Price formation without fuel costs: the interaction of demand elasticity with storage bidding

TL;DR

This paper demonstrates that incorporating demand elasticity into electricity market models stabilizes prices and addresses issues like zero-price periods and price volatility, challenging the belief that energy-only markets cannot function with high renewable shares.

Contribution

It introduces a demand elasticity-based approach to improve the stability of energy-only markets and provides simple storage bidding strategies validated with long-term weather data.

Findings

Demand elasticity reduces zero-price hours from 90% to 30%

Price stability improves with demand elasticity despite capacity perturbations

Short-term bidding strategies derived from long-term models perform well on unseen data

Abstract

Studies looking at electricity market designs for very high shares of wind and solar often conclude that the energy-only market will break down. Without fuel costs, it is said that there is nothing to set prices. Symptoms of breakdown include long phases of zero prices, scarcity prices too high to be politically acceptable, prices that collapse under small perturbations of capacities from the long-term equilibrium, cost recovery that is impossible due to low market values, high variability of revenue between different weather years, and difficulty operating long-term storage with limited foresight. We argue that all these problems are an artefact of modelling with perfectly inelastic demand. If short-term elasticity to reflect today's flexible demand (-5%) is implemented, these problems are reduced. The interaction of demand willingness to pay and storage opportunity costs is enough to produce stable pricing. This behavior is illustrated by a model with wind, solar, batteries, and hydrogen-based storage, where the price duration curve is smoothed with a piecewise linear demand curve. This removes high price peaks, reduces the fraction of zero-price hours from 90% to around 30%, and guarantees more price stability for perturbations of capacity and different weather years. Furthermore, we show that with demand elasticity, the long-term optimisation model exactly reproduces the prices of the short-term model with the same capacities. We then use insights from the long-term model to derive simple bidding strategies for storage so that we can also run the short-term model with limited operational foresight. We demonstrate this short-term operation in a model optimised using 35 years of weather data and then tested on another 35 years of unseen data. We conclude that the energy-only market can still play a key role in coordinating dispatch and investment in the future.