Pub Date : 2024-03-22DOI: 10.1177/0309524x241238353
A. Rangaraj, Y. Srinath, K. Boopathi, R. D M, Sushanth Kumar
The performance of numerical weather prediction models has improved dramatically recently. However, model biases remain a fundamental limitation prohibiting the direct implementation of model results. There are several ways to describe wind speed data. The Weibull and lognormal distributions are used to obtain the best-fit model for the wind speed data. This study aims to develop a statistical post-processing method based on the distribution-based scaling (DBS) approach, which scales NWP data to fit the distribution derived using recorded wind speed at that site location. The performance of the suggested method was evaluated using four different error measures. The optimal model is anticipated to have the lowest Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean square Error (RMSE), and variance (s2) values. It was determined that employing a DBS strategy significantly improved the NWP by at least 75%.
{"title":"Statistical post-processing of numerical weather prediction data using distribution-based scaling for wind energy","authors":"A. Rangaraj, Y. Srinath, K. Boopathi, R. D M, Sushanth Kumar","doi":"10.1177/0309524x241238353","DOIUrl":"https://doi.org/10.1177/0309524x241238353","url":null,"abstract":"The performance of numerical weather prediction models has improved dramatically recently. However, model biases remain a fundamental limitation prohibiting the direct implementation of model results. There are several ways to describe wind speed data. The Weibull and lognormal distributions are used to obtain the best-fit model for the wind speed data. This study aims to develop a statistical post-processing method based on the distribution-based scaling (DBS) approach, which scales NWP data to fit the distribution derived using recorded wind speed at that site location. The performance of the suggested method was evaluated using four different error measures. The optimal model is anticipated to have the lowest Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean square Error (RMSE), and variance (s2) values. It was determined that employing a DBS strategy significantly improved the NWP by at least 75%.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140218698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-12DOI: 10.1177/0309524x241227432
A. Yahiaoui, A. Tlemçani, Omar Labbadlia
Renewable energy technologies offer the promise of clean and abundant energy harvested from natural resources, self-renewable sources such as sun, wind, water, earth, and plants. In this work, we optimize the hybrid system using Homer power program, where the hybrid system is composed by solar panels, wind turbines with batteries to supply 20 homes that are not equipped with electricity in Ouzera area (Medea, Algeria), and by taking the results presented by the Homer program for Ouzera region, we obtained the cost of each day, of each season and the cost of energy ($/kWh), as well as the optimal number and characteristics for each solar panels and wind turbines with storage batteries. The homer software allows us to obtain real results in taking into account the constraints cost and variations in off-grid weather data. The most important criterion of this technique for optimizing renewable energy systems was the cost, seeking to minimize the expenses, while ensuring optimum quality and continuity of electricity supply.
可再生能源技术提供了从自然资源（如太阳、风、水、土地和植物）中获取清洁、丰富能源的希望。在这项工作中，我们使用荷马电力程序对混合系统进行了优化，混合系统由太阳能电池板、带蓄电池的风力涡轮机组成，为乌泽拉地区（阿尔及利亚梅迪亚）的 20 户无电力供应的家庭供电。通过荷马程序为乌泽拉地区提供的结果，我们获得了每天、每个季节的成本和能源成本（美元/千瓦时），以及每块太阳能电池板和带蓄电池的风力涡轮机的最佳数量和特性。通过 homer 软件，我们可以在考虑成本限制和离网天气数据变化的情况下获得真实结果。这种优化可再生能源系统的技术最重要的标准是成本，力求在确保最佳供电质量和连续性的同时，最大限度地减少开支。
