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Abstract
This work proposes three switched control strategies for aggregated heating, ventilation, and air conditioning (HVAC) systems in commercial buildings to track the automatic generation control (AGC) signal in smart grid. The existing control strategies include the direct load control strategy and the setpoint regulation strategy. The direct load control strategy cannot track the AGC signal when the state of charge (SOC) of the aggregated thermostatically controlled loads (TCLs) exceeds their regulation capacity, while the setpoint regulation strategy provides flexible regulation capacity, but causes larger tracking errors. To improve the tracking performance, we took the advantages of the two control modes and developed three switched control strategies. The control strategies switch between the direct load control mode and the setpoint regulation mode according to different switching indices. Specifically, we design a discrete-time controller and optimize the controller parameter for the setpoint regulation strategy using the Fibonacci optimization algorithm, enabling us to propose two switched control strategies across multiple time steps. Furthermore, we extend the switched control strategies by introducing a two-stage regulation in a single time step. Simulation results demonstrate that the proposed switched control strategies can reduce the tracking errors for frequency regulation.
Highlights
As smart grid construction is rapidly executed and large-scale intermittent renewable energy resources are being integrated, demand response programs enable consumers to schedule loads in order to save energy, reduce costs, and help grid operation [1]
(2) Second, we present a pair of switched control strategies according to two switching indices, which are used to decide which control strategy should be applied across multiple time steps
Once the state of charge (SOC) reaches a or b, the temperature priority control strategy should be switched to the sliding-mode control strategy. c and d represent that the SOC is far enough from the energy limits, and the temperature priority control strategy should be used
Summary
As smart grid construction is rapidly executed and large-scale intermittent renewable energy resources are being integrated, demand response programs enable consumers to schedule loads in order to save energy, reduce costs, and help grid operation [1]. It is essential to study the load dynamics, the model parameters, the temperature evolution, and the power consumption of HVAC units. A centralized control framework of the HVAC units was presented in [19,20,21] to provide continuous regulation services, and the operational characteristics were analyzed under different system states and communication models. In [23], the authors modeled the aggregated HVAC units as a generalized energy storage battery and proposed a temperature-priority control strategy to control the power consumption to track the frequency regulation signal to serve for the grid, and the tracking errors were reduced by controlling the on/off states directly. The tracking error is extremely large when the synchronization of loads occurs Setpoint regulation is another control strategy to regulate the HVAC units [24].
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