Modeling and Control of Aggregate Air Conditioning Loads for Robust Renewable Power Management

This paper examines the problem of demand-side energy management in smart power grids through the setpoint control of aggregate thermostatic loads. This paper models these loads using a novel partial differential equation framework that builds on existing diffusion- and transport-based load modeling ideas in the literature. Both this partial differential equation (PDE) model and its finite-difference approximations are bilinear in the state and control variables. This key insight creates a unique opportunity for designing nonlinear load control algorithms with theoretically guaranteed Lyapunov stability properties. This paper's main contribution to the literature is the development of the bilinear PDE model and a sliding mode controller for the real-time management of thermostatic air conditioning loads. The proposed control scheme shows promising performance in adapting aggregate air conditioning loads to intermittent wind power.

[1]  E. Handschin,et al.  Identification of stochastic electric load models from physical data , 1974 .

[2]  V. Utkin.  Variable structure systems with sliding modes , 1977 .

[3]  Y. Manichaikul,et al.  Physically Based Industrial Electric Load , 1979, IEEE Transactions on Power Apparatus and Systems.

[4]  Jean-Jacques E. Slotine,et al.  Sliding controller design for non-linear systems , 1984 .

[5]  R. Malhamé,et al.  Electric load model synthesis by diffusion approximation of a high-order hybrid-state stochastic system , 1985 .

[6]  M. W. Gustafson,et al.  Direct water heater load control-estimating program effectiveness using an engineering model , 1993 .

[7]  P. Kundur,et al.  Power system stability and control , 1994 .

[8]  N. Lu,et al.  Control strategies of thermostatically controlled appliances in a competitive electricity market , 2005, IEEE Power Engineering Society General Meeting, 2005.

[9]  S.E. Widergren,et al.  Modeling uncertainties in aggregated thermostatically controlled loads using a State queueing model , 2005, IEEE Transactions on Power Systems.

[10]  D.G. Infield,et al.  Stabilization of Grid Frequency Through Dynamic Demand Control , 2007, IEEE Transactions on Power Systems.

[11]  Masaaki Takagi,et al.  Power system stabilization by charging power management of Plug-in Hybrid Electric Vehicles with LFC signal , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.

[12]  Torgeir Ericson,et al.  Direct load control of residential water heaters , 2009 .

[13]  Stephan Koch,et al.  Potentials and applications of coordinated groups of thermal household appliances for power system control purposes , 2009, 2009 IEEE PES/IAS Conference on Sustainable Alternative Energy (SAE).

[14]  Duncan S. Callaway.  Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy , 2009 .

[15]  Larry Hughes,et al.  Meeting residential space heating demand with wind-generated electricity , 2010 .

[16]  Johanna L. Mathieu,et al.  Modeling and Control of Aggregated Heterogeneous Thermostatically Controlled Loads for Ancillary Services , 2011 .

[17]  Hosam K. Fathy,et al.  Modeling and control insights into demand-side energy management through setpoint control of thermostatic loads , 2011, Proceedings of the 2011 American Control Conference.

[18]  Ian A. Hiskens,et al.  Achieving Controllability of Electric Loads , 2011, Proceedings of the IEEE.

[19]  Hosam K. Fathy,et al.  Transport-Based Load Modeling and Sliding Mode Control of Plug-In Electric Vehicles for Robust Renewable Power Tracking , 2012, IEEE Transactions on Smart Grid.

[20]  Ernesto Kofman,et al.  Load management: Model-based control of aggregate power for populations of thermostatically controlled loads , 2012 .