# Chance-Constrained Ancillary Service Specification for Heterogeneous Storage Devices

## TL;DR

This paper introduces a chance-constrained optimization method for aggregators of heterogeneous energy storage devices to reliably specify their maximum supply-shortfall service capacity, improving computational efficiency and applicability.

## Contribution

The paper develops a novel chance-constrained approach for determining storage fleet capabilities, with an efficient approximation for flexible service application.

## Key findings

- Significant computational improvements over scenario simulation
- Effective handling of stochastic device availabilities
- Approximate method enables flexible service specification

## Abstract

We present a method to find the maximum magnitude of any supply-shortfall service that an aggregator of energy storage devices is able to sell to a grid operator. This is first demonstrated in deterministic settings, then applied to scenarios in which device availabilities are stochastic. In this case we implement chance constraints on the inability to deliver as promised. We show a significant computational improvement in using our method in place of straightforward scenario simulation. As an extension, we present an approximation to this method which allows the determined fleet capability to be applied to any chosen service, rather than having to re-solve the chance-constrained optimisation each time.