Optimal Frequency Regulation using Packetized Energy Management

TL;DR

This paper introduces a linearized virtual battery model for Packetized Energy Management (PEM) to enhance frequency regulation, utilizing model predictive control and packet randomization for improved grid response.

Contribution

It develops a virtual battery model for PEM, integrates it with MPC for better frequency regulation, and proposes packet randomization as an alternative control strategy.

Findings

The virtual battery model accurately predicts PEM's down-ramp response.

MPC with the model improves tracking of AGC signals.

Packet randomization enhances regulation performance.

Abstract

Packetized energy management (PEM) is a demand dispatch scheme that can be used to provide ancillary services such as frequency regulation. In PEM, distributed energy resources (DERs) are granted uninterruptible access to the grid for a pre-specified time interval called the packet length. This results in a down ramp-limited response in PEM for DERs that can only consume power from the grid. In this work, a linearized virtual battery model of PEM is provided that is capable of predicting the down-ramp limited output of PEM and is used in a model predictive control (MPC) framework to improve the performance of PEM in tracking an automatic generation control (AGC) signal. By performing statistical analysis on the AGC regulation signal, PJM Reg-D, an ARMA model is derived as a predictor for the MPC-based precompensator. Finally, as an alternative to MPC, it is shown that by varying the packet length as a function of time, for example through packet randomization, frequency regulation can be improved under PEM.