{"title":"Development of an intelligent solution for the optimization of a hybrid system using renewable energy sources","authors":"A. Yahiaoui, A. Tlemçani, Omar Labbadlia","doi":"10.1177/0309524x241227432","DOIUrl":"https://doi.org/10.1177/0309524x241227432","url":null,"abstract":"Renewable energy technologies offer the promise of clean and abundant energy harvested from natural resources, self-renewable sources such as sun, wind, water, earth, and plants. In this work, we optimize the hybrid system using Homer power program, where the hybrid system is composed by solar panels, wind turbines with batteries to supply 20 homes that are not equipped with electricity in Ouzera area (Medea, Algeria), and by taking the results presented by the Homer program for Ouzera region, we obtained the cost of each day, of each season and the cost of energy ($/kWh), as well as the optimal number and characteristics for each solar panels and wind turbines with storage batteries. The homer software allows us to obtain real results in taking into account the constraints cost and variations in off-grid weather data. The most important criterion of this technique for optimizing renewable energy systems was the cost, seeking to minimize the expenses, while ensuring optimum quality and continuity of electricity supply.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140250427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-05DOI: 10.1177/0309524x241229403
Arefe Shalbafian, S. Ganjefar
In this article, we propose a novel robust nonlinear optimal second-order sliding mode controller using the homotopy perturbation method (RNOSOSMC-HPM) to maximize wind power capture and minimize the mechanical stress on the drive train. To design the nonlinear optimal controller, the homotopy perturbation method (HPM) is applied to compute the approximate solution of the partial differential Hamilton-Jacobi-Bellman (HJB) equation. Next, the nonlinear optimal controller is combined with a second-order sliding mode controller to create robustness and eliminate chattering. The RNOSOSMC-HPM controller can provide safe wind turbine operation under uncertainties and create a good trade-off between maximizing the wind power captured and attenuating the mechanical loads by minimizing the control input. To investigate the effectiveness of the presented the RNOSOSMC-HPM controller, we compare the results of the proposed method with some existing control schemes in two different scenarios. The results indicate that the RNOSOSMC-HPM controller furnishes desired responses.
{"title":"A novel robust nonlinear optimal second-order sliding mode control scheme for power optimization of wind energy conversion systems","authors":"Arefe Shalbafian, S. Ganjefar","doi":"10.1177/0309524x241229403","DOIUrl":"https://doi.org/10.1177/0309524x241229403","url":null,"abstract":"In this article, we propose a novel robust nonlinear optimal second-order sliding mode controller using the homotopy perturbation method (RNOSOSMC-HPM) to maximize wind power capture and minimize the mechanical stress on the drive train. To design the nonlinear optimal controller, the homotopy perturbation method (HPM) is applied to compute the approximate solution of the partial differential Hamilton-Jacobi-Bellman (HJB) equation. Next, the nonlinear optimal controller is combined with a second-order sliding mode controller to create robustness and eliminate chattering. The RNOSOSMC-HPM controller can provide safe wind turbine operation under uncertainties and create a good trade-off between maximizing the wind power captured and attenuating the mechanical loads by minimizing the control input. To investigate the effectiveness of the presented the RNOSOSMC-HPM controller, we compare the results of the proposed method with some existing control schemes in two different scenarios. The results indicate that the RNOSOSMC-HPM controller furnishes desired responses.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.1177/0309524x241232158
Rui Yin, Jian-Bin Xie, Ji Yao
This study assesses the impact of three morphed trailing-edge flap (MTEF) parameters (flap deflection angle β, flap length b, and flap span length l) on increasing power and axial thrust coefficients and their comprehensive effect on wind turbines using computational fluid dynamics (CFD) method. The detailed analysis is performed on seven morphed blades at eight different wind velocities. The obtained results show that β results in the largest unit power coefficient increase rate and unit axial thrust coefficient increase rate, while l results in the smallest ones. In addition, b results in the largest power-thrust ratio increase rate. The optimum blade is achieved for β = 3°, b/ c = 0.3, and l/ R = 0.3, which results in additional power increase of 15.24% and axial thrust increase of 9.53% at a tip speed ratio of 5.949, compared with the original wind turbine.
