In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

Microgrids are gaining popularity by facilitating distributed energy resources (DERs) and
forming essential consumer/prosumer centric integrated energy systems. Integration …

With the increasing concern on climate change and global warming, the reduction of carbon
emission becomes an important topic in many aspects of human society. The development …

Renewable generation and energy storage systems are technologies which evoke the future
energy paradigm. While these technologies have reached their technological maturity, the …

In recent years, the installation of battery energy storage (BES) integrated with solar
photovoltaic (PV) panels in residential houses has been rapidly accelerated tied to the high …

The necessity to obtain, to parametrize, and to maintain models of the underlying dynamics
impedes predictive control of energy systems in many real-world applications. To alleviate …

We propose a multi-time scale energy management framework for a smart photovoltaic (PV)
system that can calculate optimized schedules for battery operation, power purchases, and …

In view of the ineluctable uncertainties induced by renewables and load demand, it
becomes challenging to realize reliable online energy scheduling for microgrid clusters. To …

The hydrogen-based multimicrogrid (HMMG) has emerged as a game changer for energy
transition. However, it encounters new challenges in tackling uncertainty data streams …

In this work, the operation of microgrids is studied, using real data for demand and
renewable energy sources. A mixed integer nonlinear program to operate the microgrid is …