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Wind energy resource assessment in Madrid region

Author

Listed:
  • Migoya, Emilio
  • Crespo, Antonio
  • Jiménez, Ángel
  • García, Javier
  • Manuel, Fernando

Abstract

The “Comunidad Autónoma de Madrid” (Autonomous Community of Madrid, in the following Madrid Region), is a region located at the geographical centre of the Iberian Peninsula. Its area is 8.028km2, and its population about five million people. The Department of Economy and Technological Innovation of the Madrid Region, together with some organizations dealing on energy saving and other research institutions have elaborated an Energy Plan for the 2004–12 period. As a part of this work, the Fluid Mechanics Laboratory of the Superior Technical School of Industrial Engineers of the Polytechnic University of Madrid has carried out the assessment of the wind energy resources [Crespo A, Migoya E, Gómez Elvira R. La energía eólica en Madrid. Potencialidad y prospectiva. Plan energético de la Comunidad de Madrid, 2004–2012. Madrid: Comunidad Autónoma de Madrid; 2004]; using for this task the WAsP program (Wind Atlas Analysis and Application Program), and the own codes, UPMORO (code to study orography effects) and UPMPARK (code to study wake effects in wind parks). Different kinds of data have been collected about climate, topography, roughness of the land, environmentally protected areas, town and village distribution, population density, main facilities and electric power supply. The Spanish National Meteorological Institute has nine wind measurement stations in the region, but only four of them have good and reliable temporary wind data, with time measurement periods that are long enough to provide representative correlations among stations. The Observed Wind Climates of the valid meteorological stations have been made. The Wind Atlas and the resource grid have been calculated, especially in the high wind resource areas, selecting appropriate measurements stations and using criteria based on proximity, similarity and ruggedness index. Some areas cannot be used as a wind energy resource mainly because they have environmental regulation or, in some cases, are very close to densely populated towns. In the finally selected areas, it is assumed that there are hypothetical wind farms, consisting of 2MW turbines in appropriate configurations, in which the turbines are about 11 diameters apart. Its energy production will give an estimation of the wind energy potential of the Madrid Region.

Suggested Citation

  • Migoya, Emilio & Crespo, Antonio & Jiménez, Ángel & García, Javier & Manuel, Fernando, 2007. "Wind energy resource assessment in Madrid region," Renewable Energy, Elsevier, vol. 32(9), pages 1467-1483.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:9:p:1467-1483
    DOI: 10.1016/j.renene.2006.06.015
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    Citations

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    Cited by:

    1. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    2. Bilal, Boudy & Adjallah, Kondo Hloindo & Yetilmezsoy, Kaan & Bahramian, Majid & Kıyan, Emel, 2021. "Determination of wind potential characteristics and techno-economic feasibility analysis of wind turbines for Northwest Africa," Energy, Elsevier, vol. 218(C).
    3. Santos, J.A. & Rochinha, C. & Liberato, M.L.R. & Reyers, M. & Pinto, J.G., 2015. "Projected changes in wind energy potentials over Iberia," Renewable Energy, Elsevier, vol. 75(C), pages 68-80.
    4. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    5. Sharma, Kaushik & Ahmed, M. Rafiuddin, 2016. "Wind energy resource assessment for the Fiji Islands: Kadavu Island and Suva Peninsula," Renewable Energy, Elsevier, vol. 89(C), pages 168-180.
    6. Dahmouni, A.W. & Salah, M. Ben & Askri, F. & Kerkeni, C. & Nasrallah, S. Ben, 2010. "Wind energy in the Gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(4), pages 1303-1311, May.
    7. Früh, Wolf-Gerrit, 2013. "Long-term wind resource and uncertainty estimation using wind records from Scotland as example," Renewable Energy, Elsevier, vol. 50(C), pages 1014-1026.
    8. Jean Souza dos Reis & Nícolas de Assis Bose & Ana Cleide Bezerra Amorim & Vanessa de Almeida Dantas & Luciano Andre Cruz Bezerra & Leonardo de Lima Oliveira & Samira de Azevedo Emiliavaca & Maria de F, 2023. "Wind and Solar Energy Generation Potential Features in the Extreme Northern Amazon Using Reanalysis Data," Energies, MDPI, vol. 16(22), pages 1-27, November.
    9. Xydis, G. & Koroneos, C. & Loizidou, M., 2009. "Exergy analysis in a wind speed prognostic model as a wind farm sitting selection tool: A case study in Southern Greece," Applied Energy, Elsevier, vol. 86(11), pages 2411-2420, November.
    10. Florin Onea & Andrés Ruiz & Eugen Rusu, 2020. "An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore," Energies, MDPI, vol. 13(15), pages 1-23, August.
    11. Milanese, Marco & Congedo, Paolo Maria & Colangelo, Gianpiero & Lala, Roberta & Laforgia, Domenico & de Risi, Arturo, 2019. "Numerical method for wind energy analysis in WTG siting," Renewable Energy, Elsevier, vol. 136(C), pages 202-210.
    12. Cabello, M. & Orza, J.A.G., 2010. "Wind speed analysis in the province of Alicante, Spain. Potential for small-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3185-3191, December.
    13. Milanese, Marco & Tornese, Ljuba & Colangelo, Gianpiero & Laforgia, Domenico & de Risi, Arturo, 2017. "Numerical method for wind energy analysis applied to Apulia Region, Italy," Energy, Elsevier, vol. 128(C), pages 1-10.
    14. Gugliani, G.K. & Sarkar, A. & Ley, C. & Mandal, S., 2018. "New methods to assess wind resources in terms of wind speed, load, power and direction," Renewable Energy, Elsevier, vol. 129(PA), pages 168-182.

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