IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v69y2017icp1199-1217.html
   My bibliography  Save this article

Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions

Author

Listed:
  • Jiang, Haiyan
  • Wang, Jianzhou
  • Wu, Jie
  • Geng, Wei

Abstract

Recently, with energy crises and environmental problems becoming increasingly obvious, the utilization of wind power has become a big concern. Meanwhile, the inconsistent relationship between China's economy and wind energy potential distribution has caused inevitable difficulties in transportation of wind power and even in grid integration. Therefore, the establishment of electrical power system integrated with local-used low-speed wind power has got considerable attention.

Suggested Citation

  • Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
    • Handle: RePEc:eee:rensus:v:69:y:2017:i:c:p:1199-1217
    DOI: 10.1016/j.rser.2016.11.241
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032116310176
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2016.11.241?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Meishen & Li, Xianguo, 2005. "MEP-type distribution function: a better alternative to Weibull function for wind speed distributions," Renewable Energy, Elsevier, vol. 30(8), pages 1221-1240.
    2. Tar, Károly, 2008. "Some statistical characteristics of monthly average wind speed at various heights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(6), pages 1712-1724, August.
    3. Masurowski, Frank & Drechsler, Martin & Frank, Karin, 2016. "A spatially explicit assessment of the wind energy potential in response to an increased distance between wind turbines and settlements in Germany," Energy Policy, Elsevier, vol. 97(C), pages 343-350.
    4. Carta, J.A. & Ramírez, P., 2007. "Analysis of two-component mixture Weibull statistics for estimation of wind speed distributions," Renewable Energy, Elsevier, vol. 32(3), pages 518-531.
    5. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    6. Compare, M. & Martini, F. & Zio, E., 2015. "Genetic algorithms for condition-based maintenance optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 244(2), pages 611-623.
    7. Feijóo, Andrés & Villanueva, Daniel, 2016. "Assessing wind speed simulation methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 473-483.
    8. Lo Brano, Valerio & Orioli, Aldo & Ciulla, Giuseppina & Culotta, Simona, 2011. "Quality of wind speed fitting distributions for the urban area of Palermo, Italy," Renewable Energy, Elsevier, vol. 36(3), pages 1026-1039.
    9. Wu, Jie & Wang, Jianzhou & Chi, Dezhong, 2013. "Wind energy potential assessment for the site of Inner Mongolia in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 215-228.
    10. Persaud, Shashi & Flynn, Damian & Fox, Brendan, 1999. "Potential for wind generation on the Guyana coastlands," Renewable Energy, Elsevier, vol. 18(2), pages 175-189.
    11. Zhang, Chi & Wei, Haikun & Zhao, Junsheng & Liu, Tianhong & Zhu, Tingting & Zhang, Kanjian, 2016. "Short-term wind speed forecasting using empirical mode decomposition and feature selection," Renewable Energy, Elsevier, vol. 96(PA), pages 727-737.
    12. Safari, Bonfils & Gasore, Jimmy, 2010. "A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda," Renewable Energy, Elsevier, vol. 35(12), pages 2874-2880.
    13. Zhao, Pan & Wang, Jiangfeng & Xia, Junrong & Dai, Yiping & Sheng, Yingxin & Yue, Jie, 2012. "Performance evaluation and accuracy enhancement of a day-ahead wind power forecasting system in China," Renewable Energy, Elsevier, vol. 43(C), pages 234-241.
    14. Celik, Ali N. & Kolhe, Mohan, 2013. "Generalized feed-forward based method for wind energy prediction," Applied Energy, Elsevier, vol. 101(C), pages 582-588.
    15. Tabassum-Abbasi, & Premalatha, M. & Abbasi, Tasneem & Abbasi, S.A., 2014. "Wind energy: Increasing deployment, rising environmental concerns," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 270-288.
    16. Arslan, Talha & Bulut, Y. Murat & Altın Yavuz, Arzu, 2014. "Comparative study of numerical methods for determining Weibull parameters for wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 820-825.
    17. Carta, José A. & Velázquez, Sergio, 2011. "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, Elsevier, vol. 36(5), pages 2671-2685.
