Risk Limiting Dispatch with Fast Ramping Storage

TL;DR

This paper extends Risk Limiting Dispatch to include fast-ramping storage, developing a threshold-based dispatch rule, analyzing storage benefits, and demonstrating improved system performance through numerical experiments.

Contribution

It introduces a closed-form threshold rule for stochastic dispatch with fast-ramping storage, enhancing the RLD framework's efficiency and reliability.

Findings

Storage improves prediction quality and dispatch efficiency.

The threshold rule effectively incorporates storage into dispatch decisions.

Numerical results validate the proposed methods.

Abstract

Risk Limiting Dispatch (RLD) was proposed recently as a mechanism that utilizes information and market recourse to reduce reserve capacity requirements, emissions and achieve other system operator objectives. It induces a set of simple dispatch rules that can be easily embedded into the existing dispatch systems to provide computationally efficient and reliable decisions. Storage is emerging as an alternative to mitigate the uncertainty in the grid. This paper extends the RLD framework to incorporate fast-ramping storage. It developed a closed form threshold rule for the optimal stochastic dispatch incorporating a sequence of markets and real-time information. An efficient algorithm to evaluate the thresholds is developed based on analysis of the optimal storage operation. Simple approximations that rely on continuous-time approximations of the solution for the discrete time control problem are also studied. The benefits of storage with respect to prediction quality and storage capacity are examined, and the overall effect on dispatch is quantified. Numerical experiments illustrate the proposed procedures.