Chance-Constrained Equilibrium in Electricity Markets With Asymmetric Forecasts

TL;DR

This paper introduces a stochastic equilibrium model for electricity markets with asymmetric renewable forecasts, demonstrating how information asymmetry affects market outcomes and convergence to ideal equilibria.

Contribution

It develops a chance-constrained equilibrium framework incorporating private and public information, analyzing the impact of information asymmetry on market convergence.

Findings

More information leads to convergence to perfect equilibrium.

Market converges under information scarcity if participants infer or share private forecasts.

Private information sample size influences equilibrium outcomes.

Abstract

We develop a stochastic equilibrium model for an electricity market with asymmetric renewable energy forecasts. In our setting, market participants optimize their profits using public information about a conditional expectation of energy production but use private information about the forecast error distribution. This information is given in the form of samples and incorporated into profit-maximizing optimizations of market participants through chance constraints. We model information asymmetry by varying the sample size of participants' private information. We show that with more information available, the equilibrium gradually converges to the ideal solution provided by the perfect information scenario. Under information scarcity, however, we show that the market converges to the ideal equilibrium if participants are to infer the forecast error distribution from the statistical properties of the data at hand or share their private forecasts.