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Game theoretic analysis of Advanced Metering Infrastructure adoption

Game theoretic analysis of Advanced Metering Infrastructure adoption. Dipayan Ghosh Cornell University. with Stephen Wicker , Dawn Schrader, William Schulze and Lawrence Blume. 11/2/2011. Electricity market crisis. 800% increase in electricity prices over 6 months.

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Game theoretic analysis of Advanced Metering Infrastructure adoption

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  1. Game theoretic analysis of Advanced Metering Infrastructure adoption DipayanGhosh Cornell University with Stephen Wicker, Dawn Schrader, William Schulze and Lawrence Blume 11/2/2011

  2. Electricity market crisis 800% increase in electricity prices over 6 months

  3. Daily Load Profile Data: ISO-NE 5% decrease in load would have led to 50% lower prices

  4. Advanced Metering Infrastructure (AMI) • Consumer-end metering system • Two-way communications between AMI modules and other management devices • Detailed information for utility • Fast response to demand and supply signals • Real-time prices • Demand response • System load levelization • Cost reductions

  5. Privacy concerns of AMI Temporally precise, fine granularity consumer data Data collection Utility Household

  6. Privacy concerns of AMI Identifiable consumer behavior [4]: (a) aggregate power consumption data; (b) derived switch events; (c) load events; (d) reference and estimated presence intervals

  7. Privacy-aware design principles • Provide full disclosure of data collection • Require consent to data collection • Minimize collection of personal data • Minimize association and identification of data with individuals • Minimize and secure data retention Fair Information Practices Department of Health, Education and Welfare

  8. Privacy-aware architecture for AMI [5]

  9. Issues with implementation • Energy industry resistant to change • Welfare assessments • PA-AMI has limited benefits to utilities • Denying utility access to consumer information eliminates avenues for profit • Consumers unaware of privacy risks • Financial value of personal data • How to analyze issues analytically?

  10. AMI adoption game [2] v: value of consumer privacy of consumption data e: cost of opting in (or out) of DR program s: savings to consumer associated with AMI adoption g: profit to utility from sale of consumption data l: savings to utility from DR program c: AMI installation cost n : risk to utility of DR program termination r: expected penalty for sale of consumption data

  11. AMI adoption game [2] Game theoretic analysis of AMI game between a representative individual consumer and the utility [2]. The desired Nash equilibrium for implementation of privacy-aware AMI is {AM, PA-AMI}

  12. AMI adoption game • Requirements for PA-AMI adoption • Risk of selling data (r)must be greater than the difference between the profit from collecting data (g) and the risk of public outcry against NPA-AMI (n) r > g - n • Consumer savings must be greater than the consumer’s cost of effort of adopting AMI s > e

  13. Regulatory regimes for AMI introduction Regime 1: standard power meter (SM) retention permitted Regime 2: advanced metering upgrade requirement Requirements for PA-AMI adoption Regime 1:(1) v + s -2xv – xs – xe –yv – ys > 0 ; (2) v + s – xv – xs – yv – 2ys – yd > 0 Regime 2: v + s – zv – 2zs – zd > 0 [1]

  14. Conclusions and future work • PA-AMI adoption rates • Regression model for privacy valuation • Willingness-to-Pay v. Willingness-to-Accept • PHEV and V2G privacy risks

  15. Questions

  16. References • D. Ghosh, D. Schrader, W. Schulze, and S. Wicker, “Economic analysis of Advanced Metering Infrastructure adoption,” ISGT USA ‘12. • D. Ghosh, S. Wicker and L. Blume, “Game theoretic analysis of Advanced Metering Infrastructure,” ISGT Europe ‘11. • D. Ghoshand S. Wicker, “Designing a privacy-aware framework for vehicle-to-grid implementation,” working 2011. • M. Lisovich, D. Mulligan, and S. Wicker, “Inferring personal information from demand response systems,” IEEE Security and Privacy, Feb 2011. • S. Wicker and R. Thomas, “A privacy-aware architecture for demand response systems,” HICSS ‘10. • S. Wicker and D. Schrader, “Privacy-aware design principles for information networks,” Proceedings of the IEEE, 2011.

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