    18. Wang, Jianzhou & Song, Yiliao & Liu, Feng & Hou, Ru, 2016. "Analysis and application of forecasting models in wind power integration: A review of multi-step-ahead wind speed forecasting models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 960-981.
    19. Vanvyve, Emilie & Delle Monache, Luca & Monaghan, Andrew J. & Pinto, James O., 2015. "Wind resource estimates with an analog ensemble approach," Renewable Energy, Elsevier, vol. 74(C), pages 761-773.
    20. Liu, Feng-Jiao & Chen, Pai-Hsun & Kuo, Shyi-Shiun & Su, De-Chuan & Chang, Tian-Pau & Yu, Yu-Hua & Lin, Tsung-Chi, 2011. "Wind characterization analysis incorporating genetic algorithm: A case study in Taiwan Strait," Energy, Elsevier, vol. 36(5), pages 2611-2619.
    21. Lun, Isaac Y.F & Lam, Joseph C, 2000. "A study of Weibull parameters using long-term wind observations," Renewable Energy, Elsevier, vol. 20(2), pages 145-153.
    22. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    23. Shishvan, Masoud Soleymani & Sattarvand, Javad, 2015. "Long term production planning of open pit mines by ant colony optimization," European Journal of Operational Research, Elsevier, vol. 240(3), pages 825-836.
    24. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    25. Pishgar-Komleh, S.H. & Keyhani, A. & Sefeedpari, P., 2015. "Wind speed and power density analysis based on Weibull and Rayleigh distributions (a case study: Firouzkooh county of Iran)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 313-322.
    26. Xiang, Yi & Zhou, Yuren & Liu, Hailin, 2015. "An elitism based multi-objective artificial bee colony algorithm," European Journal of Operational Research, Elsevier, vol. 245(1), pages 168-193.
    27. Saleh, H. & Abou El-Azm Aly, A. & Abdel-Hady, S., 2012. "Assessment of different methods used to estimate Weibull distribution parameters for wind speed in Zafarana wind farm, Suez Gulf, Egypt," Energy, Elsevier, vol. 44(1), pages 710-719.
    28. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
    29. Wang, Jianzhou & Hu, Jianming & Ma, Kailiang, 2016. "Wind speed probability distribution estimation and wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 881-899.
    30. Fthenakis, Vasilis & Kim, Hyung Chul, 2009. "Land use and electricity generation: A life-cycle analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1465-1474, August.
    31. Akdag, S.A. & Bagiorgas, H.S. & Mihalakakou, G., 2010. "Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean," Applied Energy, Elsevier, vol. 87(8), pages 2566-2573, August.
    32. Doucoure, Boubacar & Agbossou, Kodjo & Cardenas, Alben, 2016. "Time series prediction using artificial wavelet neural network and multi-resolution analysis: Application to wind speed data," Renewable Energy, Elsevier, vol. 92(C), pages 202-211.
    33. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Teo, K.T.K., 2016. "Wind energy assessment considering wind speed correlation in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1389-1400.
    34. Iversen, Emil B. & Morales, Juan M. & Møller, Jan K. & Madsen, Henrik, 2016. "Short-term probabilistic forecasting of wind speed using stochastic differential equations," International Journal of Forecasting, Elsevier, vol. 32(3), pages 981-990.
    35. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guedes, Kevin S. & de Andrade, Carla F. & Rocha, Paulo A.C. & Mangueira, Rivanilso dos S. & de Moura, Elineudo P., 2020. "Performance analysis of metaheuristic optimization algorithms in estimating the parameters of several wind speed distributions," Applied Energy, Elsevier, vol. 268(C).
    2. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
    3. Mohamed Bousla & Ali Haddi & Youness El Mourabit & Ahmed Sadki & Abderrahman Mouradi & Abderrahman El Kharrim & Saleh Mobayen & Anton Zhilenkov & Badre Bossoufi, 2023. "Analysis and Comparison of Wind Potential by Estimating the Weibull Distribution Function: Application to Wind Farm in the Northern of Morocco," Sustainability, MDPI, vol. 15(20), pages 1-17, October.
    4. Rahmatian, Mohammad Ali & Hashemi Tari, Pooyan & Mojaddam, Mohammad & Majidi, Sahand, 2022. "Numerical and experimental study of the ducted diffuser effect on improving the aerodynamic performance of a micro horizontal axis wind turbine," Energy, Elsevier, vol. 245(C).
