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Abstract
Wind energy is an abundant renewable resource that can support decarbonization of energy supply. It is, therefore, essential to conduct a comprehensive assessment of wind energy potential for effective transmission network planning and integration. This work introduces a spatial-temporal assessment methodology for wind energy name plate-rated power capacity that considers the locations of electrical substations and transmission lines. This methodology applies Geographic Information System (GIS) land cover data to define siting exclusions for wind turbine installations. The correlation between generated wind power and estimates of power system load, as well as capacity factor, on a sub-regional basis for specific latest generation low and very low wind speed turbines, is estimated. A case study for the proposed methodology is conducted for the Commonwealth of Kentucky, USA with state-of-the-art wind turbines, land cover data from the National Land Cover Database (NLCD), and publicly available spatiotemporal wind data from the NASA EarthData Pathfinder dataset. The results indicate the availability of suitable land for wind turbine deployment, which can contribute to fulfilling the regional annual energy requirement, even with the example restricted sitting exclusion scenario in which turbines must be within 10km distance of a substation.
Document Type
Conference Proceeding
Publication Date
Fall 11-2024
Digital Object Identifier (DOI)
10.1109/ICRERA62673.2024.10815143
Repository Citation
Kyeremeh, Kwabena; Alden, Rosemary E.; Patrick, Aron; and Ionel, Dan M., "Spatiotemporal Wind Energy Assessment for Transmission Network Integration Considering the Location of Electrical Substations and Loads" (2024). Electrical and Computer Engineering Graduate Research. 7.
https://uknowledge.uky.edu/ece_gradpub/7

Notes/Citation Information
Kyeremeh, K. A., Alden, R. E., Patrick, A., and Ionel, D. M., "Spatiotemporal Wind Energy Assessment for Transmission Network Integration Considering the Location of Electrical Substations and Loads," Proceedings, IEEE Conference on Renewable Energy Research and Applications (ICRERA), Nagasaki, Japan, doi: 10.1109/ICRERA62673.2024.10815143, 6p (Nov 2024)