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The Social Cost of Individual Privacy in Aggregated Residential Demand Response

Conference ·
There is an increasing body of experimental and theoretical research related to demand response using smart, connected home equipment in smart grid. However, as technologies are deployed at scale, privacy has become a major concern. One possible approach to address this concern is to model an entire home as an aggregated unit of resource for engaging in demand response. Such an approach would allow residents to participate in demand response while abstracting the specifics of the appliance usage pattern from the utility provider. The benefits of privacy-preserving demand response notwithstanding, it implies a cost in terms of wasted capacity. This paper aims to explore the privacy/capacity tradeoff by simulating a fleet of homes and comparing the results with a fleet of individual appliances. The results show that a fleet of homes only bids about 70% of available capacity, and in the presence of an aggregator this number declines to 50%. Thus, privacy of individual homes comes at a cost of sacrificing part of otherwise available capacity.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
1658001
Country of Publication:
United States
Language:
English

References (8)

Demand Response for Ancillary Services journal December 2013
PeHEMS: Privacy enabled HEMS and load balancing prototype conference November 2012
A geometric approach to virtual battery modeling of thermostatically controlled loads conference July 2016
Aggregate Flexibility of Thermostatically Controlled Loads journal January 2015
Demand response and smart grids—A survey journal February 2014
Energy Storage From Aggregate Deferrable Demand: Fundamental Trade-Offs and Scheduling Policies journal July 2018
Grid integration of distributed renewables through coordinated demand response conference December 2012
Stochastic battery model for aggregation of thermostatically controlled loads conference March 2016

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