DOI: https://doi.org/10.14710/ijred.2021.34029

Techno-Economic Analysis and Planning for the Development of Large Scale Offshore Wind Farm in India

Department of Electrical Engineering, Aligarh Muslim University, Aligarh, India

Received: 8 Nov 2020; Revised: 16 Dec 2020; Accepted: 30 Dec 2020; Available online: 2 Jan 2021; Published: 1 May 2021.
Editor(s): Grigorios Kyriakopoulos
Open Access Copyright (c) 2021 The Authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

Despite India's great potential for offshore wind energy development, no offshore wind farm exists in the country. This study aims to plan a large scale offshore wind farm in the south coastal region of India. Seven potential sites were selected for the wind resource assessment study to choose the most suitable site for offshore wind farm development. An optimally matched wind turbine was also selected for each site using the respective power curves and wind speed characteristics. Weibull shape and scale parameters were estimated using WAsP, openwind, maximum likelihood (MLH), and least square regression (LSR) algorithms. The maximum energy-carrying wind speed and the most frequent wind speed were determined using these algorithmic methods. The correlation coefficient (R2) indicated the efficiency of these methods and showed that all four methods represented wind data at all sites accurately; however, openwind was slightly better than MLH, followed by LSR and WAsP methods. The coastal site, Zone-B with RE power 6.2 M152 wind turbine, was found to be the most suitable site for developing an offshore wind farm. Furthermore, the financial analysis that included preventive maintenance cost and carbon emission analysis was also done. Results show that it is feasible to develop a 430 MW wind farm in the region, zone B, by installing seventy RE power 6.2 M152 offshore wind turbines. The proposed wind farm would provide a unit price of Rs. 6.84 per kWh with a payback period of 5.9 years and, therefore, would be substantially profitable.

Fulltext View|Download
Keywords: Weibull Parameters; Windographer; RET Screen; Offshore Wind Farm; GHG; Preventive Maintenance

Article Metrics:

