Solar energy potential assessment for electricity generation in the southeastern coast of Iran
Corresponding Author(s) : Abolfazl Ahmadi
Future Energy,
Vol. 2 No. 1 (2023): February 2023 Issue
Abstract
Among the types of renewable energy, solar energy has received more attention due to its ability to convert directly into electricity and heat, its ease of use, its possibility of storage and its endlessness, so that in recent decades, a lot of research has been done on solar energy systems in the world and in Iran. Considering Iran's potential in the field of solar energy and also the country's need for this type of energy, it is necessary to locate and identify suitable sites for the use of solar energy. In this research, the potential of generating power from solar energy in the ocean coasts of southeastern Iran has been investigated. The geographical data of the solar radiation map of Iran was used to estimate the power of electrical energy from spatial limiting criteria for the feasibility of installing photovoltaic panels at the power plant scale. Finally, the total power of electricity that can be extracted from suitable places in the region was calculated, Results showed that 37.5% of the Makran area is exploitable as solar farms. With a conversion efficiency of 15% and area factor of 70%, annual electricity production for the exploitable area is roughly 17200 GWh, which can be a driving force for industrial, economic and social development of Makran region.
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- Nejat, P., et al., A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renewable and sustainable energy reviews, 2015. 43: p. 843-862.
- Khazaee, M., et al., Assessment of renewable energy production capacity of Asian countries: a review. New Energy Exploitation and Application, 2022. 1(2): p. 25-41.
- Kannan, D., et al., A hybrid approach based on MCDM methods and Monte Carlo simulation for sustainable evaluation of potential solar sites in east of Iran. Journal of Cleaner Production, 2021. 279: p. 122368.
- Zahedi, R., et al., Modelling community-scale renewable energy and electric vehicle management for cold-climate regions using machine learning. Energy Strategy Reviews, 2022. 43: p. 100930.
- Noorollahi, Y., A. Khatibi, and S. Eslami, Replacing natural gas with solar and wind energy to supply the thermal demand of buildings in Iran: A simulation approach. Sustainable Energy Technologies and Assessments, 2021. 44: p. 101047.
- Sánchez-Lozano, J.M., et al., GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renewable Energy, 2014. 66: p. 478-494.
- Aydin, N.Y, E.Kentel, and H.S. Duzgun, GIS-based site selection methodology for hybrid renewable energy systems
- Charabi, Y. and A. Gastli, Integration of temperature and dust effects in siting large PV power plant in hot arid area. Renewable Energy, 2013. 57: p. 635-644.
- Polo, J., et al., Solar resources and power potential mapping in Vietnam using satellite-derived and GIS-based information. Energy conversion and management, 2015. 98: p. 348-358.
- Fountoulakis, I., et al., Effects of Aerosols and Clouds on the Levels of Surface Solar Radiation and Solar Energy in Cyprus. Remote Sensing, 2021. 13(12): p. 2319.
- Wu, Y., et al., Decision framework of solar thermal power plant site selection based on linguistic Choquet operator. Applied energy, 2014. 136: p. 303-311.
- Tercan, E., et al., A sustainable framework for spatial planning of photovoltaic solar farms using GIS and multi-criteria assessment approach in Central Anatolia, Turkey. Land use policy, 2021. 102: p. 105272.
- Sun, L., et al., A GIS-based multi-criteria decision making method for the potential assessment and suitable sites selection of PV and CSP plants. Resources, Conservation and Recycling, 2021. 168: p. 105306.
- Rezaei, M., et al. Location optimization of hybrid solar-wind plants by using FTOPSIS method. in Proceedings of the International Conference on Industrial Engineering and Operations Management. Bandung, Indonesia. (pp. 3284-3293), 2018.
- Janjai, S., et al., Evaluation of wind energy potential over Thailand by using an atmospheric mesoscale model and a GIS approach. Journal of Wind Engineering and Industrial Aerodynamics, 2014. 129: p. 1-10.
- Mousavi, M.S., A. Ahmadi, and A. Entezari, Forecast of Using Renewable Energies in the Water and Wastewater Industry of Iran. New Energy Exploitation and Application, 2022. 1(2).
