2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibility
Colin Jüni, Mina Montazeri, Yi Guo +3
Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling demand-side flexibility, particu…
Towards socio-techno-economic power systems with demand-side flexibility
Hanmin Cai, Federica Bellizio, Yi Guo +11
Harnessing the demand-side flexibility in building and mobility sectors can help to better integrate renewable energy into power systems and reduce global CO2 emissions. Enabling t…
Regularised Learning with Selected Physics for Power System Dynamics
Haiwei Xie, Federica Bellizio, Jochen L. Cremer +1
Due to the increasing system stability issues caused by the technological revolutions of power system equipment, the assessment of the dynamic security of the systems for changing…
Value of Optimal Trip and Charging Scheduling of Commercial Electric Vehicle Fleets with Vehicle-to-Grid in Future Low Inertia Systems
Alicia Blatiak, Federica Bellizio, Luis Badesa +1
The electrification of transport is seen as an important step in the global decarbonisation agenda. With such a large expected load on the power system from electric vehicles (EVs)…