Article Info
Section: Original Research Article
Language : EN
Recent articles
Differential Pulse Voltammetry Study for Quantitative Determination of Dysprosium (III) in Acetonitrile Solution The Effect of Amine Types on Breakthrough Separation of Methane on Biogas Techno-Economic Analysis and Planning for the Development of Large Scale Offshore Wind Farm in India Evaluation of a PV-TEG Hybrid System Configuration for an Improved Energy Output: A Review Effect of Fluid Flow Direction on Charging of Multitube Thermal Energy Storage for Flat Plate Solar Collectors More recent articles
Most cited articles
Two-Phase Expander Approach for Next Generation of Heat Recovery Systems Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition Thermodynamic Model of a Very High Efficiency Power Plant based on a Biomass Gasifier, SOFCs, and a Gas Turbine Evaluating the potential energy of a heliostat field and solar receiver of solar tower power plants in the southern region of Turkey Simulation of biogas utilization effect on the economic efficiency and greenhouse gas emission: a case study in Isfahan, Iran More cited articles
  1. Akpinar, E. K., & Akpinar, S. (2006). An assessment of wind turbine characteristics and wind energy characteristics for electricity production. Energy Sources, Part A: Recovery, Utilization and Environmental Effects, 28(10), 941–953. https://doi.org/10.1080/00908310600718817
  2. Akpınar, E., Akpınar, S., & Balpetek, N. (2018). Statistical Analysis Of Wind Speed Distribution Of Turkey As Regional. Journal of Engineering Technology and Applied Sciences, 3(1), 35–55. https://doi.org/10.30931/jetas.407141
  3. Alluri, S. K. R., Shit, T., Dhinesh, G., Gujjula, D., Phani Kumar, S. V. S., & Ramana Murthy, M. V. (2017). Offshore wind to meet increasing energy demands in India. Current Science, 113(4), 774–781. https://doi.org/10.18520/cs/v113/i04/774-781
  4. Arikan, Y., Arslan, Ö. P., & Çam, E. (2014). Accepted on: 27.04. Istanbul University - Journal of Electrical and Electronics Engineering, 15(1), 1907–1912. https://dergipark.org.tr/download/article-file/99301
  5. Ayodele, T. R., Jimoh, A. A., Munda, J. L., & Agee, J. T. (2012). Statistical analysis of wind speed and wind power potential of Port Elizabeth using Weibull parameters. Journal of Energy in Southern Africa, 23(2), 30–38
  6. Bansal, J. C., Farswan, P., & Nagar, A. K. (2018). Design of wind farm layout with non-uniform turbines using fitness difference based BBO. Engineering Applications of Artificial Intelligence, 71(April), 45–59. https://doi.org/10.1016/j.engappai.2018.02.007
  7. Baseer, M. A., Meyer, J. P., Rehman, S., & Alam, M. M. (2017). Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters. Renewable Energy, 102, 35–49. https://doi.org/10.1016/j.renene.2016.10.040
  8. Burton, T., Jenkins, N., Sharpe, D., & Bossanyi, E. (2011). Wind Energy Handbook, Second Edition. In Wind Energy Handbook, Second Edition. John Wiley and Sons. https://doi.org/10.1002/9781119992714
  9. Chalikias, M. S., Kyriakopoulos, G., & Kolovos, K. G. (2010). Environmental sustainability and financial feasibility evaluation of woodfuel biomass used for a potential replacement of conventional space heating sources. Part I: A Greek case study. Operational Research, 10(1), 43–56. https://doi.org/10.1007/s12351-009-0033-y
  10. Charles Rajesh Kumar, J., & Majid, M. A. (2020). Renewable energy for sustainable development in India: Current status, future prospects, challenges, employment, and investment opportunities. In Energy, Sustainability and Society. https://doi.org/10.1186/s13705-019-0232-1
  11. Chaurasiya, P. K., Ahmed, S., & Warudkar, V. (2018). Study of different parameters estimation methods of Weibull distribution to determine wind power density using ground based Doppler SODAR instrument. Alexandria Engineering Journal, 57(4), 2299–2311. https://doi.org/10.1016/j.aej.2017.08.008
  12. Chaurasiya, P. K., Kumar, V. K., Warudkar, V., & Ahmed, S. (2019). Evaluation of wind energy potential and estimation of wind turbine characteristics for two different sites. International Journal of Ambient Energy, 0(0), 1–24. https://doi.org/10.1080/01430750.2019.1611634
  13. Di Piazza, A., Di Piazza, M. C., Ragusa, A. (2010). Statistical Processing of Wind Speed Data for energy Forecast and Planning. International Conference on Renewable Energies and Power Quality (ICRPQ, 10). Granada, Spain
  14. Didane, D. H., Wahab, A. A., Shamsudin, S. S., Rosly, N., Zulkafli, M. F., & Mohd, S. (2017). Assessment of wind energy potential in the capital city of Chad, N’Djamena. AIP Conference Proceedings, 1831. https://doi.org/10.1063/1.4981190
  15. Emeksiz, C., & Dogan, Z. (2016). Wind Power Plant Feasibility Study in Tokat with RETScreen Analysis Program. Journal of New Results in Science, 5(11), 56–63
  16. Hemanth Kumar, M. B., Balasubramaniyan, S., Padmanaban, S., & Holm-Nielsen, J. B. (2019). Wind energy potential assessment by weibull parameter estimation using multiverse optimization method: A case study of Tirumala region in India. Energies, 12(11). https://doi.org/10.3390/en12112158
  17. Indhumathy, D., Seshaiah, C. V, & Sukkiramathi, K. (2015). Estimation of Weibull Parameters for Wind speed calculation at Kanyakumari in India. International Journal of Innovative Research in Science, Engineering and Technology, 3(1), 8340–8345. http://www.ijirset.com/upload/2014/january/33_Estimation.pdf
  18. Khahro, S. F., Soomro, A. M., Tabbassum, K., Dong, L., & Liao, X. (2013). Assessment of wind power potential at Hawksbay, Karachi Sindh, Pakistan. TELKOMNIKA Indonesian Journal of Electrical Engineering, 11(7). https://doi.org/10.11591/telkomnika.v11i7.2621
  19. Kiran, S., Alluri, R., Dhinesh, G., Kumar, S. V. S. P., Murthy, M. V. R., & Atmanand, M. A. (2017). Feasibility studies for development of offshore wind in India. OCEANS 2017 - Anchorage, 2017-Janua, 1–7
  20. Kolovos, K. G., Kyriakopoulos, G., & Chalikias, M. S. (2011). Co-evaluation of basic woodfuel types used as alternative heating sources to existing energy network. Journal of Environmental Protection and Ecology
