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Developing modeling strategies for energy storage technologies in ESOMs

keywords ENERGY FORECAST, ENERGY MODELING, ENERGY STORAGE

Reference persons LAURA SAVOLDI

External reference persons Ing. Matteo Nicoli

Research Groups MAHTEP

Thesis type RESEARCH, INNOVATIVE

Description The electricity demand is very variable during the day (from base load to peak load) with a consequent price curve that reaches higher values at the peaks and lower values at the base load. The electricity production, that is more and more reliant on renewables (and intermittent) energy sources, is also variable, implying issues that have to be considered and have significant effects on the structure of the electricity sector. From a technical point of view, the electricity system must be always able to guarantee the production of the required electrical power. From an economic point of view, the different energy price levels can make it advantageous to use innovative technologies (such as electricity storage solutions or hydrogen production from electrolysis with low electricity prices) to stabilize the system and support greater penetration of renewable energy sources into the energy mix. Current energy system simulation and optimization tools (such as the TIMES model generator or the TEMOA framework) are based on an analysis of the system mainly on an annual basis (with few time slices per year), treating the demand variability on this time scale in a very simplified way. The purpose of the activity is the development of a modeling strategy taking this phenomenon into account and allowing to evaluate the possible future development of energy storage technologies, coupled with the use of renewable energy sources for the decarbonization of the system in the long term.

Required skills Attendance of the course "Models and scenarios for energy planning".


Deadline 30/09/2023      PROPONI LA TUA CANDIDATURA




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