- Shorabeh, S.N., et al., A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran. Renewable Energy, 2019. 143: p. 958-973.
- Zahedi, R., et al., Modeling and interpretation of geomagnetic data related to geothermal sources, Northwest of Delijan. Renewable Energy, 196 (2022): 444-450.
- Zahedi, R., et al., Evaluation of Resources and Potential Measurement of Wind Energy to Determine the Spatial Priorities for the Construction of Wind-Driven Power Plants in Damghan City. International Journal of Sustainable Energy and Environmental Research, 2022. 11(1): p. 1-22.
- Al Garni, H.Z. and A. Awasthi, Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Applied energy, 2017. 206: p. 1225-1240.
- Zahedi, R., et al., Potential measurement of Iran's western regional wind energy using GIS. Journal of Cleaner Production, 2022. 330: p. 129883.
- Türk, S., A. Koç, and G. Şahin, Multi-criteria of PV solar site selection problem using GIS-intuitionistic fuzzy based approach in Erzurum province/Turkey. Scientific Reports, 2021. 11(1): p. 1-23.
- Hazarika, M. and U.S. Dixit, Setup planning for machining. 2015: Springer. ISBN: 978-3-319-13320-1.
- Bhargava, A.K., Fuzzy set theory fuzzy logic and their applications. 2013: S. Chand Publishing.
- Zahedi, R., et al., Numerical simulation of combustion of sulfide-biomass concentrate ingredients and contaminants in copper furnace smelting. Future Energy, 2023. 2(1).
- Zimmermann, H.J., Fuzzy set theory. Wiley Interdisciplinary Reviews: Computational Statistics, 2010. 2(3): p. 317-332.
- Markovic, D., D. Cvetkovic, and B. Masic, Survey of software tools for energy efficiency in a community. Renewable and Sustainable Energy Reviews, 2011. 15(9): p. 4897-4903.
- Ye, J., Correlation coefficient of dual hesitant fuzzy sets and its application to multiple attribute decision making. Applied Mathematical Modelling, 2014. 38(2): p. 659-666.
- Stackhouse, P. and C. Whitlock, NASA surface meteorology and solar energy: RETScreen data. USA: Atmospheric Science Data Center< https://eosweb. larc. nasa. gov/cgi-bin/sse/retscreen. cgi, 2016.
- Mai T, Wiser R, Sandor D, Brinkman G, Heath G, Denholm P, Hostick DJ, Darghouth N, Schlosser A, Strzepek K. Renewable electricity futures study. Volume 1: Exploration of high-penetration renewable electricity futures. National Renewable Energy Lab.(NREL), Golden, CO (United States); 2012 Jun 1.
References
Nejat, P., et al., A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries). Renewable and sustainable energy reviews, 2015. 43: p. 843-862.
Khazaee, M., et al., Assessment of renewable energy production capacity of Asian countries: a review. New Energy Exploitation and Application, 2022. 1(2): p. 25-41.
Kannan, D., et al., A hybrid approach based on MCDM methods and Monte Carlo simulation for sustainable evaluation of potential solar sites in east of Iran. Journal of Cleaner Production, 2021. 279: p. 122368.
Zahedi, R., et al., Modelling community-scale renewable energy and electric vehicle management for cold-climate regions using machine learning. Energy Strategy Reviews, 2022. 43: p. 100930.
Noorollahi, Y., A. Khatibi, and S. Eslami, Replacing natural gas with solar and wind energy to supply the thermal demand of buildings in Iran: A simulation approach. Sustainable Energy Technologies and Assessments, 2021. 44: p. 101047.
Sánchez-Lozano, J.M., et al., GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renewable Energy, 2014. 66: p. 478-494.
Aydin, N.Y, E.Kentel, and H.S. Duzgun, GIS-based site selection methodology for hybrid renewable energy systems
Charabi, Y. and A. Gastli, Integration of temperature and dust effects in siting large PV power plant in hot arid area. Renewable Energy, 2013. 57: p. 635-644.
Polo, J., et al., Solar resources and power potential mapping in Vietnam using satellite-derived and GIS-based information. Energy conversion and management, 2015. 98: p. 348-358.
