# Controlling Power and Virtual Inertia from Storage for Frequency Response

## TL;DR

This paper presents a generalized optimization framework for controlling power and virtual inertia from energy storage systems to improve frequency response during large disturbances in power systems, using centralized and distributed model predictive control.

## Contribution

It introduces a novel optimization framework that jointly controls power and virtual inertia from storage, enhancing frequency response capabilities beyond existing methods.

## Key findings

- The framework effectively improves frequency stability during disturbances.
- Distributed control achieves comparable performance to centralized control.
- Case studies validate the proposed optimization approach.

## Abstract

Nowadays, power imbalance happens more frequently due to the more integration of renewable energy sources. Energy storage is a kind of devices that can charge energy at one time and discharge energy at another time. This function makes that storage is widely envolved into promoting power balance of power system. Besides this function, storage can also emulate virtual inertia to respond to frequency deviations in the system. This work provides a generalized optimization framework to analyze how to control power and virtual inertia from storage to participate in frequency response when a large disturbance happens. Centralized and distributed model predictive control is employed here, and case study verifies the effectiveness of our optimization framework.