Zoom link: https://uio.zoom.us/j/67438761292
Speaker: Mehdi Foroughi from IFI, UiO.
Abstract: The emergence of prosumers is transforming the energy landscape, necessitating efficient and secure information exchange architectures. This presentation introduces a privacy-preserving optimization approach to enable autonomous, decentralized energy management for prosumers while safeguarding their data confidentiality. First, an overview of prosumers and (de)centralization in energy systems is provided. Next, the meaning of energy autonomy and the types of prosumer data are discussed. The core focus is the introduction of a Privacy-Sensitive Distributed Optimization (PSDO) framework that combines decentralized optimization with differential privacy. By facilitating autonomous decision-making while enforcing robust privacy guarantees, PSDO aims to maximize prosumers' control over energy management while preserving data privacy. Specifically, decentralized optimization promotes energy autonomy by enabling localized decision-making. Differential privacy provides strong confidentiality protections for sensitive information. By bringing together these techniques, PSDO allows prosumers to optimize energy management in a decentralized manner while keeping their data secure.