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Title: Supporting energy policy research with large language models: A case study in wind energy siting ordinances

Journal Article · · Energy and AI
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Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
2461639
Report Number(s):
NREL/JA--6A20-88544; S2666546824000971; 100431; PII: S2666546824000971
Journal Information:
Energy and AI, Journal Name: Energy and AI Journal Issue: C Vol. 18; ISSN 2666-5468
Publisher:
ElsevierCopyright Statement
Country of Publication:
United Kingdom
Language:
English

References (8)

Modeling the impact of the components of long work hours on injuries and “accidents” journal January 2006
Neurosymbolic AI: the 3rd wave journal March 2023
Interactions of wind energy project siting, wind resource potential, and the evolution of the U.S. power system journal May 2021
Quantifying siting difficulty: A case study of US transmission line siting journal January 2007
Exploring the capabilities and limitations of large language models in the electric energy sector journal June 2024
Wind Deployment in the United States: States, Resources, Policy, and Discourse journal November 2009
Electricity Markets and Renewables: A Survey of Potential Design Changes and Their Consequences journal November 2017
Large Language Models: A Comprehensive Survey of its Applications, Challenges, Limitations, and Future Prospects preprint July 2023

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Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
97 MATHEMATICS AND COMPUTING
energy analysis
energy policy
large language models (LLMs)
natural language processing (NLP)
siting ordinances