Optimal strategies for operating energy storage in an arbitrage market

TL;DR

This paper develops a localized, efficient algorithm to determine profit-maximizing energy storage strategies in arbitrage markets, accounting for inefficiencies, constraints, and complex operational costs.

Contribution

It introduces a novel, localized algorithm for optimal energy storage operation considering various real-world constraints and cost functions.

Findings

Algorithm effectively determines optimal strategies in various scenarios.

Inclusion of operational constraints like minimum switching times.

Framework accommodates leakage and inefficiencies in storage models.

Abstract

We characterize profit-maximizing operating strategies, over some time horizon [0,T], for an energy store which is trading in an arbitrage market. Our theory allows for leakage, operating inefficiencies, operating constraints and general cost functions. In the special case where the operating cost of a store depends only on its instantaneous power output (or input), we present an algorithm to determine the optimal strategies. A key feature is that this algorithm is localized in time, in the sense that the action of the store at a time t only requires information about electricity prices over some subinterval of time [t,t_k] contained within [t,T]. To introduce more complex storage models, we discuss methods for an example which includes minimum switching times between modes of operation.