    5. Kim, Ji-Young & Oh, Ki-Yong & Kim, Min-Suek & Kim, Kwang-Yul, 2019. "Evaluation and characterization of offshore wind resources with long-term met mast data corrected by wind lidar," Renewable Energy, Elsevier, vol. 144(C), pages 41-55.
    6. Mehr Gul & Nengling Tai & Wentao Huang & Muhammad Haroon Nadeem & Moduo Yu, 2020. "Evaluation of Wind Energy Potential Using an Optimum Approach based on Maximum Distance Metric," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    7. Saeed, Muhammad Abid & Ahmed, Zahoor & Zhang, Weidong, 2021. "Optimal approach for wind resource assessment using Kolmogorov–Smirnov statistic: A case study for large-scale wind farm in Pakistan," Renewable Energy, Elsevier, vol. 168(C), pages 1229-1248.
    8. Jianxing Yu & Yiqin Fu & Yang Yu & Shibo Wu & Yuanda Wu & Minjie You & Shuai Guo & Mu Li, 2019. "Assessment of Offshore Wind Characteristics and Wind Energy Potential in Bohai Bay, China," Energies, MDPI, vol. 12(15), pages 1-19, July.
    9. Alrashidi, Musaed & Rahman, Saifur & Pipattanasomporn, Manisa, 2020. "Metaheuristic optimization algorithms to estimate statistical distribution parameters for characterizing wind speeds," Renewable Energy, Elsevier, vol. 149(C), pages 664-681.
    10. Ye, Jianjun & Cheng, Yanglin & Xie, Junlong & Huang, Xiaohong & Zhang, Yuan & Hu, Siyao & Salem, Shehab & Wu, Jiejun, 2020. "Effects of divergent angle on the flow behaviors in low speed wind accelerating ducts," Renewable Energy, Elsevier, vol. 152(C), pages 1292-1301.
    11. Lins, Davi Ribeiro & Guedes, Kevin Santos & Pitombeira-Neto, Anselmo Ramalho & Rocha, Paulo Alexandre Costa & de Andrade, Carla Freitas, 2023. "Comparison of the performance of different wind speed distribution models applied to onshore and offshore wind speed data in the Northeast Brazil," Energy, Elsevier, vol. 278(PA).
    12. Ayman Al-Quraan & Bashar Al-Mhairat, 2022. "Intelligent Optimized Wind Turbine Cost Analysis for Different Wind Sites in Jordan," Sustainability, MDPI, vol. 14(5), pages 1-24, March.
    13. Liang, Yushi & Wu, Chunbing & Ji, Xiaodong & Zhang, Mulan & Li, Yiran & He, Jianjun & Qin, Zhiheng, 2022. "Estimation of the influences of spatiotemporal variations in air density on wind energy assessment in China based on deep neural network," Energy, Elsevier, vol. 239(PC).
    14. Tonglin Fu & Chen Wang, 2018. "A Hybrid Wind Speed Forecasting Method and Wind Energy Resource Analysis Based on a Swarm Intelligence Optimization Algorithm and an Artificial Intelligence Model," Sustainability, MDPI, vol. 10(11), pages 1-24, October.
    15. Ali Mostafaeipour & Mostafa Rezaei & Mehdi Jahangiri & Mojtaba Qolipour, 2020. "Feasibility analysis of a new tree-shaped wind turbine for urban application: A case study," Energy & Environment, , vol. 31(7), pages 1230-1256, November.
    16. Akpan, Anthony E. & Ben, Ubong C. & Ekwok, Stephen E. & Okolie, Chukwuma J. & Epuh, Emeka E. & Julzarika, Atriyon & Othman, Abdullah & Eldosouky, Ahmed M., 2024. "Technical and performance assessments of wind turbines in low wind speed areas using numerical, metaheuristic and remote sensing procedures," Applied Energy, Elsevier, vol. 357(C).
    17. Han, Qinkai & Ma, Sai & Wang, Tianyang & Chu, Fulei, 2019. "Kernel density estimation model for wind speed probability distribution with applicability to wind energy assessment in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    18. Abbassi, Abdelkader & Abbassi, Rabeh & Heidari, Ali Asghar & Oliva, Diego & Chen, Huiling & Habib, Arslan & Jemli, Mohamed & Wang, Mingjing, 2020. "Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach," Energy, Elsevier, vol. 198(C).
    19. Ayman Al-Quraan & Bashar Al-Mhairat & Ahmad M. A. Malkawi & Ashraf Radaideh & Hussein M. K. Al-Masri, 2023. "Optimal Prediction of Wind Energy Resources Based on WOA—A Case Study in Jordan," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
    20. Wang, Han & Yan, Jie & Han, Shuang & Liu, Yongqian, 2020. "Switching strategy of the low wind speed wind turbine based on real-time wind process prediction for the integration of wind power and EVs," Renewable Energy, Elsevier, vol. 157(C), pages 256-272.
