Reduced-Order Load Models for Large Populations of Flexible Appliances

To respond to volatility and congestion in the power grid, demand response (DR) mechanisms allow for shaping the load compared to a base load profile. When tapping on a large population of heterogeneous appliances as a DR resource, the challenge is in modeling the dimensions available for control. Such models need to strike the right balance between accuracy of the model and tractability. The goal of this paper is to provide a medium-grained stochastic hybrid model to represent a population of appliances that belong to two classes: deferrable or thermostatically controlled loads. We preserve quantized information regarding individual load constraints, while discarding information about the identity of appliance owners. The advantages of our proposed population model are 1) it allows us to model and control load in a scalable fashion, useful for ex-ante planning by an aggregator or for real-time load control; 2) it allows for the preservation of the privacy of end-use customers that own submetered or directly controlled appliances.

[1]  Mihaela van der Schaar,et al.  Incentive design for Direct Load Control programs , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

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

[3]  Tyrone L. Vincent,et al.  A generalized battery model of a collection of Thermostatically Controlled Loads for providing ancillary service , 2013, 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[4]  R.P. Hamalainen,et al.  Identification of consumers' price responses in the dynamic pricing of electricity , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[5]  Yuting Ji,et al.  Large scale charging of Electric Vehicles , 2012, PES 2012.

[6]  Cynthia Dwork,et al.  Differential Privacy: A Survey of Results , 2008, TAMC.

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

[8]  G. W. Hart,et al.  Nonintrusive appliance load monitoring , 1992, Proc. IEEE.

[9]  Vincent W. S. Wong,et al.  Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid , 2010, IEEE Transactions on Smart Grid.

[10]  G. Sanchez,et al.  Direct Load Control Decision Model for Aggregated EV Charging Points , 2012, IEEE Transactions on Power Systems.

[11]  H. Vincent Poor,et al.  Smart Meter Privacy: A Theoretical Framework , 2013, IEEE Transactions on Smart Grid.

[12]  Giacomo Verticale,et al.  Privacy-friendly appliance load scheduling in smart grids , 2013, 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[13]  Peng Liu,et al.  Secure Information Aggregation for Smart Grids Using Homomorphic Encryption , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[14]  Constantine Caramanis,et al.  Efficient Energy Delivery Management for PHEVs , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[15]  P. Gilman,et al.  MICROPOWER SYSTEM MODELING WITH HOMER , 2005 .

[16]  Felix A. Farret,et al.  Micropower System Modeling with Homer , 2006 .

[17]  Georgios Kalogridis,et al.  Privacy for Smart Meters: Towards Undetectable Appliance Load Signatures , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[18]  Olof M. Jarvegren,et al.  Pacific Northwest GridWise™ Testbed Demonstration Projects; Part I. Olympic Peninsula Project , 2008 .

[19]  Francois Bouffard,et al.  Electric vehicle aggregator/system operator coordination for charging scheduling and services procurement , 2013, 2013 IEEE Power & Energy Society General Meeting.

[20]  Claude Castelluccia,et al.  I Have a DREAM! (DiffeRentially privatE smArt Metering) , 2011, Information Hiding.

[21]  Sanem Sergici,et al.  Dynamic pricing of electricity for residential customers: the evidence from Michigan , 2013 .

[22]  K. Poolla,et al.  Optimal power and reserve capacity procurement policies with deferrable loads , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[23]  Nick Mathewson,et al.  Tor: The Second-Generation Onion Router , 2004, USENIX Security Symposium.

[24]  Anna Scaglione,et al.  Information infrastructure for cellular load management in green power delivery systems , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[25]  Mohamed A. El-Sharkawi,et al.  Optimal Combined Bidding of Vehicle-to-Grid Ancillary Services , 2012, IEEE Transactions on Smart Grid.

[26]  Chee-Yee Chong,et al.  Statistical Synthesis of Physically Based Load Models with Applications to Cold Load Pickup , 1984 .

[27]  A. Faruqui,et al.  Household response to dynamic pricing of electricity: a survey of 15 experiments , 2010 .

[28]  George Kesidis,et al.  Incentive-Based Energy Consumption Scheduling Algorithms for the Smart Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[29]  Leandros Tassiulas,et al.  Periodic Flexible Demand: Optimization and Phase Management in the Smart Grid , 2013, IEEE Transactions on Smart Grid.

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

[31]  Eilyan Bitar,et al.  Deadline differentiated pricing of deferrable electric power service , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[32]  Peter Xiaoping Liu,et al.  A game-theoretical decision-making scheme for electricity retailers in the smart grid with demand-side management , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[33]  Thomas A. Henzinger,et al.  Hybrid Automata: An Algorithmic Approach to the Specification and Verification of Hybrid Systems , 1992, Hybrid Systems.

[34]  Stephan Koch,et al.  Provision of Load Frequency Control by PHEVs, Controllable Loads, and a Cogeneration Unit , 2011, IEEE Transactions on Industrial Electronics.

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

[36]  C. Chung,et al.  Multi-Constrained Optimal Power Flow by an opposition-based differential evolution , 2012, 2012 IEEE Power and Energy Society General Meeting.

[37]  Kameshwar Poolla,et al.  Real-time scheduling of deferrable electric loads , 2012, 2012 American Control Conference (ACC).

[38]  N. Lu,et al.  A state-queueing model of thermostatically controlled appliances , 2004 .

[39]  A. Scaglione,et al.  A Scalable Stochastic Model for the Electricity Demand of Electric and Plug-In Hybrid Vehicles , 2014, IEEE Transactions on Smart Grid.

[40]  Manuel A. Matos,et al.  Optimization Models for EV Aggregator Participation in a Manual Reserve Market , 2013, IEEE Transactions on Power Systems.

[41]  Shuai Lu,et al.  Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response , 2012, 2012 45th Hawaii International Conference on System Sciences.

[42]  Chen Chen,et al.  An innovative RTP-based residential power scheduling scheme for smart grids , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[43]  Gerard Ledwich,et al.  A Hierarchical Decomposition Approach for Coordinated Dispatch of Plug-in Electric Vehicles , 2013, IEEE Transactions on Power Systems.

[44]  George Danezis,et al.  Privacy-Friendly Aggregation for the Smart-Grid , 2011, PETS.

[45]  Alexander Shapiro,et al.  The Sample Average Approximation Method for Stochastic Discrete Optimization , 2002, SIAM J. Optim..

[46]  Ross Baldick,et al.  Energy Delivery Transaction Pricing for flexible electrical loads , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[47]  Anna Scaglione,et al.  Least laxity first scheduling of thermostatically controlled loads for regulation services , 2013, 2013 IEEE Global Conference on Signal and Information Processing.

[48]  M. Caramanis,et al.  Optimal Power Market Participation of Plug-In Electric Vehicles Pooled by Distribution Feeder , 2013, IEEE Transactions on Power Systems.

[49]  Bart Jacobs,et al.  Privacy-Friendly Energy-Metering via Homomorphic Encryption , 2010, STM.

[50]  Ram Rajagopal,et al.  A method for automatically scheduling notified deferrable loads , 2013, 2013 American Control Conference.

[51]  Johanna L. Mathieu,et al.  State Estimation and Control of Electric Loads to Manage Real-Time Energy Imbalance , 2013 .