Data-Driven Aggregation Control for Thermoelectric Loads in Demand Response

Within the concept of a smart grid, aggregators have task coordinating behavior large sets Distributed Energy Resources, each them offering small power/energy capacities, which help to balance power grid and can serve as providers services. Adequate coordination strategies are required optimally exploit these resources in ancillary services market. However, deriving model-based control policies for is complex due heterogeneity uncertainty related set associated agents. Then, data-driven model an adequate solution this sort situation. This paper presents application Youla–Kucera Data-Driven Control strategy development aggregator regulate consumption thermoelectric refrigerators, avoiding modeling process directly designing controller from data. A detailed simulation framework was executed verify validity proposed methodology. It shown that derived able offer frequency containment reserves service, achieving settling time 30 seconds with tracking error below 4.7%.