G.W. Hart

Bio: G.W. Hart is an academic researcher from Columbia University. The author has an hindex of 1, co-authored 1 publications receiving 186 citations.

Residential energy monitoring and computerized surveillance via utility power flows

Abstract: The author notes that all novel technologies have the potential to affect society in a complex manner, with both beneficial and detrimental consequences. He considers an illustrative case study: a nonintrusive appliance load monitoring technique that can provide vital information to help avoid future energy crises, but can also be used for surveillance purposes. He notes that there appears to be a significant potential for the technology to be abused. The danger that the technology might eventually lead to an erosion of civil liberties and privacy rights leaves its developers in an ethical quandary. The author examines how this technology should be controlled. >

Nonintrusive appliance load monitoring

Abstract: A nonintrusive appliance load monitor that determines the energy consumption of individual appliances turning on and off in an electric load, based on detailed analysis of the current and voltage of the total load, as measured at the interface to the power source is described. The theory and current practice of nonintrusive appliance load monitoring are discussed, including goals, applications, load models, appliance signatures, algorithms, prototypes field-test results, current research directions, and the advantages and disadvantages of this approach relative to intrusive monitoring. >

Privacy-friendly energy-metering via homomorphic encryption

Abstract: The first part of this paper discusses developments wrt. smart (electricity) meters (simply called E-meters) in general, with emphasis on security and privacy issues. The second part will be more technical and describes protocols for secure communication with E-meters and for fraud detection (leakage) in a privacy-preserving manner. Our approach uses a combination of Paillier's additive homomorphic encryption and additive secret sharing to compute the aggregated energy consumption of a given set of users.

Protecting consumer privacy from electric load monitoring

Abstract: The smart grid introduces concerns for the loss of consumer privacy; recently deployed smart meters retain and distribute highly accurate profiles of home energy use. These profiles can be mined by Non Intrusive Load Monitors (NILMs) to expose much of the human activity within the served site. This paper introduces a new class of algorithms and systems, called Non Intrusive Load Leveling (NILL) to combat potential invasions of privacy. NILL uses an in-residence battery to mask variance in load on the grid, thus eliminating exposure of the appliance-driven information used to compromise consumer privacy. We use real residential energy use profiles to drive four simulated deployments of NILL. The simulations show that NILL exposes only 1.1 to 5.9 useful energy events per day hidden amongst hundreds or thousands of similar battery-suppressed events. Thus, the energy profiles exhibited by NILL are largely useless for current NILM algorithms. Surprisingly, such privacy gains can be achieved using battery systems whose storage capacity is far lower than the residence's aggregate load average. We conclude by discussing how the costs of NILL can be offset by energy savings under tiered energy schedules.

Eco-visualization: combining art and technology to reduce energy consumption

Abstract: Can creative visualizations of real time energy consumption patterns trigger more ecologically responsible behavior? Media art that displays the real time usage of key resources such as electricity offers new strategies to conserve energy in the home and workplace. This paper details the development of a public art project created for the National Center for Supercomputing Applications that measures electricity usage in real time for the purpose of education and curtailment of power usage. A version of this piece will be on view in the exhibition, Speculative Data and the Creative Imaginary, a component of the 2007 Creativity and Cognition conference.