Using Italy as a case study, the model predicted that the Italian grid would need enough short-duration storage to absorb around 10 per cent of the country’s renewable generation. TEMOA (Tools for Energy Model Optimization and Analysis), developed by engineers at North Carolina State University (NC State), could be a vital instrument to assist policymakers with long-term energy system planning. The work is published in the Journal of Energy Storage.
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“As the world moves toward renewable power sources, we need to find ways to account for their variability,” said Anderson de Queiroz, an associate professor of civil, construction and environmental engineering at NC State and co-author of a paper.
“Energy storage devices give us the flexibility to adjust to fluctuations in energy production while also giving us the reliability we need to meet energy demands. And models like the one we’ve demonstrated here provide critical insights for policymakers regarding their long-term energy storage needs.”
For a fully decarbonised Italian grid by 2050, the study found that the optimal deployed storage capacity would be 40GW and 250GWh, corresponding to an average storage duration of about six hours. Notably, the NC State team found that the availability of nuclear power had a significant role on results, with nuclear baseload reducing the need for storage but also curtailing the penetration of renewables. Italy stopped using nuclear power in 1990 following a 1987 referendum on the issue.
“We focused this study on Italy’s energy system because it has suffered significantly in recent years, due to difficulties obtaining affordable natural gas due to Russia’s invasion of Ukraine,” said de Queiroz.
“That has raised questions about how Italy can make its energy system more robust. Our goal here was to develop a model that would allow us to determine what Italy’s energy storage needs would be if it moved completely away from fossil fuels and met its electricity demands with renewable resources.”
While this paper focuses on Italy, the model can be used to project energy storage needs for any energy system.
“Our projection related to short-term energy storage devices is driven both by the energy system’s energy storage needs and the fact that these devices are the most cost-effective way to meet those needs, based on recent cost projections and estimates,” said de Queiroz.
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