Market Design Considerations for Scarcity Pricing: A Stochastic Equilibrium Framework

Abstract

Scarcity pricing is a mechanism for improving the valuation of reserve capacity in real-time electricity markets. The goal of scarcity pricing is to mitigate the missing money problem and enhance investment in flexible resources. The implementation of scarcity pricing is underway in a number of U.S. markets, including Texas and PJM. The implementation is also currently under consideration in Belgium. As the mechanism was originally conceived in the context of a U.S.-style two-settlement system, its implementation in a European setting poses a number of interesting market design dilemmas which can affect the back-propagation of scarcity prices to forward day-ahead markets for energy and reserve capacity. We propose a modeling framework for analyzing these market design choices based on stochastic equilibrium, and use this modeling framework in order to represent and analyze a wide range of market design proposals. We report results on a case study of the Belgian electricity market.

Calibration of Operating Reserve Demand Curves Using a System Operation Simulator

“…Although scarcity pricing is a real-time mechanism, the uplifted real-time energy and reserve prices are expected to back-propagate to forward (e.g. dayahead) energy and reserve markets, thereby generating robust investment signals in the market [4].…”

Market Design Options for Scarcity Pricing in European Balancing Markets

“…The settlement of BRP imbalances at an imbalance price that is different from the balancing price used for the settlement of BSP balancing energy deviates from the law of one price. In previous analysis [11], stochastic equilibrium has been used as our quantitative method of choice for representing the back-propagation effect quantitatively. The stochastic equilibrium framework that we have developed, which has originally been applied in the context of investment [12], [13], reveals the strengths and weaknesses of different market design choices in back-propagating the value of reserve to forward reserve auctions.…”

“…By comparison, the stochastic equilibrium approach [11] combines the advantages of analytical insights and numerical scalability in a single modeling framework. Concretely, the complementarity conditions of the stochastic equilibrium model provide generalizable conclusions about the effect of market design choices on the back-propagation of reserve prices (see, for instance, the discussion in page 21 of [11]). Assuming risk-neutral market agents, the stochastic equilibrium models of [11] can further be expressed as equivalent tractable two-stage stochastic programming optimization problems.…”

“…Concretely, the complementarity conditions of the stochastic equilibrium model provide generalizable conclusions about the effect of market design choices on the back-propagation of reserve prices (see, for instance, the discussion in page 21 of [11]). Assuming risk-neutral market agents, the stochastic equilibrium models of [11] can further be expressed as equivalent tractable two-stage stochastic programming optimization problems. However, it is not clear how the stochastic equilibrium framework can be adapted in order to account for how agents internalize opportunity costs in their bidding behavior, and for the fact that the EU market design allows BSPs and BRPs to trade at different settlement prices.…”

“…The scarcity pricing evolutions in the Belgian market have focused on the introduction of scarcity adders based on ORDC related to aFRR and mFRR. The separate consideration of aFRR and mFRR adders has been considered by the authors in previous work [7], [8], [1], [11], and is not developed further in the present paper in order to focus the analysis on the design of the balancing market.…”