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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid.

Daniele Croce1,2, Fabrizio Giuliano1, Ilenia Tinnirello1

  • 1Department of Engineering, University of Palermo, Viale delle Scienze, ed. 9, 90128 Palermo, Italy.

Sensors (Basel, Switzerland)
|April 23, 2020
PubMed
Summary
This summary is machine-generated.

We developed PP-Overgrid, a privacy-preserving system for smart buildings to manage energy demand response. This approach aggregates energy data securely, enabling better integration of renewable energy sources.

Keywords:
P2Pdistributedgossipingovergridoverlay networkspeer to peerprivacysecret sharingsmart grid

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Energy Systems

Background:

  • Distributed Demand Response (DR) schemes are crucial for smart grids.
  • Existing DR systems often face challenges in user privacy and data aggregation.
  • Peer-to-peer (P2P) architectures offer potential for decentralized energy management.

Purpose of the Study:

  • To introduce PP-Overgrid, a privacy-preserving scheme for distributed Demand Response (DR) in smart buildings.
  • To enhance the Overgrid P2P architecture with secure data aggregation capabilities.
  • To enable efficient DR by classifying flexible energy consumption and integrating renewable energy sources.

Main Methods:

  • Extension of Overgrid algorithms with privacy-preserving data aggregation (PP-Overgrid).
  • Integration of Secure Multi-Party Computation (SMPC) with a distributed data aggregation scheme.
  • Classification of flexible energy consumption from building energy profiles.
  • Application of DR schemes to match flexible consumption with renewable energy generation.

Main Results:

  • Demonstration of a privacy-preserving data aggregation technique for smart building energy management.
  • Successful classification of flexible energy consumption for DR optimization.
  • Validation of the PP-Overgrid algorithm's feasibility through large-scale network simulations.
  • Effective matching of flexible energy demand with available renewable energy sources.

Conclusions:

  • PP-Overgrid provides a viable solution for privacy-preserving Demand Response in P2P smart building networks.
  • The proposed method enhances user privacy while enabling efficient energy management and renewable energy integration.
  • The PP-Overgrid algorithm is validated for scalability and effectiveness in simulated smart grid environments.