Wind and Structures

  • 제31권4호
  • /
  • Pages.311-319
  • /
  • 2020
  • /
  • 1226-6116(pISSN)
  • /
  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Evaluation of wind power potential for selecting suitable wind turbine

  • Sukkiramathi, K. (Department of Mathematics, Sri Ramakrishna Engineering College) ;
  • Rajkumar, R. (Department of Mathematics, Kumaraguru College of Technology) ;
  • Seshaiah, C.V. (Department of Basic Science and Humanities, GMR Institute of Technology)
  • 투고 : 2019.04.25
  • 심사 : 2020.10.08
  • 발행 : 2020.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

India is a developing nation and heavily spends on the development of wind power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of Ennore site using wind data collected over a period of two years by three parameter Weibull distribution. The Weibull parameters are estimated using maximum likelihood, least square method and moment method and the accuracy is determined using R2 and root mean square error values. The site specific capacity factor is calculated by the mathematical model developed by three parameter Weibull distribution at different hub heights above the ground level. At last, the wind energy economic analysis is carried out using capacity factor at 30 m, 40 m and 50 m height for different wind turbine models. The analysis showed that the site has potential to install utility wind turbines to generate energy at the lowest cost per kilowatt-hour at height of 50 m. This research provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine.

키워드

참고문헌

  1. Amirinia, G., Mafi, S. and Mazaheri, S. (2017), "Offshore wind resource assessment of Persian Gulf using uncertainty analysis and GIS", Renew. Energy, 113, 915-929. https://doi.org/10.1016/j.renene.2017.06.070.
  2. Baloch, M.H., Abro, S.A., Sarwar Kaloi, G., Mirjat, N.H., Tahir, S., Nadeem, M.H. and Kumar, M. (2017), "A research on electricity generation from wind corridors of Pakistan (two provinces): A technical proposal for remote zones", Sustainability, 9(9). 1611. https://doi.org/10.3390/su9091611.
  3. Baloch, M.H., Chauhdary, S.T., Ishak, D., Kaloi, G.S., Nadeem, M.H., Wattoo, W.A. and Hamid, H.T. (2019), "Hybrid energy sources status of Pakistan: An optimal technical proposal to solve the power crises issues", Energy Strategy Rev., 24, 132-153. https://doi.org/10.1016/j.esr.2019.02.001.
  4. Baloch, M.H., Kaloi, G.S. and Memon, Z.A. (2016), "Current scenario of the wind energy in Pakistan challenges and future perspectives: A case study", Energy Reports, 2, 201-210. https://doi.org/10.1016/j.egyr.2016.08.002.
  5. Baloch, M.H., Kaloi, G.S. and Wang, J. (2015), "Feasible wind power potential from coastal line of Sindh Pakistan", Res. J. Appl. Sci. Eng. Technol., 10(4), 393-400. http://dx.doi.org/10.19026/rjaset.10.2504.
  6. Baloch, M.H., Wang, J., Kaloi, G.S., Memon, A.A., Larik, A.S. and Sharma, P. (2019), "Techno-economic analysis of power generation from a potential wind corridor of Pakistan: An overview", Environment. Progress Sustain. Energy, 28(2). https://doi.org/10.1002/ep.13005.
  7. Baqir, A.M., Mazhar, H.B., Abdul, H.M., Sajid, H.Q., Touqeer, A. J., Sohaib, T. and Dahaman, I. (2019), "Wind energy potential assessment and mapping through various distribution techniques: An experimental investigation for wind zone", Int. J. Energy Convers. (IRECON), 7(1), 29-37. https://doi.org/10.15866/irecon.v7i1.16449.
  8. Baseer, M.A., Meyer, J.P., Rehman, S. and Alam, M.M. (2016), "Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters", Renew Energy, 102, 35-49. https://doi.org/10.1016/j.renene.2016.10.040.
  9. Bassyouni, M., Gutub, S.A., Javaid, U., Awais, M., Rehman, S., Hamid, S.S.A. and Shafeek, H. (2015), "Assessment and analysis of wind power resource using Weibull parameters", Energy Explor. Exploit., 33(1),105-122. https://doi.org/10.1260%2F0144-5987.33.1.105. https://doi.org/10.1260/0144-5987.33.1.105
