Optimal Operation and Valuation of Electricity Storages in Intraday Markets

TL;DR

This paper introduces a computational approach using convex stochastic optimization and indifference pricing to determine optimal operation and valuation of electricity storage systems in uncertain intraday markets.

Contribution

It applies the Stochastic Dual Dynamic Programming algorithm to model storage operations considering market uncertainties and user preferences, enabling fast, realistic strategy computation.

Findings

Strategies vary with risk preferences and battery characteristics

Valuations are consistent with market views and user risk appetite

Optimal strategies are computed within minutes on standard hardware

Abstract

This paper applies computational techniques of convex stochastic optimization to optimal operation and valuation of electricity storages in the face of uncertain electricity prices. Our valuations are based on the indifference pricing principle, which builds on optimal trading strategies and calibrates to the user's financial position, market views and risk preferences. The underlying optimization problem is solved with the Stochastic Dual Dynamic Programming algorithm which is applicable to various specifications of storages, and it allows for e.g. hard constraints on storage capacity and charging speed. We illustrate the approach in intraday trading where the agent charges or discharges a battery over a finite number of delivery periods, and the electricity prices are subject to bid-ask spreads and significant uncertainty. Optimal strategies are found in a matter of minutes on a regular PC. We find that the corresponding trading strategies and battery valuations vary consistently with respect to the agent's risk preferences as well as the physical characteristics of the battery.