PNNL Engineer Samrat Acharya and Team Receive Best Paper Award
Accolade earned at IEEE Conference on Innovative Smart Grid Technologies
Samrat Acharya, an electrical engineer at Pacific Northwest National Laboratory (PNNL), led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award at the organization’s recent annual conference.
The paper, “Weather Sensitive High Spatio-Temporal Resolution Transportation Electric Load Profiles For Multiple Decarbonization Pathways,” presents a methodology that could contribute to long-term energy planning. The research is part of a PNNL-funded initiative known as the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP).
Acharya accepted the award during the 2024 Conference on Innovative Smart Grid Technologies, North America, held February 19–22 in Washington, D.C.
“As an early career scientist and engineer in the field of clean energy, receiving the Best Paper Award at such a prestigious conference is a great source of motivation,” said Acharya, who joined PNNL in June 2022 as a power systems research engineer. “The award reinforces my commitment to conducting impactful and practical research that not only addresses current challenges but also propels humanity toward a future powered by sustainable, clean, and secure energy.”
The paper presents a novel methodology to downscale state-level annual transportation energy into weather-sensitive hourly charging loads for all-duty vehicles across balancing authorities in the Western U.S. interconnection. The resulting datasets are critical to inform long-term energy planning and specifically to understand the changes in electricity peak demand associated with the compound impact of decarbonization and climate change.
Acharya credited GODEEEP as well as several GODEEEP colleagues who contributed to the research, including Malini Ghosal, Travis Thurber, Allison Campbell, Casey Burleyson, Yang Ou, Gokul Iyer, Nathalie Voisin, and Jason Fuller.
Judges in the best paper competition praised the approach used in the Acharya-led study, as its authors explored the sensitivity of charging load profiles to temperature, charging strategies, and capacities. The paper also was praised for its use of open-source code and datasets.