Game theoretic analysis of Advanced Metering Infrastructure adoption

Dipayan GhoshCornell University

with Stephen Wicker,Dawn Schrader, William Schulze

and Lawrence Blume11/2/2011

Electricity market crisis

800% increase in electricity prices over 6 months

Daily Load Profile

6/1/2011 0:00 6/1/2011 2:45 6/1/2011 5:30 6/1/2011 8:15 6/1/2011 11:00 6/1/2011 13:45 6/1/2011 16:30 6/1/2011 19:15 6/1/2011 22:000

5000

10000

15000

20000

25000

NE load

Five-Minute Timestamp

Syst

em L

oad

(MW

)

Data: ISO-NE

5% decrease in load would have led to 50% lower prices

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

Privacy concerns of AMI

Temporally precise, fine granularity consumer data

Data collection

Utility

Household

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

Privacy concerns of AMI

Privacy-aware design principles

1. Provide full disclosure of data collection2. Require consent to data collection3. Minimize collection of personal data4. Minimize association and identification of

data with individuals5. Minimize and secure data retention

Fair Information PracticesDepartment of Health, Education and Welfare

Privacy-aware architecture for AMI

[5]

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?

AMI adoption game

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

[2]

AMI adoption game

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}

[2]

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 AMIs > e

Regulatory regimes for AMI introduction

Requirements for PA-AMI adoptionRegime 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

Regime 1: standard power meter (SM) retention permitted

Regime 2: advanced metering upgrade requirement

[1]

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

Questions

References1. D. Ghosh, D. Schrader, W. Schulze, and S. Wicker, “Economic analysis

of Advanced Metering Infrastructure adoption,” ISGT USA ‘12.2. D. Ghosh, S. Wicker and L. Blume, “Game theoretic analysis of

Advanced Metering Infrastructure,” ISGT Europe ‘11.3. D. Ghosh and S. Wicker, “Designing a privacy-aware framework for

vehicle-to-grid implementation,” working 2011.4. M. Lisovich, D. Mulligan, and S. Wicker, “Inferring personal

information from demand response systems,” IEEE Security and Privacy, Feb 2011.

5. S. Wicker and R. Thomas, “A privacy-aware architecture for demand response systems,” HICSS ‘10.

6. S. Wicker and D. Schrader, “Privacy-aware design principles for information networks,” Proceedings of the IEEE, 2011.