  21. Kore, S. B., & S, L. A. A. G. D. A. S. S. (2016). Feasibility of Offshore Wind Farm in India. International Research Journal of Engineering and Technology, 3(11), 995–998
  22. Kumaraswamy, B. G., Keshavan, B. K., & Jangamshetti, S. H. (2009). A statistical analysis of wind speed data in west central part of karnataka based on weibull distribution function. 2009 IEEE Electrical Power and Energy Conference, EPEC 2009, 1–5. https://doi.org/10.1109/EPEC.2009.5420878
  23. Kyriakopoulos, G., Kolovos, K. G., & Chalikias, M. S. (2010). Environmental sustainability and financial feasibility evaluation of woodfuel biomass used for a potential replacement of conventional space heating sources. Part II: A combined Greek and the nearby Balkan countries case study. Operational Research, 10(1), 57–69. https://doi.org/10.1007/s12351-009-0034-x
  24. Kyriakopoulos, G. L. (2010). European and international policy interventions of implementing the use of wood fuels in bioenergy sector: a trend analysis and a specific wood fuels’ energy application. International Journal of Knowledge and Learning, 6(1), 43–54. https://doi.org/10.1504/IJKL.2010.034482
  25. Maples, B., Saur, G., Hand, M., Pietermen, R. van, & Obdam, T. (2013). Installation, Operation, and Maintenance Strategies to Reduce the Cost of Offshore Wind Energy. Technical Report Nrel/Tp-5000-57403, July, 1–106. http://www.nrel.gov/docs/fy13osti/57403.pdf
  26. Mathew, S. (2007). Wind energy: Fundamentals, resource analysis and economics. In Wind Energy: Fundamentals, Resource Analysis and Economics. Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-30906-3
  27. Mohsin, M., & Rao, K. V. S. (2018). Estimation of weibull distribution parameters and wind power density for wind farm site at Akal at Jaisalmer in Rajasthan. 3rd International Conference on Innovative Applications of Computational Intelligence on Power, Energy and Controls with Their Impact on Humanity, CIPECH 2018, 3, 14–19. https://doi.org/10.1109/CIPECH.2018.8724170
  28. NA, U., A, O., & KA, I. (2017). Investigation of Wind Power Potential over Some Selected Coastal Cities in Nigeria. Innovative Energy & Research, 06(01), 1–12. https://doi.org/10.4172/2576-1463.1000156
  29. Pobočíkova, I., Sedliačkova, Z., & Simon, J. (2018). Comparative study of seven methods for estimating the weibull distribution parameters for wind speed in bratislava - mlynská dolina. 17th Conference on Applied Mathematics, APLIMAT 2018 - Proceedings, 2018-Febru(February), 840–852
  30. Population of India. (n.d.). Ministry of Statistics and Programme Implementation. Retrieved October 28, 2020, from http://statisticstimes.com/demographics/country/india-population.php
  31. R. Gasch, J. T. (2005). Wind power Plants, Fundamaental, Design, construction,& Operation. James & James London
  32. Rafique, M. M., Rehman, S., Alam, M. M., & Alhems, L. M. (2018). Feasibility of a 100 MW installed capacity wind farm for different climatic conditions. Energies, 11(8). https://doi.org/10.3390/en11082147
  33. Rajagopalan, P. (2018). Challenges in grid integration of offshore wind in Tamil Nadu and Gujarat for policy makers and transmission planners. 2017 7th International Conference on Power Systems, ICPS 2017, 206–211. https://doi.org/10.1109/ICPES.2017.8387294
  34. RETScreen | Natural Resources Canada 2019. (n.d.). Web Site. Retrieved April 20, 2019, from https://www.nrcan.gc.ca/energy/retscreen/7465
  35. Riaz, M. M., & Khan, B. H. (2019a). Economic feasibility study to design a large offshore wind farm near coastal region of Rameshvaram, India. International Conference on Electrical, Electronics and Computer Engineering, UPCON 2019, 3–7. https://doi.org/10.1109/UPCON47278.2019.8980119
  36. Riaz, M. M., & Khan, B. H. (2019b). Estimation of Weibull parameters and selection of optimal wind turbine for the development of large offshore wind farm. 2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON), 1–6. https://doi.org/10.1109/UPCON47278.2019.8980167
  37. Saeidi, D., Mirhosseini, M., Sedaghat, A., & Mostafaeipour, A. (2011). Feasibility study of wind energy potential in two provinces of Iran: North and South Khorasan. Renewable and Sustainable Energy Reviews, 15(8), 3558–3569. https://doi.org/10.1016/j.rser.2011.05.011
  38. Sharma, P. K., Warudkar, V., & Ahmed, S. (2019). A comparative analysis of wind resource parameters using WAsP and windPRO. International Journal of Green Energy, 16(2), 152–166. https://doi.org/10.1080/15435075.2018.1550783
  39. Soe, T. T., Zheng, M., & Aung, Z. N. (2015). Assessment of economic feasibility on promising wind energy sites in Myanmar. International Journal of Renewable Energy Research, 5(3), 699–707
  40. Sohoni, V., Gupta, S., & Nema, R. (2016). A comparative analysis of wind speed probability distributions for wind power assessment of four sites. Turkish Journal of Electrical Engineering and Computer Sciences, 24(6), 4724–4735. https://doi.org/10.3906/elk-1412-207
  41. Stevens, M. J. M., & Smulders, P. T. (1979). The estimation of parameters of the weibull wind speed distribution for wind energy utilization purposes. Wind Engineering, 3(2), 132–145
  42. Sumair, M., Aized, T., Gardezi, S. A. R., Ur Rehman, S. U., & Rehman, S. M. S. (2020). Wind potential estimation and proposed energy production in Southern Punjab using Weibull probability density function and surface measured data. Energy Exploration & Exploitation, 166, 014459872092074. https://doi.org/10.1177/0144598720920748
  43. Tran, V. T., & Chen, T. H. (2013). Assessing the wind energy for rural areas of vietnam. International Journal of Renewable Energy Research, 3(3), 523–528. https://doi.org/10.20508/ijrer.59861
  44. Windnavigator,AWS Truepower, a UL Company. (n.d.). Retrieved September 16, 2019, from www.awstruepower.com
  45. Yu, J., Fu, Y., Yu, Y., Wu, S., Wu, Y., You, M., Guo, S., & Li, M. (2019). Assessment of offshore wind characteristics and wind energy potential in Bohai Bay, China. Energies, 12(15). https://doi.org/10.3390/en12152879

