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


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.
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- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Population of India. (n.d.). Ministry of Statistics and Programme Implementation. Retrieved October 28, 2020, from http://statisticstimes.com/demographics/country/india-population.php
- R. Gasch, J. T. (2005). Wind power Plants, Fundamaental, Design, construction,& Operation. James & James London
- 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
- 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
- RETScreen | Natural Resources Canada 2019. (n.d.). Web Site. Retrieved April 20, 2019, from https://www.nrcan.gc.ca/energy/retscreen/7465
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- Windnavigator,AWS Truepower, a UL Company. (n.d.). Retrieved September 16, 2019, from www.awstruepower.com
- 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
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