本研究使用计算流体动力学（CFD）方法评估了三个变形尾翼（MTEF）参数（襟翼偏转角 β、襟翼长度 b 和襟翼跨度长度 l）对增加功率和轴向推力系数的影响及其对风力涡轮机的综合影响。详细分析是在八个不同风速下对七个变形叶片进行的。结果表明，β 导致的单位功率系数增加率和单位轴向推力系数增加率最大，而 l 导致的单位功率系数增加率和单位轴向推力系数增加率最小。此外，b 的功率-推力比增长率最大。当 β = 3°、b/ c = 0.3 和 l/ R = 0.3 时，叶片达到最佳状态，与原始风力涡轮机相比，在叶尖速比为 5.949 时，功率增加了 15.24%，轴向推力增加了 9.53%。
{"title":"Effects of the morphed trailing-edge flap parameters on the aerodynamic performance of NREL Phase II wind turbine","authors":"Rui Yin, Jian-Bin Xie, Ji Yao","doi":"10.1177/0309524x241232158","DOIUrl":"https://doi.org/10.1177/0309524x241232158","url":null,"abstract":"This study assesses the impact of three morphed trailing-edge flap (MTEF) parameters (flap deflection angle β, flap length b, and flap span length l) on increasing power and axial thrust coefficients and their comprehensive effect on wind turbines using computational fluid dynamics (CFD) method. The detailed analysis is performed on seven morphed blades at eight different wind velocities. The obtained results show that β results in the largest unit power coefficient increase rate and unit axial thrust coefficient increase rate, while l results in the smallest ones. In addition, b results in the largest power-thrust ratio increase rate. The optimum blade is achieved for β = 3°, b/ c = 0.3, and l/ R = 0.3, which results in additional power increase of 15.24% and axial thrust increase of 9.53% at a tip speed ratio of 5.949, compared with the original wind turbine.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140416207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-21DOI: 10.1177/0309524x241229405
Luis Felipe Quesada-Bedoya, Jonathan Sandoval-Guerrero, Santiago Bernal-Del Ro, Ricardo Mejía-Gutiérrez, G. Osorio-Gómez
In the domain of Horizontal Wind Turbines, the key role of blade material and process selection is discussed. Existing methodologies and manual manufacturing processes, while addressing this issue, suffer from complexity and environmental drawbacks. To mitigate these issues, the study introduces a comprehensive methodology for the selection, implementation, testing and analysis of materials and processes for small blade construction, taking into account various constraints. The research conducts a thorough exploration of manufacturing processes, considering factors such as time, affordability, machine accessibility, repeatability, elements to be manufactured, and adaptability to complex surfaces. A systematic comparison of materials and processes, along with proposed filtering methods, reveals that rotomolding/polyurethane casting exhibits superior performance due to improved energy capture and inertia. The study underscores the importance of careful material and process selection to optimize blade efficiency and highlights the need for further research to address mechanical, economic, environmental, scalability, and material advancement challenges.
{"title":"Exploration of bioinspired small wind turbine blade manufacturing alternatives: Defining materials and processes","authors":"Luis Felipe Quesada-Bedoya, Jonathan Sandoval-Guerrero, Santiago Bernal-Del Ro, Ricardo Mejía-Gutiérrez, G. Osorio-Gómez","doi":"10.1177/0309524x241229405","DOIUrl":"https://doi.org/10.1177/0309524x241229405","url":null,"abstract":"In the domain of Horizontal Wind Turbines, the key role of blade material and process selection is discussed. Existing methodologies and manual manufacturing processes, while addressing this issue, suffer from complexity and environmental drawbacks. To mitigate these issues, the study introduces a comprehensive methodology for the selection, implementation, testing and analysis of materials and processes for small blade construction, taking into account various constraints. The research conducts a thorough exploration of manufacturing processes, considering factors such as time, affordability, machine accessibility, repeatability, elements to be manufactured, and adaptability to complex surfaces. A systematic comparison of materials and processes, along with proposed filtering methods, reveals that rotomolding/polyurethane casting exhibits superior performance due to improved energy capture and inertia. The study underscores the importance of careful material and process selection to optimize blade efficiency and highlights the need for further research to address mechanical, economic, environmental, scalability, and material advancement challenges.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140444243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-19DOI: 10.1177/0309524x231216398
M. Ouria, Pedro S Moura, Aníbal T. de Almeida
This paper investigates the decarbonization of Tabriz-City focusing on its wind power for electrification. Statistical, quantitative, comparative, and simulation-research-methods used to analyze the existing and future total energy consumption, demand, and cost in the city according to carbon-based and wind-based electricity. The Monte Carlo Simulation Method has been used to estimate the probability of the Levelized Cost of Electricity. Tabriz thermal power plant generates 1kWh electricity that costs 0.15 US$/kW without subsidies and produces 575 g.CO2/kW.h overall while it will plunge to 0.05US$/kWh producing 7 g.CO2/kWh using wind. The NPV and IRR (32%) analysis show that that investment in wind-based electricity is three times cheaper than thermal power electricity in Tabriz. It is shown that the electrification of an oil-based economy with wind-based power plants is an economical investment for the city. Besides the hub-height and rotor sweep area, the capacity factor is the most decisive in the productivity of the alternative turbines.
