Energy system modeling activities in the MAHTEP Group

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Energy system modeling activities in the MAHTEP Group Dr Daniele Lerede, Politecnico di Torino 16–17th november 2023, dr daniele lerede, etsap meeting, etsap winter workshop, italy, mathep group, november 2023, politecnico di torino, semi-annual meeting, turin

Medio ambiente

Energy system modeling activities in the
MAHTEP Group
Our publications:
Our tools:
Postdoc
@ UniTo
PhD student
@ PoliTo
PhD student
@ PoliTo
PhD student
@ PoliTo
PhD student
@ UniTo
PhD student
@ PoliTo
PhD student
@ PoliTo
D. Lerede M. Nicoli G. Colucci
F. Amirkavei
D. Mosso A. Balbo M.E. Alfano
L. Savoldi
Professor
@ PoliTo
In collaboration with
Prof. Valeria Di Cosmo UniTo
Prof. Francesco Quatraro UniTo
Prof. A.R. De Queiroz NCSU
Prof. V. Bertsch RUB
Dr. Francesco Gracceva ENEA
Dr. Maurizio Gargiulo E4SMA
Dr. Alessandro Chiodi E4SMA

Modeling energy storage in TEMOA-Italy
0
50
100
150
200
250
300
2010 2020 2030 2040 2050
Storage
Capacity
(GWh)
Ref
NoStg
YNuc
Power
(GW)
Ref
No Storage
Yes Nuclear
Hour of the day
Integration of storage
technologies and short-
term dynamics related to the
availability of renewable
sources
Time scale refinement
(up to 288 time slices) of TEMOA-
Italy over the long run (up to 2050)
Ref NoStg YNuc
In collaboration with

Energy-material nexus
Domestic
production
Import
Technology
Supply
Commodity level-
supply risk
Technology
level-supply risk
Energy commodity Material commodity
Installation
Operation
Study the trade-off between:
Energy
supply
risk
Material
supply
risk
In collaboration with
Highly material intenstive energy transition
Potential bottlenecks along the supply chain
How to consider this in ESOMs?

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Micro RNAs (miRNAs) are small non-coding RNAs molecules having approximately 18-25 nucleotides, they are present in both plants and animals genomes. MiRNAs have diverse spatial expression patterns and regulate various developmental metabolisms, stress responses and other physiological processes. The dynamic gene expression playing major roles in phenotypic differences in organisms are believed to be controlled by miRNAs. Mutations in regions of regulatory factors, such as miRNA genes or transcription factors (TF) necessitated by dynamic environmental factors or pathogen infections, have tremendous effects on structure and expression of genes. The resultant novel gene products presents potential explanations for constant evolving desirable traits that have long been bred using conventional means, biotechnology or genetic engineering. Rice grain quality, yield, disease tolerance, climate-resilience and palatability properties are not exceptional to miRN Asmutations effects. There are new insights courtesy of high-throughput sequencing and improved proteomic techniques that organisms’ complexity and adaptations are highly contributed by miRNAs containing regulatory networks. This article aims to expound on how rice miRNAs could be driving evolution of traits and highlight the latest miRNA research progress. Moreover, the review accentuates miRNAs grey areas to be addressed and gives recommendations for further studies.

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Energy system modeling activities in the MAHTEP Group

1. Energy system modeling activities in the MAHTEP Group Our publications: Our tools: Postdoc @ UniTo PhD student @ PoliTo PhD student @ PoliTo PhD student @ PoliTo PhD student @ UniTo PhD student @ PoliTo PhD student @ PoliTo D. Lerede M. Nicoli G. Colucci F. Amirkavei D. Mosso A. Balbo M.E. Alfano L. Savoldi Professor @ PoliTo In collaboration with Prof. Valeria Di Cosmo UniTo Prof. Francesco Quatraro UniTo Prof. A.R. De Queiroz NCSU Prof. V. Bertsch RUB Dr. Francesco Gracceva ENEA Dr. Maurizio Gargiulo E4SMA Dr. Alessandro Chiodi E4SMA

2. Modeling energy storage in TEMOA-Italy 0 50 100 150 200 250 300 2010 2020 2030 2040 2050 Storage Capacity (GWh) Ref NoStg YNuc Power (GW) Ref No Storage Yes Nuclear Hour of the day Integration of storage technologies and short- term dynamics related to the availability of renewable sources Time scale refinement (up to 288 time slices) of TEMOA- Italy over the long run (up to 2050) Ref NoStg YNuc In collaboration with

3. Energy-material nexus Domestic production Import Technology Supply Commodity level- supply risk Technology level-supply risk Energy commodity Material commodity Installation Operation Study the trade-off between: Energy supply risk Material supply risk In collaboration with Highly material intenstive energy transition Potential bottlenecks along the supply chain How to consider this in ESOMs?

Energy system modeling activities in the MAHTEP Group

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