Privacy-Preserving Distributed Optimization for Power Systems via ADMM
The FITNESS project is pleased to announce its second webinar, titled “Privacy-Preserving Distributed Optimization for Power Systems via ADMM”, which will take place on 25 March 2026 at 10:00 CET.
The session will be delivered by Prof. Natalia Alguacil, Professor of Electrical Engineering at the University of Castilla-La Mancha (UCLM), Ciudad Real, Spain, and member of the PEARL Research Group. Her research focuses on the operation, planning and economics of electric energy systems, as well as mathematical modelling, optimization and simulation applied to modern power systems.
Date: March 25, 2026
Time: 10:00–11:00 CET
Link: JOIN
ABSTRACT
Modern power systems are typically managed by independent agents that must preserve the privacy of their network data and assets. This new paradigm requires new optimization approaches that enable coordination across agents while ensuring the efficiency of the overall system. In this talk, a distributed framework for solving Optimal Power Flow (OPF) problems in both planning and operational contexts using the Alternating Direction Method of Multipliers (ADMM) will be presented. The proposed approach decomposes the original OPF problem into smaller subproblems that can be solved locally by different agents, allowing them to collaborate without sharing sensitive information such as network parameters, costs, or operational constraints. We will discuss the algorithmic structure, convergence properties, and practical considerations for implementing privacy-preserving distributed OPF in large-scale power systems. Numerical examples illustrate how the method enables scalable and coordinated decision-making while maintaining data privacy.