Last update:

  1. Techno-Economic Analysis and Modelling of the Feasibility of Wind Energy in Kuwait

    Ali M. H. A. Khajah, Simon P. Philbin. Clean Technologies, 4 (1), 2022. doi: 10.3390/cleantechnol4010002

  2. Techno-economic assessment of wind farm for sustainable power generation in Northern coastal region of Arabian sea

    Muhammad Zaid Masood Khan, Hafiz M. Abdur Rehman, Abdul Kashif Janjua, Adeel Waqas, Sehar Shakir, Majid Ali. Energy Reports, 9 , 2023. doi: 10.1016/j.egyr.2022.12.057

  3. RETRACTED: Techno-economic analysis and modelling of the feasibility of wind energy in Kuwait

    Seyed Amir Kaboli, Reyhaneh Nazmabadi. Renewable Energy and Environmental Sustainability, 7 , 2022. doi: 10.1051/rees/2021056

  4. Approaches in performance and structural analysis of wind turbines – A review

    Sakthivel Rajamohan, Abhiram Vinod, Mantri Pragada Venkata Sesha Aditya, Harshini Gopalakrishnan Vadivudaiyanayaki, Van Nhanh Nguyen, Müslüm Arıcı, Sandro Nižetić, Thi Thai Le, Rahmat Hidayat, Dinh Tuyen Nguyen. Sustainable Energy Technologies and Assessments, 53 , 2022. doi: 10.1016/j.seta.2022.102570

  5. Technological, Financial and Ecological Analysis of Photovoltaic Power System using RETScreen® : A Case in Khuzdar, Pakistan

    Um-E-Habiba Alvi, Ijaz Ahmed, Alveena Alvi, Babar Ashfaq, Sana Mukhtar, Paghunda Roheela Ali. 2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC), 2022. doi: 10.1109/ICETECC56662.2022.10069314

  6. Wind Power Potential Assessment at Different Locations in Lebanon: Best–Fit Probability Distribution Model and Techno-Economic Feasibility

    Youssef Kassem, Huseyin Gokcekus, Ahmed Mohamed Salah Essayah. Engineering, Technology & Applied Science Research, 13 (2), 2023. doi: 10.48084/etasr.5686

  7. Comparative evaluation of wind resources using the computer tool WAPs, case study of Mecheria West Algeria

    Amrani F, Missoum I, Bekkouche B. Trends in Computer Science and Information Technology, 7 (3), 2022. doi: 10.17352/tcsit.000054

Last update: 2023-12-02 06:49:37

No citation recorded.