Researchers develop model to project energy storage needs for renewable energy

Researchers have developed a model that can be used to project what a nation’s energy storage needs would be if it were to shift entirely to renewable energy sources, moving away from fossil fuels for electric power generation. The model offers policymakers critical information for use when making near-term decisions and engaging in long-term energy system planning.
The paper, “Modeling energy storage in long-term capacity expansion energy planning: an analysis of the Italian system,” is published in the Journal of Energy Storage.
“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,” says Anderson de Queiroz, co-author of a paper on the work and an associate professor of civil, construction and environmental engineering at North Carolina State University.
“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.”
Energy storage is a critical piece of this puzzle because renewable energy sources, such as solar or wind, don’t produce energy at the same rate all the time. For example, you need to be able to store energy generated by solar power so that you can use that energy at night, when the sun is not shining.
To better understand an energy system’s energy storage needs, the researchers modified an existing optimization model called Temoa.
Specifically, the researchers modified the model to account for how renewable energy production would change during different times of day and different times of the year. For example, there would be greater solar power production during summer when days are longer, but solar power would still drop overnight.
The researchers also accounted for changes in energy consumption at different times of day and during different seasons. For example, energy consumption may go up during hot summer afternoons if people use air conditioners.
Capturing these daily and seasonal fluctuations in renewable energy production and energy consumption allowed the researchers to create a more detailed model of the energy system, which allowed them to better answer questions about the system’s energy storage needs. How much renewable energy could be redirected to storage? How much energy storage would be needed to meet demands?
“Our modified model makes clear that increasing energy storage capacity is critical for decarbonizing Italy’s power sector, but it also offers some detailed insights,” de Queiroz says. “For example, the model suggests that Italy needs to be able to store about 10% of its electricity generation in short-term energy storage devices.”
The term “short-term energy storage” is somewhat confusing. It does not refer to how long a storage device can store energy. Rather, it refers to how long the device can sustain its maximum power output. For example, a one-hour 2-kilowatt device could release two kilowatts of power for one hour, whereas a three-hour 2-kilowatt device could release two kilowatts of power for three hours. Energy storage systems that can release the maximum power output for four hours or less are typically considered short-term energy storage devices.
“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,” de Queiroz says.
But while this paper focuses on Italy, the modified model the researchers developed for this work can be used to project energy storage needs for any energy system.
“As the world moves toward renewable power sources, we need to find ways to account for their variability,” says de Queiroz.
“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.”