  10. Bhattacharya, P. and Bhattacharjee, R. (2010), "A study on Weibull distribution for estimating the parameters", J. Appl. Quant. Methods, 5(2), 234-241. https://doi.org/10.1260%2F030952409790291163.
  11. Chang, T. P. (2011), "Estimation of wind energy potential using different probability density functions", Appl. Energy, 88(5), 1848-1856. https://doi.org/10.1016/j.apenergy.2010.11.010.
  12. Hong, H. P. and Li, S.H. (2014), "Plotting positions and approximating first two moments of order statistics for Gumbel distribution: estimating quantiles of wind speed", Wind Struct., 19(4), 371-387. https://doi.org/10.12989/was.2014.19.4.371.
  13. Hussain Baloch, M., Ishak, D., Tahir Chaudary, S., Ali, B., Asghar Memon, A. and Ahmed Jumani, T. (2019), "Wind power integration: An experimental investigation for powering local communities", Energies, 12(4), 621. https://doi.org/10.3390/en12040621.
  14. Kaloi, G.S., Wang, J., Baloch, M.H. and Tahir, S. (2017), "Wind energy potential at Badin and Pasni coastal line of Pakistan", Int. J. Renew. Energy Develop., 6(2), 103-110. https://doi.org/10.14710/ijred.6.2.103-110.
  15. Katinas, V., Marciukaitis, M., Gecevicius, G. and Markevicius, A. (2017), "Statistical analysis of wind characteristics based on Weibull methods for estimation of power generation in Lithuania", Renew. Energy, 113, 190-201. https://doi.org/10.1016/j.renene.2017.05.071.
  16. Mahesar, S., Baloch, M.H., Kaloi, G.S., Kumar, M., Soomro, A. M., Solangi, A.A. and Memon, Y.A. (2018), "Power management of a stand-alone hybrid wind/solar/battery energy system: An experimental investigation", Int. J. Advan. Comput. Sci. Appl., 9(6). https://dx.doi.org/10.14569/IJACSA.2018.090631.
  17. Majid, S., Siamak, K.H. and Mehrdad, B. (2015), "Estimation of Weibull parameters for wind energy application in Iran", Wind Struct., 21(2), 203-221. https://doi.org/10.12989/was.2015.21.2.203.
  18. Mo, H.M., Hong, H.P. and Fan, F. (2015), "Estimating the extreme wind speed for regions in china using surface wind observations and real analysis data", J. Wind Eng. Indus. Aerod., 143, 19-33. https://doi.org/10.1016/j.jweia.2015.04.005.
  19. Piotr, W.A. (2017), "Review of Weibull functions in wind sector", Renew. Sustain. Energy Rev., 70, 1099-1107. https://doi.org/10.1016/j.rser.2016.12.014.
  20. Pryor, S.C., Shepherd, T.J. and Barthelmie, R.J. (2018), "Interannual variability of wind climates and wind turbine annual energy production", Wind Energy Sci., 3, 651-665. http://doi.org/10.5194/wes-3-651-2018.
  21. Rocha, P.A.C., de Sousa, R.C., de Andrade, C.F. and da Silva, M. E.V. (2012), "Comparison of seven numerical methods for determining Weibull parameters for wind energy generation in the northeast region of Brazil", Appl. Energy, 89(1), 395-400. https://doi.org/10.1016/j.apenergy.2011.08.003.
  22. Sarkar, A., Singh, S. and Mitra, D. (2011), "Wind climate modeling using Weibull and extreme value distribution", Int. J. Eng. Sci. Technol., 3(5), 100-106. http://dx.doi.org/10.4314/ijest.v3i5.68571.
  23. Shami, S.H., Ahamed, J., Zafar, R., Haris, M. and Bashir, S. (2016), "Evaluating wind energy potential in Pakistan's three provinces, with proposal for integration into national power grid", Renew. Sustain. Energy Rev., 53, 408-421 https://doi.org/10.1016/j.rser.2015.08.052.
  24. Sukkiramathi, K. and Seshaiah, C.V. (2016), "A mathematical model to estimate the wind power using three parameter Weibull distribution", Wind Struct., 22(4), 393-408. http://dx.doi.org/10.12989/was.2016.22.4.393.
  25. Sukkiramathi, K. and Seshaiah, C.V. (2020), "Analysis of wind power potential by the three-parameter Weibull distribution to install a wind turbine", Energy Explor. Exploit., 38(1), 158-174. https://doi.org/10.1177%2F0144598719871628. https://doi.org/10.1177/0144598719871628
  26. Zahid, H.H., Wei J. and Rehman, S. (2017), "Technical and economic assessment of wind power potential of Nooriabad, Pakistan", Energy Sustain. Soc., 7, 35. https://doi.org/10.1186/s13705-017-0137-9.