Evaluated the location of wind power plants based on spatial assessment of environmental factors Mazandaran Province, Iran

Document Type : Full length article

Authors

1 PhD student in Climatology, Department of Geography, Noor Branch, Islamic Azad University, Noor, Iran

2 Associate Professor of Department of Geography, Noor Branch, Islamic Azad University, Noor, Iran

3 Assistant Professor, Department of Geography, Noor Branch, Islamic Azad University, Noor, Iran

4 Assistant Professor of Geomorphology, Department of Natural Heritage, Research Institute of Cultural Heritage and Tourism, Tehran, Iran

Abstract

Extended Abstract
Introduction
Wind energy offers many advantages, which explains why it's one of the fastest-growing energy sources in the world. Many researches efforts are aimed at addressing the challenges to greater use of wind energy. Wind energy doesn't pollute the air like power plants that rely on combustion of fossil fuels, such as coal or natural gas. On the other hands, the world is fast becoming a global village due to the increasing daily requirement of energy by all population across the world while the earth in its form cannot change. The need for energy and its related services to satisfy human social and economic development, welfare and health is increasing. Returning to renewables to help mitigate climate change is an excellent approach which needs to be sustainable in order to meet energy demand of future generations. Recently, Mazandaran Province has needed more energy. Considering the capabilities of this province in generating renewable energy, recognizing the potentials of clean energy generation and consumption, especially wind energy, should be a priority in the plans of managers and researchers.
 
Materials and methods
Current study has been done with the aim of spatial capability of wind energy in Mazandaran Province with emphasis on its environmental factors. A descriptive, analytical and field approach is used in this study. The spatial capability of wind energy in Mazandaran Province was evaluated using spatial and quantitative data. In order to initially estimate the energy that can be obtained from wind flow in the province, the necessary calculations were performed on wind direction and velocity information over a period of 12 years. Statistics of 15 synoptic meteorological stations in the province at a height of 10 meters were used to collect daily wind speed and direction data. After calculating the average wind speed, wind speed continuity and wind power density in the meteorological stations, layers of each were prepared at heights of 10, 30 and 50 m using interpolation in ArcGIS software environment. Using AHP and ANP models, layers of 4 technical (climatic), environmental-social, topographic and economic criteria including 21 sub-criteria were prepared then overlapped to determine suitable locations for construction of power plants or installation of wind turbines in Mazandaran Province. Finally, wind potential spatial measurement was performed using spatial, cellular and zoning analyzes in ArcMap software environment.
 
Result and discussion
According to the calculations, it is clear that the price of fuel consumed by power plants in the current situation and based on the use of gas will make gas power plants still more cost-effective. In this case, it can be seen that even the cost of pollution cannot make the wind power plant more economical; Because the wind power plant is highly sensitive to exchange rate which this sensitivity is due to the high cost of imported equipment. But if the price of fuel used by power plants is calculated on the basis of the real price, wind farms will be justified. Therefore, with the resistance economy approach, replacing thermal power plants with wind power plants will be economical and cost-effective in the medium and long term. In this way, in addition to using the potential of renewable and clean energy in electricity generation (according to the environmental potential of Mazandaran Province), much lower environmental damage compared to fossil fuels and greater durability of non-renewable fuels for transmission to future generations, the economic costs of power generation and power plant networks maintenance will also be reduced. The relative weights obtained from the network analysis process model (AHP) in the process of selection of the suitable location of wind power plants in the province showed that the effect of climatic criterion with a relative weight of 0.543 is greater than other three criteria in preparing the zoning map. Topographic criteria with a relative weight of 0.26, economic with a relative weight of 0.111 and environmental-social criteria with a relative weight of 0.086 are in the second to fourth categories of influencing the preparation of optimal zoning maps for wind power plants in Mazandaran Province. According to the zoning map obtained from ANP model such as AHP map, the western parts of Noor township, the northern parts of Savadkuh, Sari, Neka and Behshahr townships, the central zone of Babol township along with the central zone and the northern parts of Amol township are more suitable than other parts of the province to establish or build wind power plants.
 