{"title":"Will wind power be cost-effective for decarbonizing the city of Tabriz-Iran, whose economy is oil-based, and how?","authors":"M. Ouria, Pedro S Moura, Aníbal T. de Almeida","doi":"10.1177/0309524x231216398","DOIUrl":"https://doi.org/10.1177/0309524x231216398","url":null,"abstract":"This paper investigates the decarbonization of Tabriz-City focusing on its wind power for electrification. Statistical, quantitative, comparative, and simulation-research-methods used to analyze the existing and future total energy consumption, demand, and cost in the city according to carbon-based and wind-based electricity. The Monte Carlo Simulation Method has been used to estimate the probability of the Levelized Cost of Electricity. Tabriz thermal power plant generates 1kWh electricity that costs 0.15 US$/kW without subsidies and produces 575 g.CO2/kW.h overall while it will plunge to 0.05US$/kWh producing 7 g.CO2/kWh using wind. The NPV and IRR (32%) analysis show that that investment in wind-based electricity is three times cheaper than thermal power electricity in Tabriz. It is shown that the electrification of an oil-based economy with wind-based power plants is an economical investment for the city. Besides the hub-height and rotor sweep area, the capacity factor is the most decisive in the productivity of the alternative turbines.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-19DOI: 10.1177/0309524x241229206
Mokhtar Abid, M. Belazzoug, Souhil Mouassa, Abdallah Chanane, F. Jurado
In the current century, electrical networks have witnessed great developments and continuous increases in the demand for fossil fuels based energy, leading to an excessive rise in the total production cost (TPC), as well as the pollutant (toxic) gases emitted by thermal plants. Under this circumstances, energy supply from different resources became necessary, such as renewable energy sources (RES) as an alternative solution. This latter, however, characterized with uncertainty nature in its operation principle, especially when operator system wants to define the optimal contribution of each resource in an effort to ensure economic and enhanced reliability of grid. This paper presents an Enhanced version of Kepler optimization algorithm (EKOA) to solve the problem of stochastic optimal power flow (SOPF) in a most efficient way incorporating wind power generators and solar photovoltaic with different objective functions, the stochastic nature of wind speed and solar is modeled using Weibull and lognormal probability density functions respectively. To prove the effectiveness of the proposed EKOA, various case studies were carried out on two test systems IEEE 30-bus system and Algerian power system 114-bus, obtained results were evaluated in comparison with those obtained using the original KOA and other methods published in the literatures. Thus, shows the effectiveness and superiority of the efficient EKOA over other optimizers to solve complex problem. The incorporation of RES resulted in a significant 2.39% decrease in production cost, showcasing EKOA’s efficiency with a $780/h, compared to KOA’s $781/h, for IEEE 30-bus system. For the DZA 114-bus system revealed even more substantial reductions, with EKOA achieving an impressive 12.6% reduction, and KOA following closely with a 12.4% decrease in production cost.
