Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters
(2020)
Presentation / Conference Contribution
Briggs, C., Fan, Z., & Andras, P. (2020, December). Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters. Presented at NeurIPS 2020 Workshop: Tackling Climate Change with Machine Learning, Online
In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations. High resolution smart meter data can expose many private aspects of a consumer’s ho... Read More about Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters.