Multi Energy System Analysis:
The research group has been developing an open-source software called Multi Energy System Simulator (MESS), available at https://github.com/pielube/MESSpy, specifically designed to perform a detailed representation of a wide range of different energy systems, ranging from industrial-scale “Power to Hydrogen” systems to renewable energy communities and single-standing buildings under different timescales, boundary conditions and operation logics. MESS operates on a modular, bottom-up architecture, which not only ensures scalability but also allows for the exploration of best techno-economic solutions across multi-node energy systems enabling researchers to gain a holistic understanding of complex energy systems and their dynamics.
Natural Gas Networks Modelling:
Long experience in fluid-dynamic modeling of gas networks within simulation and optimization frameworks.
Engaged in research focused on decarbonizing gas networks, including modeling the impact of alternative energy vectors such as hydrogen on existing gas networks.
Effects of Transporting Blends of Natural Gas and Hydrogen in Gas Pipelines
Investigating the consequences on pressure losses, compressor power requirements, gas flow velocities, and flexibility implications modeling the Line Packing problem.
Modelling the localized hydrogen injections requires the development of quality tracking algorithms to guarantee the respect of the quality constraints at end users.
Building Energy Monitoring and Targeting:
In the smart systems management context, energy Monitoring and Targeting (M&T) is a method designed to provide insight into energy practices and consumption. It involves the processes of monitoring energy use, analysing the data collected and presenting the results to facilitate informed decision-making and subsequent action.
M&T is based on the realization of an energy model capable of representing the standard building energy consumption. The actual energy consumption must be then compared to the standard energy pattern to identify anomalies in the energy demand behaviour. In other words, building energy monitoring involves creating a predictive model to represent the building energy demand under standard conditions.
The model predictions are then compared with the actual energy consumption data through statistical methods, in order to highlight changes and anomalies in the energy demand behaviour of the analysed system.
The primary aim of energy monitoring is to identify small and gradual changes that may otherwise go unnoticed, resulting in significant energy waste.
Modelling of Traditional and Innovative Thermal Power Plants and Energy Storage Systems:
The decarbonization of the energy system and the increase of its climate resilience requires the development of affordable and integrated energy storage solutions. In this sense, a contribution can be offered from several points of view, among which:
Modelling in each part (bleeding and cooling system) of a Gas turbine, using ESMS code (with modular approach), the gas turbine and the bottomer HRSG performances can be determined in design and off-design. Using long experience, the effect of using hydrogen or ammonia as fuel in the Gas turbine performaces can determined. The exhaust gas recirculation effects can be simulated.
Modelling of energy storage management solutions taking into account electrical and thermal loads to favor the integration of renewable energy sources.
The gained experience in the simulation of complex power plants constitutes the background for the thermodynamic, design, off-design and thermo-economic optimization of thermo-mechanical systems such as Compressed Air Energy Storage (CAES)
Integration in smart-energy districts and neighborhoods should be considered, as a mean to enhance flexibility and optimized energy consumption.
Ultimo aggiornamento
02.05.2024