    21. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    22. Memon, Mudasir Ahmed & Mekhilef, Saad & Mubin, Marizan & Aamir, Muhammad, 2018. "Selective harmonic elimination in inverters using bio-inspired intelligent algorithms for renewable energy conversion applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2235-2253.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Allouhi, A. & Zamzoum, O. & Islam, M.R. & Saidur, R. & Kousksou, T. & Jamil, A. & Derouich, A., 2017. "Evaluation of wind energy potential in Morocco's coastal regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 311-324.
    2. Hu, Qinghua & Wang, Yun & Xie, Zongxia & Zhu, Pengfei & Yu, Daren, 2016. "On estimating uncertainty of wind energy with mixture of distributions," Energy, Elsevier, vol. 112(C), pages 935-962.
    3. Soukissian, Takvor H. & Karathanasi, Flora E., 2017. "On the selection of bivariate parametric models for wind data," Applied Energy, Elsevier, vol. 188(C), pages 280-304.
    4. Wais, Piotr, 2017. "Two and three-parameter Weibull distribution in available wind power analysis," Renewable Energy, Elsevier, vol. 103(C), pages 15-29.
    5. Wais, Piotr, 2017. "A review of Weibull functions in wind sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1099-1107.
    6. Wang, Jianzhou & Hu, Jianming & Ma, Kailiang, 2016. "Wind speed probability distribution estimation and wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 881-899.
    7. Jung, Christopher & Schindler, Dirk, 2019. "Wind speed distribution selection – A review of recent development and progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    8. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
    9. Bagci, Kubra & Arslan, Talha & Celik, H. Eray, 2021. "Inverted Kumarswamy distribution for modeling the wind speed data: Lake Van, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Usta, Ilhan, 2016. "An innovative estimation method regarding Weibull parameters for wind energy applications," Energy, Elsevier, vol. 106(C), pages 301-314.
    11. Alrashidi, Musaed & Rahman, Saifur & Pipattanasomporn, Manisa, 2020. "Metaheuristic optimization algorithms to estimate statistical distribution parameters for characterizing wind speeds," Renewable Energy, Elsevier, vol. 149(C), pages 664-681.
    12. Campisi-Pinto, Salvatore & Gianchandani, Kaushal & Ashkenazy, Yosef, 2020. "Statistical tests for the distribution of surface wind and current speeds across the globe," Renewable Energy, Elsevier, vol. 149(C), pages 861-876.
    13. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.
    14. Dongbum Kang & Kyungnam Ko & Jongchul Huh, 2018. "Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea," Energies, MDPI, vol. 11(2), pages 1-19, February.
    15. Zhao, Xuejing & Wang, Chen & Su, Jinxia & Wang, Jianzhou, 2019. "Research and application based on the swarm intelligence algorithm and artificial intelligence for wind farm decision system," Renewable Energy, Elsevier, vol. 134(C), pages 681-697.
    16. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    17. Suwarno Suwarno & M. Fitra Zambak, 2021. "The Probability Density Function for Wind Speed Using Modified Weibull Distribution," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 544-550.
    18. Basir Khan, M. Reyasudin & Jidin, Razali & Pasupuleti, Jagadeesh & Shaaya, Sharifah Azwa, 2015. "Optimal combination of solar, wind, micro-hydro and diesel systems based on actual seasonal load profiles for a resort island in the South China Sea," Energy, Elsevier, vol. 82(C), pages 80-97.
    19. Guedes, Kevin S. & de Andrade, Carla F. & Rocha, Paulo A.C. & Mangueira, Rivanilso dos S. & de Moura, Elineudo P., 2020. "Performance analysis of metaheuristic optimization algorithms in estimating the parameters of several wind speed distributions," Applied Energy, Elsevier, vol. 268(C).
    20. Mehr Gul & Nengling Tai & Wentao Huang & Muhammad Haroon Nadeem & Moduo Yu, 2019. "Assessment of Wind Power Potential and Economic Analysis at Hyderabad in Pakistan: Powering to Local Communities Using Wind Power," Sustainability, MDPI, vol. 11(5), pages 1-23, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:69:y:2017:i:c:p:1199-1217. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.