbents directly (to further reduce CO 2 emissions) or newcomers (to further reduce market power). Particularly in FIP-based auctions, incumbents have the incentive to obtain all auctioned capacity, which could lead to an unchanged market price despite the entrance of new capacity into the market.

Auctions for Renewables: Does the Choice of the Remuneration Scheme Matter?

“…However, limited attention has been paid to the effect of the remuneration method in the context of RES auction design. Darudi & Weigt (2020) demonstrate that a strategic incumbent has an advantage over newcomers in auctions with FIP remuneration. Brown & Eckert (2020) analyzed the investment incentives of two incumbents and a price-taking fringe in FIT and FIP auctions followed by spot and forward markets.…”

“…The RES auctions' design should conform to the characteristics of the target electricity market, particularly the degree of competitiveness (Darudi and Weigt 2020). Some electricity markets are susceptible to the exercise of market power due to the dominance of a few incumbents.…”

“…The proposed method takes a substantially different approach compared to the literature as, unlike typical numerical simulation methods (e.g., Bahn et al (2021), Bushnell et al (2008), and Genc & Reynolds (2019), it does not directly solve the incumbent's optimization problems; instead, it relies on a model of its optimal behavior that is fit using its observed behavior in a market. The method's reliance on hourly data is also in direct contrast with those of Brown & Eckert (2020) and Darudi & Weigt (2020), which provided numerical analyses based only on annual market representations.…”

Introduction to the Special Issue on “Competition in the Electricity Sector”

“…Counterfactual analysis tools are employed to illustrate that the provision of hourly trading reports facilitate learning and allowed for an increased exercise of market power. • Darudi and Weigt (2020) develop a game theoretical framework to examine how different renewable support policies, including feed in tariff's and feed in premium's, can impact strategic actions of incumbent firms. Among other things, their paper documents how regulators choices over renewable policy support may align with a tradeoff balancing market power considerations against emission abatement.…”