Abstract

This paper develops methods for state estimation of aggregated thermostatically controlled loads (TCLs) in smart grids, via partial differential equation (PDE) techniques. TCLs include on/off controlled devices, such as heat pumps, HVAC systems, and deep freezers. Control of aggregated TCLs provides a promising opportunity to mitigate the mismatch between power generation and demand, thus enhancing grid reliability and enabling renewable energy penetration. However, persistent communication between thousands of TCLs to a central server can be prohibitive. To this end, this paper focuses on designing a state estimation scheme for a PDE-based model of aggregated TCLs, thus reducing the required communication. First, a two-state linear hyperbolic PDE model for homogenous TCL populations is presented. This model is extended to heterogeneous populations by including a diffusive term. Next, a state observer is derived, which uses only measurements of how many TCLs turn on/off at any given time. The design is proven to be exponentially stable via backstepping techniques. Finally, the observer's properties are demonstrated via simulation examples. The estimator provides system-critical information for power system monitoring and control.

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