Methodolgy for preliminary assessment of regional wind energy potential

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

2 Scopus citations

Abstract

This paper describes a methodology for a preliminary assessment of a region's wind energy potential. The methodology begins by discussing four primary considerations for site location: wind resources, wildlife corridors, proximity to transmission grids, and required land area. Algorithms to calculate wind energy production using both hourly and annual average wind speed are presented. The hourly data method adjusts for differences in height, air density and terrain effects between the measurement site and the proposed turbine site. The annual average wind data method adjusts for these factors, and uses the average annual wind speed to generate a Rayleigh distribution of wind speeds over the year. Wind turbine electricity generation is calculated using the wind speed data and the turbine power curve. The lifecycle cost of electricity is calculated from operating costs, purchase costs, a discount rate, and the project lifetime. A case study demonstrates the use of the methodology to investigate the potential for producing electricity from wind turbines in Southwest Ohio. This information is useful to utilities, power producers and municipalities as they look to incorporate renewable energy generation into their portfolios.

Original languageEnglish
Title of host publicationProceedings of the ASME 3rd International Conference on Energy Sustainability 2009, ES2009
Pages1031-1040
Number of pages10
DOIs
StatePublished - 2009
Externally publishedYes
EventASME 3rd International Conference on Energy Sustainability, ES2009 - San Francisco, CA, United States
Duration: Jul 19 2009Jul 23 2009

Publication series

NameProceedings of the ASME 3rd International Conference on Energy Sustainability 2009, ES2009
Volume2

Conference

ConferenceASME 3rd International Conference on Energy Sustainability, ES2009
Country/TerritoryUnited States
CitySan Francisco, CA
Period07/19/0907/23/09

Keywords

  • Clean energy generation
  • Renewable energy
  • System modeling
  • Wind economics
  • Wind energy simulation
  • Wind turbines

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