Conclusion
Energy sector strategies should be developed and planned with the approach of optimizing energy consumption and planning in renewable energy development. This study was done with the aim of spatial measurement of wind energy in Mazandaran Province. The most favorable conditions for the installation of wind turbines can be observed in the mountainous and high parts of Noor Township.

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Main Subjects


  1. Aghajani, H., Fattahi Moghaddam, M., Akbari, H., & Fattahi, R. (2015). Location of wind turbines based on environmental spatial assessment (Case study: Khorasan Razavi Province). Journal of Iran Energy, Vol. 18. No. 1. Pp. 85-100. [In Persian].
  2. Ahmadi, M., & Dadashi Roudbari, A. (2015). Feasibility study of wind power plants with AHP method in Semnan region. Journal of the Iranian Geographical Association, 13, 81-98. [In Persian].
  3. Allouhi, A., Zamzoum, O., & Islam, M.R. (2017). Evaluation of wind energy potential in Morocco’s coastal regions. Renewable and Sustainable Energy Reviews, 72, 311-324.
  4. Anthrax: General Information [Online] http://www.windpowerworks. Net, available 30.12.08.
  5. Asadi, M., & Khorshidoust, A.M. (2020). Site selection of wind power in East Azerbaijan Province by using AHP. Geography and Planning, 23(70), 101-122. [In Persian].
  6. Azizi, G., Farid Mojtahedi, N., Shaebanzadeh, F., Negah, S., & Abed, H. (2017). Wind behavior in west Alborz stations influenced by environmental implications. Geography and Planning, 21(62), 203-222. [In Persian].
  7. Baban, S.M.J., & Parry, T. (2001). Developing and applying a GIS-assisted approach to locating wind arms in the UK. Renewable Energy, 24, 59-71.
  8. Brower, M., (1992). Cool energy, revised edition, renewable solution to environment problems. Cambridge. MA, The MIT Press, 200pp.
  9. Caralis, G., Perivolaris, Y. Rados, K., & Zervos, A. (2008). On the effect of spatial dispersion of wind power plants on the wind energy capacity credit in Greece. Environmental Research Letter, 3, 3-15.
  10. Chen, W., Castruccio, S., & Genton, M.G. (2018). Current and future estimates of wind energy potential over Saudi Arabia. Journal of Geophysical Research: Atmospheres, 123, 6443-6459.
  11. Clarke, A. (1991). Wind energy progress and potential. Energy Policy, 19, 742-55.
  12. Entezari, A., Amir Ahmadi, A., Erfani, A., & Borzuie, A. (2012). Evaluation of wind energy potential and feasibility of wind power plant construction in Sabzevar. geographical studies of arid regions. Geographical Studies of Arid Regions, 3(9-10), 33-46. [In Persian].
  13. Esfandiari, A., Rangzi, K., Saberi, A., & Phattahi Moghadam, M. (2011). Potential measurement of solar power plants construction by studying climatic parameters in Khuzestan province using GIS, Geomatic National Conference, Tehran, Iran. [In Persian].
  14. Gandomkar, A. (2010). Determining the horizontal wind direction of Sistan using cluster analysis. Physical Geography Journal, 10, 67-76. [In Persian].
  15. Ilkilic, C., & Aydin, H. (2015). Wind power potential and usage in the coastal regions of Turkey. Renewable and Sustainable Energy Reviews, 44, 78-86.
  16. International Energy Agency. (2003). Renewables for power generation status and prospects. Paris, France: IEA, 194pp.
  17. International Energy Agency. (2006). Renewable energy: RD and D priorities. Insight from IEA technology programs. Paris, France: IEA, 224pp.
