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Performance Evaluation of Six Methods for Estimating Weibull Distribution Parameters for Wind Energy: Applications to Three Sites in Morocco


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DOI: https://doi.org/10.15866/iremos.v16i4.22899

Abstract


Wind power offers a clean and viable solution for generating electricity, but its effective utilization demands a thorough analysis of wind characteristics and precise wind energy forecasting at the study location. In this study, wind speed distributions are examined to calculate two Weibull parameters (shape and scale) using the Matlab software, which is frequently employed for modeling and offers accurate estimates of wind resources. These parameters are derived from a year of measured wind speed data collected in El Fnidek, Dakhla, and Essouira, Morocco. Six methods are presented for estimating the Weibull parameters: the Empirical Method of Justus (EMJ), the Empirical Method of Lysen (EML), Wind Energy Pattern Factor Method (WEPFM), the Graphical method (GRAPH), Alternative Maximum Likelihood Method (AMLM), and Method of Four Moments Mixture (MFMM). The comparison of these methods is based on four scoring criteria to assess goodness-of-fit, including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Chi-square (X2), and Correlation Coefficient (R2). The results indicate that the AMLM, GRAPH, and EMJ methods are the most successful in computing Weibull parameters. Additionally, the Annual Energy Production (AEP) and the economic analysis were calculated by using RETScreen software. The wind turbine models used in this study are the Sinovel 1500/77 and the Guodian Power UP77/1500, which have been considered for the production of 60 MW of electric power from the wind energy farm installed in three cities in Morocco: Dakhla, El Fnidek, and Essouira. According to the study results, the Guodian Power UP77/1500 has higher annual production with lower installation costs, making it a more favorable option. The resource analysis highlights Dakhla as a location with good potential for wind farm deployment compared to other sites. The comprehensive assessment of wind data, Weibull parameters, and economic aspects contributes valuable insights to the field of wind energy forecasting and decision-making for renewable energy projects.
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Keywords


Weibull Parameters; Wind Power; MATLAB Software; RETScreen Software; Sinovel 1500/77; Guodian Power UP77/1500; Annual Energy Production; Economic Analysis

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References


A. Khaled Khamees et al., Mixture probability distribution functions using novel metaheuristic method in wind speed modeling, Ain Shams Engineering Journal, vol. 13, n° 3, p. 101613, May 2022.
https://doi.org/10.1016/j.asej.2021.10.008

J. Zhang, M. Zhang, X. Jiang, L. Wu, J. Qin, et Y. Li, Pair-Copula-based trivariate joint probability model of wind speed, wind direction and angle of attack, Journal of Wind Engineering and Industrial Aerodynamics, vol. 225, p. 105010, June 2022.
https://doi.org/10.1016/j.jweia.2022.105010

Zyoud, S., Zyoud, A., Abdelkader, A., Ahmed, N., Numerical Simulation for Optimization of ZnTe-Based Thin-Film Heterojunction Solar Cells with Different Metal Chalcogenide Buffer Layers Replacements: SCAPS-1D Simulation Program, (2021) International Review on Modelling and Simulations (IREMOS), 14 (2), pp. 79-88.
https://doi.org/10.15866/iremos.v14i2.19954

J. A. Carta et P. Cabrera, Optimal sizing of stand-alone wind-powered seawater reverse osmosis plants without use of massive energy storage, Applied Energy, vol. 304, p. 117888, Dec. 2021.
https://doi.org/10.1016/j.apenergy.2021.117888

N. Mrabet, C. Benzazah, et A. El Akkary, Technical Analysis and Comparative Study of three Wind Turbines for a 50MW wind farm in Laayoune City Morocco, ITM Web Conf., vol. 46, p. 01002, 2022.
https://doi.org/10.1051/itmconf/20224601002

J. Li et al., Tree-Based Risk Factor Identification and Stroke Level Prediction in Stroke Cohort Study, BioMed Research International, vol. 2023, p. 1-10, Apr. 2023.
https://doi.org/10.1155/2023/7352191

I. Lahlouh, F. Rerhrhaye, A. Elakkary, N. Sefiani, et A. Bybi, Robust LQR control based on multidimensional particle swarm optimization for enhancing the dynamic performance of poultry house system, Int. J. Dynam. Control, vol. 11, no 4, p. 1593-1608, Aug. 2023.
https://doi.org/10.1007/s40435-022-01082-5

