Exploring the Mechanics of Hybrid Markets in a Context of Deep Decarbonization

Overview The power sector has a key role to play through electrification and deep decarbonization to combat climate change (IEA, 2021). However, its institutional model inherited from the liberalization era is the subject of much debate, especially regarding its ability to deliver long-run efficiency (i.e., trigger optimal investment and retirement decisions). The idea that market design should evolve towards hybrid markets is gaining momentum, in particular regarding the massive investments needed for the energy transition (Keppler, Quemin, & Saguan, 2022). The key concept of these hybrid markets is to complement short-term markets with an adequate long-term framework for investments. The recent European energy crisis, although caused by exceptional factors, also highlighted the shortterm bias of the current model and invited economists to find ways of completing power markets (Schittekatte & Batlle, 2023). The process of defining how a hybrid market should be implemented is only being initiated, however, and market designers have many dimensions and possible options to explore (e.g., centralized procurement vs. decentralized obligations, scope and type of planning, contract design, etc.). Finding desirable and workable designs requires an impact assessment of design elements, notably in terms of dynamic performances (in the pluriannual sense) and considering realistic economic behaviors. As a contribution to this endeavor, this paper analyzes one possible hybrid design option relying on long-term contracts and phase-out compensation through a quantitative exercise based on optimization and dynamic simulations. Methods Our model combines market simulations and optimization. We use the modeling framework developed in (Lebeau, Petitet, Saguan, & Quemin, 2021) with new developments aiming at complementing the core Energy-Only Market model with long-term auction modules for CfD and closure compensations, consistently with the hybrid approach. In the market simulation model, the state variables of the system are chronologically computed based on decisionmaking and operating rules governing the different components in the system, i.e., representing the behavior of various economic agents (e.g. investors, regulatory agency) possibly in a non-idealistic manner (e.g., risk aversion, bounded rationality). The outcome of this model is assessed against an optimal development plan from the optimization module. The latter is also used to provide information in the simulation when assuming optimal anticipations. Results We build a stylized case study with fundamentals from California. Preliminary findings from simulations are threefold. First, the quantity-based long-term contracts allocation process yields capacity trajectories that are in line with policy objectives, even in presence of risk aversion. Second, the strike price formation of a CfD is characterized depending on the shape (e.g., "yardstick" à la (Newbery, 2021) or baseload) and duration of the contract (lifespan of the asset or less), as well as regarding behavioral aspects such as risk aversion. Third, implementing this market design requires the definition of a financial mechanism to balance the costs or proceeds of the contracts with final consumers. This architecture provides new levers on end-users pricing and raises question regarding the treatment of the existing fleet. Conclusion This paper investigates the functioning of one possible market design falling in the hybrid category. Working with simulations has the particular advantage of requiring a high degree of explicit assumptions, which invites us to question how the market design could actually materialize besides general guidelines.