Assessment of Land and Renewable Energy Resource Potential for Regional Power System Integration with ML Spatio-Temporal Clustering

Rosemary E. Alden, Claire Halloran, Donovin D. Lewis, Dan M. Ionel, Malcolm McCulloch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Toward the planning and development of future electric power systems with extremely large penetration of renewable resources (DERs), detailed assessment of power and energy potential is needed considering both spatial and temporal data per region. Within this paper, a methodology for spatio-temporal DER capacity potential considering land cover types and weather variation are presented using spatio-temporal data. Additionally, an application of empirical orthogonal functions (EOFs) and max-p unsupervised learning techniques is proposed for DER generation to identify zones of similar output power in space and time. A detailed case study for the example region of Kentucky, USA is completed with state-of-the-art utility scale solar photovoltaic (PV) panels, wind turbines, and publicly available data from the National Aeronautics and Space Administration (NASA) Earthdata resource and the National Land Cover Database (NLCD). Annual estimates of wind and solar PV power for the example region are found to meet the state's public annual energy demand, even in the low land usage case. Further efforts to decarbonize energy generation and build additional renewable energy capacity are supported through the methodology and case study.

Original languageEnglish
Title of host publication12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023
Pages618-624
Number of pages7
ISBN (Electronic)9798350337938
DOIs
StatePublished - 2023
Event12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 - Oshawa, Canada
Duration: Aug 29 2023Sep 1 2023

Publication series

Name12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023

Conference

Conference12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023
Country/TerritoryCanada
CityOshawa
Period8/29/239/1/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • GIS
  • Renewable energy
  • open source modeling
  • spatial clustering
  • spatio-temporal modeling
  • unsupervised learning

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

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