W. Ajbar, A. Parrales, S. Silva-Martínez, A. Bassam, O. A. Jaramillo, et J. A. Hernández, Identification of the relevant input variables for predicting the parabolic trough solar collector's outlet temperature using an artificial neural network and a multiple linear regression model, Journal of Renewable and Sustainable Energy, vol. 13, no 4, p. 043701, July 2021.
https://doi.org/10.1063/5.0055992

Z. Li et X. Zhao, Buckley-James estimation of generalized additive accelerated lifetime model with ultrahigh-dimensional data, Statistical Analysis, vol. 16, no 3, p. 305-312, June 2023.
https://doi.org/10.1002/sam.11615

A. Celik, B. Sahin, E. Manay, et A. Balin, A Study Using the Hybrid Fuzzy AHP&TOPSIS Method in the Conversion of a LEED-Certified Education Building into a Nearly Zero-Energy Building in a Cold Climate, sv-jme, vol. 69, n° 5-6, p. 208-223, May 2023.
https://doi.org/10.5545/sv-jme.2023.529

M. Daş, E. Akpinar, et S. Akpinar, Modelling Wind Energy Potential in Different Regions with Different Methods, Gazi University Journal of Science, vol. 34, n° 4, p. 1128-1143, Dec. 2021.
https://doi.org/10.35378/gujs.795265

H. R. Alsamamra, S. Salah, J. A. H. Shoqeir, et A. J. Manasra, A comparative study of five numerical methods for the estimation of Weibull parameters for wind energy evaluation at Eastern Jerusalem, Palestine, Energy Reports, vol. 8, p. 4801-4810, Nov. 2022.
https://doi.org/10.1016/j.egyr.2022.03.180

O. J. Mdee, Performance evaluation of Weibull analytical methods using several empirical methods for predicting wind speed distribution, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, p. 1-24, Oct. 2020.
https://doi.org/10.1080/15567036.2020.1832161

Rerhrhaye, F., Lahlouh, I., Ennaciri, Y., Benzazah, C., Akkary, A., Sefiani, N., New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Ant Colony Optimization, (2022) International Review of Automatic Control (IREACO), 15 (3), pp. 113-121.
https://doi.org/10.15866/ireaco.v15i3.22076

M. A. Saeed, Z. Ahmed, J. Yang, et W. Zhang, An optimal approach of wind power assessment using Chebyshev metric for determining the Weibull distribution parameters, Sustainable Energy Technologies and Assessments, vol. 37, p. 100612, Feb. 2020.
https://doi.org/10.1016/j.seta.2019.100612

R. Chibante et F. Carvalho, Chibante, R., Carvalho, F., Thyristor Circuits Modelling for Fast Simulation of Controlled Rectifiers, (2022) International Review on Modelling and Simulations (IREMOS), 15 (4), pp. 214-225.
https://doi.org/10.15866/iremos.v15i4.22120

A. G. Kaplan et A. Kaplan, Determination of Weibull Coefficients for Hatay Region by Polynomial Curve Fitting in Matlab, European Journal of Science and Technology, Apr. 2022.
https://doi.org/10.31590/ejosat.1106944

A. A. Salami, S. Ouedraogo, K. M. Kodjoa, et A. S. A. Ajavona, Influence of the Random Data Sampling in Estimation of Wind Speed Resource: Case Study, Int. J. Renew. Energy Dev., vol. 11, n° 1, p. 133-143, Feb. 2022.
https://doi.org/10.14710/ijred.2022.38511

Smily, J., Sossey-Alaoui, I., Radi, B., Reliability Analysis of a Wind Turbine Blade, (2022) International Review on Modelling and Simulations (IREMOS), 15 (5), pp. 303-311.
https://doi.org/10.15866/iremos.v15i5.22374

S. Li, W. Gong, L. Wang, X. Yan, et C. Hu, Optimal power flow by means of improved adaptive differential evolution, Energy, vol. 198, p. 117314, MaY 2020.
https://doi.org/10.1016/j.energy.2020.117314

