Data-based Aggregate Model of Refrigerators for Electric Power Grid Services

Electrical power system stability under high penetration of intermittent renewable energy generation, such as wind and solar energy, has become a high concern. It is unpredictable and hard to control due to little inertial behavior characteristic to these generation resources. To help mitigate possibly undesirable frequency excursions, demand-side frequency control presents an emerging solution. By observing the frequency deviation, devices could switch operating modes for a short time to rebalance generation. To analyze device level control algorithms, aggregate models for their behavior are needed. Refrigerators are household devices that could help with load modulation. This paper uses real measured data to analyze the refrigerator behavior, learn about its operating mode and power consumption ranges. A Markov chain process is proposed to model the transition of a refrigerator population from one operating mode to another, such that the overall load is modulated according to the control input. The Markov-chain model can be used to design control so that the overall load is modulated according to the control input.