Fountoulakis, I., et al., Effects of Aerosols and Clouds on the Levels of Surface Solar Radiation and Solar Energy in Cyprus. Remote Sensing, 2021. 13(12): p. 2319.
Wu, Y., et al., Decision framework of solar thermal power plant site selection based on linguistic Choquet operator. Applied energy, 2014. 136: p. 303-311.
Tercan, E., et al., A sustainable framework for spatial planning of photovoltaic solar farms using GIS and multi-criteria assessment approach in Central Anatolia, Turkey. Land use policy, 2021. 102: p. 105272.
Sun, L., et al., A GIS-based multi-criteria decision making method for the potential assessment and suitable sites selection of PV and CSP plants. Resources, Conservation and Recycling, 2021. 168: p. 105306.
Rezaei, M., et al. Location optimization of hybrid solar-wind plants by using FTOPSIS method. in Proceedings of the International Conference on Industrial Engineering and Operations Management. Bandung, Indonesia. (pp. 3284-3293), 2018.
Janjai, S., et al., Evaluation of wind energy potential over Thailand by using an atmospheric mesoscale model and a GIS approach. Journal of Wind Engineering and Industrial Aerodynamics, 2014. 129: p. 1-10.
Mousavi, M.S., A. Ahmadi, and A. Entezari, Forecast of Using Renewable Energies in the Water and Wastewater Industry of Iran. New Energy Exploitation and Application, 2022. 1(2).
Shorabeh, S.N., et al., A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran. Renewable Energy, 2019. 143: p. 958-973.
Zahedi, R., et al., Modeling and interpretation of geomagnetic data related to geothermal sources, Northwest of Delijan. Renewable Energy, 196 (2022): 444-450.
Zahedi, R., et al., Evaluation of Resources and Potential Measurement of Wind Energy to Determine the Spatial Priorities for the Construction of Wind-Driven Power Plants in Damghan City. International Journal of Sustainable Energy and Environmental Research, 2022. 11(1): p. 1-22.
Al Garni, H.Z. and A. Awasthi, Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Applied energy, 2017. 206: p. 1225-1240.
Zahedi, R., et al., Potential measurement of Iran's western regional wind energy using GIS. Journal of Cleaner Production, 2022. 330: p. 129883.
Türk, S., A. Koç, and G. Şahin, Multi-criteria of PV solar site selection problem using GIS-intuitionistic fuzzy based approach in Erzurum province/Turkey. Scientific Reports, 2021. 11(1): p. 1-23.
Hazarika, M. and U.S. Dixit, Setup planning for machining. 2015: Springer. ISBN: 978-3-319-13320-1.
Bhargava, A.K., Fuzzy set theory fuzzy logic and their applications. 2013: S. Chand Publishing.
Zahedi, R., et al., Numerical simulation of combustion of sulfide-biomass concentrate ingredients and contaminants in copper furnace smelting. Future Energy, 2023. 2(1).
Zimmermann, H.J., Fuzzy set theory. Wiley Interdisciplinary Reviews: Computational Statistics, 2010. 2(3): p. 317-332.
Markovic, D., D. Cvetkovic, and B. Masic, Survey of software tools for energy efficiency in a community. Renewable and Sustainable Energy Reviews, 2011. 15(9): p. 4897-4903.
Ye, J., Correlation coefficient of dual hesitant fuzzy sets and its application to multiple attribute decision making. Applied Mathematical Modelling, 2014. 38(2): p. 659-666.
Stackhouse, P. and C. Whitlock, NASA surface meteorology and solar energy: RETScreen data. USA: Atmospheric Science Data Center< https://eosweb. larc. nasa. gov/cgi-bin/sse/retscreen. cgi, 2016.
Mai T, Wiser R, Sandor D, Brinkman G, Heath G, Denholm P, Hostick DJ, Darghouth N, Schlosser A, Strzepek K. Renewable electricity futures study. Volume 1: Exploration of high-penetration renewable electricity futures. National Renewable Energy Lab.(NREL), Golden, CO (United States); 2012 Jun 1.