Delay-aware Model Predictive Control for Fast Frequency Control

IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), pp. 1–7

Abstract

In secondary frequency control of power systems, measurement data, state information, and control signals must be transmitted over communication networks, where network delays and packet loss may occur. This paper presents a delay- and loss-aware model predictive controller (MPC) for fast frequency control in future power systems. The networked control strategy consists of a time-varying Kalman Filter with a butter, state augmentation of the prediction model, and an actuator function, hence making the controller delay- and loss-aware compared to traditional delay-tolerant or robust control designs. We present a co-simulation setup of a power system and a communication network simulator, where we demonstrate the networked control strategy in a realistic environment. The performance of the proposed control strategy is compared against a Smith Predictor-based PI controller in a microgrid and a transmission system, each supplied by grid-forming inverters, for varying communication network conditions, including different communication technologies and network traffic.

Authors 8

1. Tobias Heins Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University,Aachen,Germany

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

2. René Glebke Aachen Chair of Communication and Distributed Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Communication and Distributed Systems,Aachen,Germany

   Chair of Communication and Distributed Systems, RWTH Aachen University, Aachen, Germany

3. Mirko Stoffers Aachen Chair of Communication and Distributed Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Communication and Distributed Systems,Aachen,Germany

   Chair of Communication and Distributed Systems, RWTH Aachen University, Aachen, Germany

4. Sriram Karthik Gurumurthy Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University,Aachen,Germany

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

5. Jan Heesemann Aachen Chair of Communication and Distributed Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Communication and Distributed Systems,Aachen,Germany

   Chair of Communication and Distributed Systems, RWTH Aachen University, Aachen, Germany

6. Martina Joševski Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University,Aachen,Germany

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

7. Antonello Monti Aachen Institute for Automation of Complex Power Systems

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University,Aachen,Germany

   Fraunhofer FIT, Aachen, Germany

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

8. Klaus Wehrle Aachen Chair of Communication and Distributed Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Communication and Distributed Systems,Aachen,Germany

   Chair of Communication and Distributed Systems, RWTH Aachen University, Aachen, Germany