Abstract
Identification of appropriate location for windmills in landlocked states, like the state of Iowa requires consideration of multiple factors and analysis of a large database, which is time-consuming. Under this study, advanced remote sensing and Python-based programming language have been utilized to select three specific sites within the boundaries of Lyon and Sioux county to locate new windmills based on three crucial factors; wind speed, elevation, and physicals barriers. The entire study area has been divided into several zones and ArcGIS tools, like selection, clipping, and merging have been used to process the entire database collected from secondary sources. Python scripts have been also used to calculate zone wise mean value of all three factors. Python scripts developed under this study are easily modifiable to include more than three factors providing a cost-effective method of decision making in the case of locating new windmills. An algorithm has been developed in the end section to combine all three factors and to rank all the zones considering their energy efficiency and environmental sustainability.
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Source: U.S. Energy Information Administration, 2019
Source: National Renewable Energy Laboratory, 2019
Source: National Renewable Energy Laboratory, 2019
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References
Arcgis. (2019). What is lidar data? Retrieved January 25, 2014, from http://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/what-is-lidar-data-.htm.
Awea. (2019a). Living near wind turbines. Retrieved December 26, 2019, from https://www.awea.org/wind-101/benefits-of-wind/wind-in-my-community/living-near-wind-turbines.
Awea. (2019b). 10 Steps in building a wind farm. Retrieved December 26, 2019, from https://www.agmrc.org/media/cms/10stwf_fs_8EF50C47B61F5.pdf.
Beef2live. (2019). States with the most and least wind. Retrieved January 29, 2019, from https://beef2live.com/story-states-least-wind-0-122176.
Biswal, G., & Soorya, S. (2015). Site selection for wind farm installation. International Journal of Innovative Research in Electrical, Electronics, Instrumentation, and Control Engineering (IJIREEICE), 3(8), 59–61.
Conca, J. (2015). EROI: a tool to predict the best energy mix. Retrieved December 26, 2019, from https://www.forbes.com/sites/jamesconca/2015/02/11/eroi-a-tool-to-predict-the-best-energy-mix/#26b5a4a1a027.
Drews, L. (2012). Multi-criteria GIS analysis for siting of small wind power plants: a case study from Berlin. Department of Physical Geography and Ecosystem Science Lund University. Retrieved January 29, 2019, from https://pdfs.semanticscholar.org/4f95/e0f2d685b84ca21bc0625bc7f0bb51f3bb51.pdf.
Edkins, A. (2014). Impacts of wind energy developments on birds and bats: looking into the problem. Oxford: University of Oxford.
EIA. (2015). Wind generation seasonal patterns vary across the United States. Retrieved January 29, 2019, from https://www.eia.gov/todayinenergy/detail.php?id=20112.
EIA. (2019). Wind explained: wind energy and the environment. Retrieved December 26, 2019, from https://www.eia.gov/energyexplained/wind/wind-energy-and-the-environment.php.
Energygeckkd. (2018). Wind energy principles, conversion and site selection. Retrieved January 25, 2014, from http://energygeckkd.blogspot.com/2013/02/wind-energy-principlesconversion-site.html.
Frey Architects. (2011). First wind turbine on power pole. Retrieved December 26, 2019, from http://www.architekten-frey.de/pressevents/first-wind-turbine-on-power-pole-1341.html.
Gaughan, R. (2018). How much land is needed for wind turbines? Retrieved January 29, 2019, from https://sciencing.com/much-land-needed-wind-turbines-12304634.html.
Gasch, R., & Twele, J. (2012). Wind power plants. Springer-Verlag Berlin Heidelberg.
Helgason, K. (2012). Selecting optimum location and type of wind turbines in Iceland. School of Science and Engineering, Reykjavík University. Retrieved January 29, 2019, from https://skemman.is/bitstream/1946/12679/1/MScKristbjornHelgason.pdf.
Kulkarni, K., Anil, T., & Gowdar, R. (2016). Wind energy development in India and a methodology for evaluating performance of wind farm clusters. Journal of Renewable Energy. https://doi.org/10.1155/2016/6769405.
Line, B. (2012). The 10 states that run on nuclear power. Retrieved January 29, 2019, from https://www.nbcnews.com/businessmain/10-states-run-nuclear-power-169050.
Mayer, S. (2018). Kern County named wind turbine capital of the world. Retrieved December 26, 2019, from https://www.bakersfield.com/news/kern-county-named-wind-turbine-capital-of-the-world/article_f4e22e40-5a34-11e8-a6a2-e7db220d3d8b.html.
Miller, A., & Li, R. (2014). A geospatial approach for prioritizing wind farm development in northeast Nebraska, USA. ISPRS International Journal of Geo-Information, 3(3), 968–979. https://doi.org/10.1155/2016/6769405.
Pamucar, D., Gigovic, L., Bajic, Z., & Janosevic, M. (2017). Location selection for wind farms using GIS multi-criteria hybrid model: An approach based on fuzzy and rough numbers. Sustainability, 9(8), 1315.
Parsons. (2003). Grid impacts of wind power: A summary of recent studies in the United States. EWEC Madrid.
Porter, J. (2019). US power output from renewables exceeds coal for the first time in history. Retrieved January 29, 2019, from https://www.theverge.com/2019/6/26/18759933/usa-coal-power-natural-gas-renewables.
Ritchie, H., & Roser, M. (2019). Renewable energy. Retrieved January 25, 2014, from https://ourworldindata.org/renewable-energy.
Rivera, R. (2014). Wind power. Retrieved January 25, 2014, from http://www.physics.rutgers.edu/~kotliar/honors/honsem02/somalwar/HonSem02/WindPower.pdf.
Rodman, L. C., & Meentemeyer, R. K. (2006). A geographic analysis of wind turbine placement in Northern California. Energy Policy, 34(15), 2137–2149.
Szurek, M., Blachowski, J., & Nowacka, A. (2014). GIS-based method for wind farm location multi-criteria analysis. Prace Naukowe Instytutu Gornictwa Politechniki Wroclawskiej.
The European Wind Energy Association (EWEA). (2009). Wind energy-the facts: A guide to the technology, economics and future of wind power. London: Earthscan.
Thomas, C. (2009). Tax law conferee. Nebraska Department of Revenue.
Uluyol, O., Parthasarathy, G., Foslien, W., & Kim, K. (2011). Power curve analytic for wind turbine performance monitoring and prognostics. Retrieved January 29, 2019, from https://pdfs.semanticscholar.org/b091/178c1b568a63793704e6cdcaaec82f075882.pdf.
Wilder, F. (1989) Geology of Lyon and Sioux Counties. Iowa Geological Survey Annual Report (Vol. 10, pp 85–184). Retrieved January 25, 2014, from https://doi.org/10.17077/2160-5270.1056.
Windexchange. (2019). Iowa 80-meter wind resource map. Retrieved January 29, 2019, from https://windexchange.energy.gov/states/ia.
Yilmaz, U., Turksoy, O., Ibrikci, T., & Teke, A. (2019). Estimation of electrical characteristics and maximum power point of photovoltaic panel. Journal of Electrical Systems, 13(2), 255–265.
Acknowledgements
I weight to express my gratitude to Dr. Brian K Gelder, Adjunct Assistant Professor, Department of Agronomy, Iowa State University who gave me a golden opportunity to do this research on the locational analysis of windmills. I would also express my appreciation to the research staffs of Iowa State University.
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Hossain, M.R. Python based location analysis of wind mills in urban environment. GeoJournal 86, 1355–1373 (2021). https://doi.org/10.1007/s10708-020-10137-z
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DOI: https://doi.org/10.1007/s10708-020-10137-z