A phase model approach for thermostatically controlled load demand response

A significant portion of electricity consumed worldwide is used to power thermostatically controlled loads (TCLs) such as air conditioners, refrigerators, and water heaters. Because the short-term timing of operation of such systems is inconsequential as long as their long-run average power consumption is maintained, they are increasingly used in demand response (DR) programs to balance supply and demand on the power grid. Here, we present an \textit{ab initio} phase model for general TCLs, and use the concept to develop a continuous oscillator model of a TCL and compute its phase response to changes in temperature and applied power. This yields a simple control system model that can be used to evaluate control policies for modulating the power consumption of aggregated loads with parameter heterogeneity and stochastic drift. We demonstrate this concept by comparing simulations of ensembles of heterogeneous loads using the continuous state model and an established hybrid state model. The developed phase model approach is a novel means of evaluating DR provision using TCLs, and is instrumental in estimating the capacity of ancillary services or DR on different time scales. We further propose a novel phase response based open-loop control policy that effectively modulates the aggregate power of a heterogeneous TCL population while maintaining load diversity and minimizing power overshoots. This is demonstrated by low-error tracking of a regulation signal by filtering it into frequency bands and using TCL sub-ensembles with duty cycles in corresponding ranges. Control policies that can maintain a uniform distribution of power consumption by aggregated heterogeneous loads will enable distribution system management (DSM) approaches that maintain stability as well as power quality, and further allow more integration of renewable energy sources.

[1]  R. M. Delgado,et al.  Demand-side management alternatives , 1985, Proceedings of the IEEE.

[2]  Evangelos Vrettos,et al.  Load frequency control by aggregations of thermally stratified electric water heaters , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[3]  Johan Lilliestam,et al.  The potential and usefulness of demand response to provide electricity system services , 2017 .

[4]  Eugene M. Izhikevich,et al.  Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting , 2006 .

[5]  Journal of Dynamic Systems, Measurement, and Control Guest Editorial Special Issue on Novel Robotics and Control , .

[6]  Mani Srivastava Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings , 2014 .

[7]  B. Ronacher,et al.  Phase response curves elucidating the dynamics of coupled oscillators. , 2009, Methods in enzymology.

[8]  Sho Shirasaka,et al.  Phase reduction theory for hybrid nonlinear oscillators. , 2016, Physical review. E.

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

[10]  Scott Backhaus,et al.  Safe control of thermostatically controlled loads with installed timers for demand side management , 2014 .

[11]  Jürgen Kurths,et al.  Optimal synchronization of oscillatory chemical reactions with complex pulse, square, and smooth waveforms signals maximizes Tsallis entropy , 2015 .

[12]  Takahiro Harada,et al.  Optimal waveform for the entrainment of a weakly forced oscillator. , 2010, Physical review letters.

[13]  Igor Kuzle,et al.  Low carbon technologies as providers of operational flexibility in future power systems , 2016, Applied Energy.

[14]  Tyrone L. Vincent,et al.  Aggregate Flexibility of Thermostatically Controlled Loads , 2015, IEEE Transactions on Power Systems.

[15]  J. Moehlis,et al.  On the Response of Neurons to Sinusoidal Current Stimuli: Phase Response Curves and Phase-Locking , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[16]  Fred Schweppe,et al.  Physically Based Modeling of Cold Load Pickup , 1981, IEEE Transactions on Power Apparatus and Systems.

[17]  Jr-Shin Li,et al.  Optimal entrainment of neural oscillator ensembles , 2012, Journal of neural engineering.

[18]  Hisa-aki Tanaka Optimal entrainment with smooth, pulse, and square signals in weakly forced nonlinear oscillators , 2014 .

[19]  Wei Zhang,et al.  Aggregated Modeling and Control of Air Conditioning Loads for Demand Response , 2013 .

[20]  Duncan S. Callaway,et al.  Quantifying flexibility of residential thermostatically controlled loads for demand response: a data-driven approach , 2014, BuildSys@SenSys.

