Effects of Risk on Privacy Contracts for Demand-Side Management

As smart meters continue to be deployed around the world collecting unprecedented levels of fine-grained data about consumers, we need to find mechanisms that are fair to both, (1) the electric utility who needs the data to improve their operations, and (2) the consumer who has a valuation of privacy but at the same time benefits from sharing consumption data. In this paper we address this problem by proposing privacy contracts between electric utilities and consumers with the goal of maximizing the social welfare of both. Our mathematical model designs an optimization problem between a population of users that have different valuations on privacy and the costs of operation by the utility. We then show how contracts can change depending on the probability of a privacy breach. This line of research can help inform not only current but also future smart meter collection practices.

[1]  G.W. Hart,et al.  Residential energy monitoring and computerized surveillance via utility power flows , 1989, IEEE Technology and Society Magazine.

[2]  T. Gedra Optional forward contracts for electric power markets , 1994 .

[3]  F. Alvarado,et al.  Designing cost effective demand management contracts using game theory , 1999, IEEE Power Engineering Society. 1999 Winter Meeting (Cat. No.99CH36233).

[4]  F. Alvarado,et al.  Designing incentive compatible contracts for effective demand management , 2000 .

[5]  S. Basov A Partial Characterization of the Solution of the Multidimensional Screening Problem with Nonlinear Preferences , 2002 .

[6]  T. Mulgan The Contract Theory , 2006 .

[7]  Elias Leake Quinn,et al.  Smart Metering and Privacy: Existing Laws and Competing Policies , 2009 .

[8]  Stephen B. Wicker,et al.  Inferring Personal Information from Demand-Response Systems , 2010, IEEE Security & Privacy.

[9]  H. Vincent Poor,et al.  Smart meter privacy: A utility-privacy framework , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[10]  Stephen B. Wicker,et al.  A Privacy-Aware Architecture for Demand Response Systems , 2011, 2011 44th Hawaii International Conference on System Sciences.

[11]  Thomas A. Weber Optimal Control Theory with Applications in Economics , 2011 .

[12]  Bashar Nuseibeh,et al.  Adaptive security and privacy in smart grids: A software engineering vision , 2012, 2012 First International Workshop on Software Engineering Challenges for the Smart Grid (SE-SmartGrids).

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

[14]  Henrik Ohlsson,et al.  Fundamental limits of nonintrusive load monitoring , 2013, HiCoNS.

[15]  Hamidreza Tavafoghi,et al.  Optimal Energy Procurement from a Strategic Seller with Private Renewable and Conventional Generation , 2014, ArXiv.

[16]  Henrik Ohlsson,et al.  Quantifying the Utility-Privacy Tradeoff in the Smart Grid , 2014, ArXiv.

[17]  Henrik Ohlsson,et al.  Privacy and customer segmentation in the smart grid , 2014, 53rd IEEE Conference on Decision and Control.