Smart meters have the capability to measure and record consumption data at a high time resolution and communicate such data to the energy provider. This provides the opportunity to better monitor and control the power grid and to enable demand response at the residential level. This not only improves the reliability of grid operations but also constitutes a key enabler to integrate variable renewable generation, such as wind or solar. However, the communication of high resolution consumption data also poses privacy risks as such data allows the utility, or a third party, to derive detailed information about consumer behavior. Hence, the main research objective of COPES is to develop new technologies to protect consumer privacy, while not sacrificing the “smartness”, i.e., advanced control and monitoring functionalities. The core idea is to overlay the original consumption pattern with additional physical consumption or generation, thereby hiding the consumer privacy sensitive consumption. The means to achieve this include the usage of storage, small scale distributed generation and/or elastic energy consumptions. Hence, COPES proposes and develops a radically new approach to alter the physical energy flow, instead of purely relying on encryption of meter readings, which provides protection against third party intruders but does not prevent the use of this data by the energy provider. In order to efficiently hide consumption information, intelligent decisions and strategies on when to charge/discharge the storage, which energy source to tap into, need to be made in real time. Therefore, in this project, algorithms based on and extending upon differential privacy, information and detection theoretic first principles that allow efficient use of physical capabilities to alter the overall consumption measured by the smart meters will be developed. Since these resources can also be used to minimize the electricity bill or increase the integration of renewables, trade-offs between these objectives and privacy will be studied and combined into a holistic privacy guaranteeing house energy management system. Implementations on multiple small test systems will serve as a proof of concept of the proposed methods.
Start date: (36 months)
Funding support: 1 170 000 €
- KTH Royal Institute of Technology - Sweden
- Imperial College London - United Kingdom
- INRIA Grenoble - France
- ETH Zurich - Switzerland