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Quasi-Stochastic Electricity Markets

Jacob Mays (jacobmays***at***cornell.edu)

Abstract: With wind and solar becoming major contributors to electricity production in many systems, wholesale market operators have become increasingly aware of the need to address uncertainty when forming prices. While implementing theoretically ideal stochastic market clearing to address uncertainty may be impossible, the use of operating reserve demand curves allows market designers to inject an element of stochasticity into deterministic market clearing formulations. The construction of these curves, which alter the procurement of reserves and therefore the pricing of both reserves and energy, relies on contentious administrative parameters that lack strong theoretical justification. This paper proposes instead to link their construction to outcomes that would be expected in efficient stochastic markets. The analysis considers the potential of these "quasi-stochastic" market clearing approaches to improve efficiency relative to the deterministic status quo, as well as ways in which they are unable to fully replicate the stochastic ideal. Further, the paper argues that efficiently managing uncertainty entails a reexamination of the discriminatory uplift payments and enhanced pricing schemes currently employed to address non-convexity.

Keywords: Electricity market design, operating reserves, stochastic competitive equilibrium

Category 1: Applications -- OR and Management Sciences

Citation: Working Paper, School of Civil and Environmental Engineering, Cornell University

Download: [PDF]

Entry Submitted: 10/08/2019
Entry Accepted: 10/08/2019
Entry Last Modified: 01/28/2021

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