PhD in Engineering

Within the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie project GREYDIENT (https://www.greydient.eu/), we are hiring an of Early Stage Researchers (ESR 7) to develop a methodology to estimate the reliability and availability of energy-grid systems including components equipped with Prognostics and Health Management (PHM) capabilities. First, ESR 7 will model the effect of condition monitoring on the reliability and availability of the single components, assisted by virtual sensors that capture unmeasurable quantities based on measurable quantities and a white-box model of the component. Then, the effect of this change in reliability at the subsystems and network levels is propagated to the grid level, considering mutual dependencies of the components (e.g., via copula theory). Based on these developments, ESR 7 will map hybrid physical-virtual condition monitoring solutions (i.e., results of virtual sensors) to global performance metrics of the network, with corresponding uncertainties making it possible to maximize grid resilience vs. investment cost by optimally selecting portfolios of sensors on the grid elements. Finally, ESR 7 will model and optimize the Operations & Maintenance (O&M) costs of the grid by considering mutual relationships existing between the O&M decisions taken to manage variable energy demand and production, stochastic degradation and failure behaviour of the network elements and, finally, the uncertain information retrievable from PHM. This will be obtained by considering the problem as a sequential decision problem over a long horizon and employing Deep Reinforcement Learning approaches, trained by a white-box model of the network, that encode the stochastic behaviour of renewable energy production and energy demand, and the uncertainty in the sensor signal values.

The ESR will be enrolled at the PhD school of Politecnico di Milano (Italy), and will be supervised by Prof. E. Zio, P. Baraldi, F. Di Maio from Politecnico di Milano, by Prof. M. Beer from LEIBNIZ UNIVERSITAET HANNOVER as external co-supervisor, and by Dr. M. Compare  from ARAMIS as Non-university co-supervisor.