The global transition toward low-carbon energy systems has become an urgent objective, prompting major economies to implement a range of support schemes aimed at accelerating decarbonization. However, the evolving characteristics of low-carbon energy ...
The global transition toward low-carbon energy systems has become an urgent objective, prompting major economies to implement a range of support schemes aimed at accelerating decarbonization. However, the evolving characteristics of low-carbon energy markets have exposed fundamental limitations in these conventional mechanisms. In particular, today’s markets are defined by a diverse mix of emerging energy sources, increased decentralization of participation, and heightened volatility in generation costs, which exacerbate both information asymmetry and market uncertainty. Furthermore, these environments are populated by strategic agents who make decisions to maximize their payoffs based on expectations about others’ actions and private information. In such settings, asymmetries in information or uncertainty can lead to significant deviations from efficient outcomes, as agents strategically misreport information or adjust their behavior to gain a competitive advantage. As a result, there is a growing need for efficient market designs that explicitly account for these informational and structural complexities.
This dissertation addresses these challenges by proposing novel market designs using mechanism design theory for two representative low-carbon energy sectors: peer-to-peer (P2P) energy trading platforms and clean hydrogen power procurement markets. Both settings are characterized by different forms of features: P2P markets involve decentralized and two-sided interactions with bilateral trading, while hydrogen procurement markets face severe cost uncertainty and technological immaturity.
Initially, we develop a double auction mechanism for P2P energy trading that explicitly incorporates power losses and transaction costs. P2P trading enables energy prosumers, such as households or EV users, to directly exchange surplus electricity, bypassing the centralized grid and potentially achieving better economic outcomes. The proposed mechanism accounts for heterogeneous power losses and transaction costs, which vary depending on the trading pair. The auction efficiently determines buyer-seller matching, allocates traded quantities, and sets trading prices, while satisfying desirable properties of direct mechanisms. This design offers an efficient and fair allocation rule for decentralized trading environments.
Then, we develop multi-attribute auction mechanisms for South Korea’s hydrogen power procurement market. In this market, the government incentivizes private generation companies (Gencos) to invest in hydrogen-based power generation by purchasing electricity through competitive bidding and offering long-term stable revenue. We derive an efficient procurement auction mechanism under information asymmetry, enabling the buyer to evaluate both price and non-price attributes of sellers. Accordingly, we characterize sellers' equilibrium bidding strategies, establishing the existence of weakly dominant strategies in this multi-attribute environment.
Finally, building on the procurement auction mechanism, we extend the model to account for market uncertainty by interpreting awarded contracts as real options. In this framework, bidders face uncertain future generation costs and are granted the option to abandon the contract with a penalty. We develop a modified multi-attribute auction mechanism that incorporates this managerial flexibility and allows bidders to submit non-price attributes contingent on future cost realizations. By integrating auction theory with real options analysis, we characterize the equilibrium bidding strategies in this setting. Our approach enables the derivation of equilibrium bidding strategies under both information asymmetry and cost uncertainty, highlighting the strategic value of flexibility.
Overall, the dissertation contributes to both the theory and practice of market design by addressing both structural complexities and informational asymmetries in emerging low-carbon energy markets. It offers new insights for policymakers aiming to develop efficient and adaptive market-based incentive mechanisms that support long-term goals of decarbonization and energy transition. Moreover, this work provides valuable tools for industry practitioners seeking to make optimal investment decisions in auction markets under uncertainty.