Calì, M., Cacopardo, G., Baiamonte, G., Laudani, G., Ambu, R., Efficiency Optimization in Medium Power Wind Turbines: an Innovative Mechanical Pitch Control System, (2022) International Review on Modelling and Simulations (IREMOS), 15 (6), pp. 367-373.
https://doi.org/10.15866/iremos.v15i6.23237

S. Rehman, N. Natarajan, M. Vasudevan, et L. M. Alhems, Assessment of wind energy potential across varying topographical features of Tamil Nadu, India, Energy Exploration & Exploitation, vol. 38, n° 1, p. 175-200, Jan. 2020.
https://doi.org/10.1177/0144598719875276

Dbaghi, Y., Farhat, S., Mediouni, M., Essakhi, H., Comparative Study Between Back-Stepping Control and ANN-Sliding Mode Control of DFIG-Based Wind Turbine System, (2021) International Review on Modelling and Simulations (IREMOS), 14 (4), pp. 261-271.
https://doi.org/10.15866/iremos.v14i4.19376

A. Guenoukpati, A. A. Salami, M. K. Kodjo, et K. Napo, Estimating Weibull Parameters for Wind Energy Applications using Seven Numerical Methods: Case studies of three costal sites in West Africa, IJRED, vol. 9, no 2, p. 217-226, July 2020.
https://doi.org/10.14710/ijred.9.2.217-226

I. Lahlouh, F. Rerhrhaye, A. Elakkary, N. Sefiani, et A. Bybi, A combined static output feedback-PID control for TITO process based particle swarm optimization: simulation and practical implementation for the poultry house system, Int. J. Dynam. Control, vol. 10, no 5, p. 1485-1498, Oct. 2022.
https://doi.org/10.1007/s40435-021-00882-5

A. Ouammi, R. Sacile, D. Zejli, A. Mimet, et R. Benchrifa, Sustainability of a wind power plant: Application to different Moroccan sites, Energy, vol. 35, n° 10, p. 4226-4236.
https://doi.org/10.1016/j.energy.2010.07.010

M. Sumair, T. Aized, M. M. Aslam Bhutta, F. A. Siddiqui, L. Tehreem, et A. Chaudhry, Method of Four Moments Mixture-A new approach for parametric estimation of Weibull Probability Distribution for wind potential estimation applications, Renewable Energy, vol. 191, p. 291-304, May 2022.
https://doi.org/10.1016/j.renene.2022.04.054

Y. Dagdougui, S. Berrhazi, D. Zejli, et R. Benchrifa, Artificial Neural Network Analysis of Moroccan Solar and Wind Potential and their Use in Hydrogen Production, ISESCO Journal of Science and Technology, vol. 10.

M. Wadi et W. Elmasry, Statistical analysis of wind energy potential using different estimation methods for Weibull parameters: a case study, Electr Eng, vol. 103, n° 6, p. 2573-2594, Dec. 2021.
https://doi.org/10.1007/s00202-021-01254-0

I. Lahlouh, D. Khouili, A. Elakkary, et N. Sefiani, Pareto optimality based multi-objective genetic algorithm: Application for livestock building system using an independent PID controller, Engineering and Applied Science Research, vol. 48, p. 8391, 2021.

M. A. Ehyaei, A. Mozafari, et M. H. Alibiglou, Exergy, economic & environmental (3E) analysis of inlet fogging for gas turbine power plant, Energy, p. S0360544211006700, Nov. 2011.
https://doi.org/10.1016/j.energy.2011.10.011

Elkodama, A., Ismaiel, A., Abdellatif, A., Shaaban, S., Modelling and Simulation of an Asynchronous Generator for a 5 MW Wind Turbine, (2022) International Review of Automatic Control (IREACO), 15 (5), pp. 233-241.
https://doi.org/10.15866/ireaco.v15i5.22922

Chakir, A., Tabaa, M., Moutaouakkil, F., Medromi, H., Alami, K., Control System for a Permanent Magnet Wind Turbine Using Particle Swarm Optimization and Proportional Integral Controller, (2020) International Review of Automatic Control (IREACO), 13 (5), pp. 231-243.
https://doi.org/10.15866/ireaco.v13i5.18482


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