  18. Janbazghobadi, G.( 2020). Potentiometric analysis of wind energy to determine the optimum location for wind turbines in Mazandaran province. Geographical Planning of Space Journal, 9(34), 209-224. [In Persian].
  19. Kruyt, B., Dujardin, J., & Lehning, M. (2018). Improvement of wind power assessment in complex terrain: the case of COSMO-1 in the Swiss Alps. Front. Energy Res, 6(102), 1-10.
  20. Kuswandari, R., (2004). Assessment of different methods for measuring the sustainability of forest management. International Institute for Geo-Information Science and Earth Observation Enschede, Netherlands, 143pp.
  21. Malczewski, J. (1999). GIS and multicriteria decision analysis. John Wiley and Sons, New York, 408pp.
  22. Malczewski, J. (2006). Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis. Applied Earth Observation and Geoinformation, 8, 270-277.
  23. Maryanaji, Z., Hossieni, A., & Abbasi, H. (2018). Zoning and forecasting of the wind energy potential in Hamadan Province using, Geographic Information System, 26(104), 186-196. [In Persian].
  24. Morrison, M.L., & Sinclair, K. (2004). Wind energy technology, environmental impacts of. Encyclopedia of Energy, 6, 435-48.
  25. Negash, T., Mollerstrom, E., & Ottermo, F. (2020). An assessment of wind energy potential for the three topographic regions of Eritrea. Energies, 13(1846). 1-12.
  26. Noorollahi, Y., Ashraph, M.A., & Zamani, M. (2011). Assessment of the West Regional wind power energy potential using Geographic Information System (GIS). Iranian Journal of Energy, 14(37), 2-22. [In Persian].
  27. Ramirez-Rosado, I.J., Garcia-Garrido, E., Fernandez-Jimeneza, A., Zorzano-Santamaria P.J, Monteiro, C., & Miranda, V., (2008). Promotion of new wind farms based on a decision support system. Renewable Energy, 33, 558-66.
  28. Rehman, S., Natarajan, N., Vasudenvan, M., & Alhems, L.M. (2020). Assessment of wind energy potential across varying topographical features of Tamil Nadu, India. Energy Exploration and Exploitation, 38(1), 175-200.
  29. Rezaie Banafsheh, M., Jahanbakhsh, S., Dinpazhooh, Y., & Esmaeli, M. (2014). Feasibility study of using wind energy in Ardabil and Zanjan Provinces. Natural Geography Research, 3(46), 261-274. [In Persian].
  30. Sadeqi, Z., Dalalbashi Esfehani, Z., & Horri, H.R. (2013). Prioritize the factors affecting the location of renewable energy plants (solar and wind energy) in Kerman Province using GIS and multi-criteria decision-making techniques. Energy Planning and Policy Research, 1(2), 93-110. [In Persian].
  31. Salam, M.A., Yazdani, M.G., & Rahman, Q.M. (2018). Investigation of wind energy potentials in Brunei Darussalam. Frontiers in Energy. Available at: https://doi.org/10.1007/s11708-018-0528-4 (accessed 26 August 2019).
  32. Strantzali, E., & Aravosis, K. (2016). Decision making in renewable energy investments: A review. Renewable and Sustainable Energy Reviews, 55, 885-898.
  33. Tester, J.W., Drake, E.M., Driscoll, M.J., Golay, M.W., & Peters, W.A. (2005). Sustainable energy. Second edition, choosing among options, Cambridge, MA: The MIT Press, 1056pp.
  34. Tonakian, S., Piri Sahragard, H., & Amiri, M. (2018). Selection the locating areas for the construction of wind farms using fuzzy hierarchical analysis (Case study: Sistan plain). Desert Ecosystem Engineering Journal, 7(19), 1-16. [In Persian].
  35. Wrixon, G.T., Rooney, A.M.E., & Palz, W. (1993). Renewable energy-2000. Springer-Verlag, Berlin, Germany, 126pp.