[21]  R. F. Bischke,et al.  Design and Controlled Use of Water Heater Load Management , 1985, IEEE Transactions on Power Apparatus and Systems.

[22]  Ana Busic,et al.  Ancillary Service to the Grid Using Intelligent Deferrable Loads , 2014, IEEE Transactions on Automatic Control.

[23]  Denis V. Efimov,et al.  Controlling the phase of an oscillator: A phase response curve approach , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[24]  Rustam Singh,et al.  Simulating , 2012 .

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

[26]  Sarat Kumar Sahoo,et al.  Renewable and sustainable energy reviews solar photovoltaic energy progress in India: A review , 2016 .

[27]  Lieve Helsen,et al.  Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response , 2017 .

[28]  Jianzhong Wu,et al.  Challenges on primary frequency control and potential solution from EVs in the future GB electricity system , 2017 .

[29]  Sijie CHEN,et al.  From demand response to transactive energy: state of the art , 2017 .

[30]  Lingfeng Wang,et al.  IEEE TRANSACTIONS ON SMART GRID EDITOR-IN-CHIEF , 2014 .

[31]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[32]  Gabriela Hug,et al.  Impact of Disturbances on Modeling of Thermostatically Controlled Loads for Demand Response , 2015, IEEE Transactions on Smart Grid.

[33]  Jayashri Ravishankar,et al.  A hybrid control approach for regulating frequency through demand response , 2018 .

[34]  Hosam K. Fathy,et al.  Demand Response Using Heterogeneous Thermostatically Controlled Loads: Characterization of Aggregate Power Dynamics , 2017 .

[35]  Jianzhong Wu,et al.  Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market , 2017 .

[36]  Florian Dörfler,et al.  Synchronization and transient stability in power networks and non-uniform Kuramoto oscillators , 2009, Proceedings of the 2010 American Control Conference.

[37]  Jr-Shin Li,et al.  Optimal design of minimum-power stimuli for phase models of neuron oscillators. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[39]  R. W. Revans,et al.  Decision and Control , 1968 .

[40]  Fernando Paganini,et al.  IEEE Transactions on Automatic Control , 2006 .

[41]  Mattia Marinelli,et al.  Provision of secondary frequency control via demand response activation on thermostatically controlled loads: Solutions and experiences from Denmark , 2016 .

[42]  Bard Ermentrout,et al.  Simulating, analyzing, and animating dynamical systems - a guide to XPPAUT for researchers and students , 2002, Software, environments, tools.

[43]  Ana Busic,et al.  Spectral Decomposition of Demand-Side Flexibility for Reliable Ancillary Services in a Smart Grid , 2015, 2015 48th Hawaii International Conference on System Sciences.

[44]  Mattia Marinelli,et al.  Impact of thermostatically controlled loads' demand response activation on aggregated power: A field experiment , 2016 .

[45]  Soumya Kundu,et al.  Safe Protocols for Generating Power Pulses with Heterogeneous Populations of Thermostatically Controlled Loads , 2012, 1211.0248.

[46]  Jr-Shin Li,et al.  Optimal Subharmonic Entrainment of Weakly Forced Nonlinear Oscillators , 2014, SIAM J. Appl. Dyn. Syst..

[47]  Jinyue Yan,et al.  Renewable energy integration with mini/micro-grids , 2017 .

[48]  Ned Djilali,et al.  Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets , 2018 .

[49]  Hiroya Nakao,et al.  Phase reduction approach to synchronisation of nonlinear oscillators , 2016, 1704.03293.

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

[51]  Xinping Guan,et al.  Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids , 2017 .

[52]  Miroslav Krstic,et al.  Modeling, Control, and Stability Analysis of Heterogeneous Thermostatically Controlled Load Populations Using Partial Differential Equations , 2015 .

[53]  Mark O'Malley,et al.  Challenges and barriers to demand response deployment and evaluation , 2015 .