Robust Hierarchical Control Mechanism for Aggregated Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) are good candidates for direct load control (DLC). They can be aggregated to join the electricity market through a centralized management performed by virtual power plant (VPP). However, there are two main concerns that arise when TCLs participate in DLC. The first is related to the dispatchability of VPP against normal energy demand of individual TCLs in uncertain time-variant environments. The second refers to the tremendous increase of communication and computational requirements needed to perform DLC on a large population of TCLs. This paper introduces aggregators between the DLC controller and TCLs with a novel robust control mechanism to reconcile these concerns. The control mechanism is implemented with two layers: the upper layer suppresses the control payback effect with a quadratic optimization model, and the lower layer addresses the power trajectory tracking with a novel payback tracking error model (PTEM). The control method needs minimum sensing infrastructure since it requires power data only at the aggregation level. Our simulations resulted in a robust reference power tracking by the aggregator with a percentage root mean squared error between 3.33% - 5.69% under uncertain time-variant environments. The continuous responsiveness indicates that the aggregators manage to convert the aggregated TCLs into manageable resources that ensure the dispatchability of VPP.

Automated summary

Thermostatically controlled loads are suitable for direct load control and can be aggregated through a virtual power plant for electricity market participation. Challenges arise when TCLs participate in DLC, related to the dispatchability of VPP and the increase of communication and computational requirements. The paper proposes aggregators with a robust control mechanism to address these concerns, achieving robust power tracking and ensuring the dispatchability of VPP.