Title: An Integrative Approach to Data-Driven Control in Electric Distribution Networks
Speaker: Roel Dobbe
Ubiquitous computing, algorithms, better devices, connectivity, and the ability to collect, store and probe large amounts of data are all becoming new commodities -- commodities that are the key ingredients to enabling new forms of automation and innovation in critical infrastructures. The question is then: how can we integrate data-driven techniques to improve and extend the capabilities of existing critical infrastructure, while safeguarding important values such as safety or privacy? In this talk, this question forms the driver for modernizing electric distribution networks to deal with higher levels of renewable generation and electrification.
We integrate concepts from control theory, machine learning, optimization, information theory and differential privacy to make concrete contributions in this context:
(1) decentralizing optimal power flow, by reconstructing the solution to centralized problems with locally available information, (2) providing a formal framework to assess learning-based decentralized policies and determine optimal communication strategies, by adopting a rate distortion approach, and (3) enabling the protection of sensitive information in the objectives and constraints of distributed optimization and control problems, by integrating a differential privacy mechanism.
We conclude with an overview on the inherent accumulation of bias and error in data-driven decision-making, and a call for assessing one's epistemology and engaging with domain experts and beneficiaries to steer the design of systems towards promoting safe, beneficial and just outcomes.
Roel’s research addresses the development, analysis, integration and governance of data-driven systems. His PhD work combined optimization, machine learning and control theory to enable monitoring and control of safety-critical systems, including energy & power