{"title":"Optimal power flow of thermal-wind-solar power system using enhanced Kepler optimization algorithm: Case study of a large-scale practical power system","authors":"Mokhtar Abid, M. Belazzoug, Souhil Mouassa, Abdallah Chanane, F. Jurado","doi":"10.1177/0309524x241229206","DOIUrl":"https://doi.org/10.1177/0309524x241229206","url":null,"abstract":"In the current century, electrical networks have witnessed great developments and continuous increases in the demand for fossil fuels based energy, leading to an excessive rise in the total production cost (TPC), as well as the pollutant (toxic) gases emitted by thermal plants. Under this circumstances, energy supply from different resources became necessary, such as renewable energy sources (RES) as an alternative solution. This latter, however, characterized with uncertainty nature in its operation principle, especially when operator system wants to define the optimal contribution of each resource in an effort to ensure economic and enhanced reliability of grid. This paper presents an Enhanced version of Kepler optimization algorithm (EKOA) to solve the problem of stochastic optimal power flow (SOPF) in a most efficient way incorporating wind power generators and solar photovoltaic with different objective functions, the stochastic nature of wind speed and solar is modeled using Weibull and lognormal probability density functions respectively. To prove the effectiveness of the proposed EKOA, various case studies were carried out on two test systems IEEE 30-bus system and Algerian power system 114-bus, obtained results were evaluated in comparison with those obtained using the original KOA and other methods published in the literatures. Thus, shows the effectiveness and superiority of the efficient EKOA over other optimizers to solve complex problem. The incorporation of RES resulted in a significant 2.39% decrease in production cost, showcasing EKOA’s efficiency with a $780/h, compared to KOA’s $781/h, for IEEE 30-bus system. For the DZA 114-bus system revealed even more substantial reductions, with EKOA achieving an impressive 12.6% reduction, and KOA following closely with a 12.4% decrease in production cost.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140451213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.1177/0309524x231225965
Badr El Kihel, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali
This document delves into evaluating wind power potential within Morocco’s Oriental region, encompassing an extensive study of 23 locations over 43 years. The analysis was conducted using the advanced MERRA2 data reanalysis system coupled with MATLAB software. Our comprehensive study aims to map the wind energy capabilities across these sites. We employed eight distinct algorithms to adapt the Weibull distribution for the wind speed data. Additionally, the research includes an analysis of the wind rose and assesses the Capacity Factor ([Formula: see text]) to determine the most efficient periods for wind energy production. Our findings highlight that sites S4, S7, and S11 create an ideal geographic formation for wind farm placement. Within this formation, site S8, boasting a ([Formula: see text]) of 36.97%, emerges as a critical location, especially when paired with the EWT DW54 500 wind turbine model. This investigation opens new avenues for advancing wind energy in the region.
{"title":"Evaluation of Weibull parameters for wind energy analysis in the eastern region of the Kingdom of Morocco","authors":"Badr El Kihel, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali","doi":"10.1177/0309524x231225965","DOIUrl":"https://doi.org/10.1177/0309524x231225965","url":null,"abstract":"This document delves into evaluating wind power potential within Morocco’s Oriental region, encompassing an extensive study of 23 locations over 43 years. The analysis was conducted using the advanced MERRA2 data reanalysis system coupled with MATLAB software. Our comprehensive study aims to map the wind energy capabilities across these sites. We employed eight distinct algorithms to adapt the Weibull distribution for the wind speed data. Additionally, the research includes an analysis of the wind rose and assesses the Capacity Factor ([Formula: see text]) to determine the most efficient periods for wind energy production. Our findings highlight that sites S4, S7, and S11 create an ideal geographic formation for wind farm placement. Within this formation, site S8, boasting a ([Formula: see text]) of 36.97%, emerges as a critical location, especially when paired with the EWT DW54 500 wind turbine model. This investigation opens new avenues for advancing wind energy in the region.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139833666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.1177/0309524x231225965
Badr El Kihel, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali
This document delves into evaluating wind power potential within Morocco’s Oriental region, encompassing an extensive study of 23 locations over 43 years. The analysis was conducted using the advanced MERRA2 data reanalysis system coupled with MATLAB software. Our comprehensive study aims to map the wind energy capabilities across these sites. We employed eight distinct algorithms to adapt the Weibull distribution for the wind speed data. Additionally, the research includes an analysis of the wind rose and assesses the Capacity Factor ([Formula: see text]) to determine the most efficient periods for wind energy production. Our findings highlight that sites S4, S7, and S11 create an ideal geographic formation for wind farm placement. Within this formation, site S8, boasting a ([Formula: see text]) of 36.97%, emerges as a critical location, especially when paired with the EWT DW54 500 wind turbine model. This investigation opens new avenues for advancing wind energy in the region.
{"title":"Evaluation of Weibull parameters for wind energy analysis in the eastern region of the Kingdom of Morocco","authors":"Badr El Kihel, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali","doi":"10.1177/0309524x231225965","DOIUrl":"https://doi.org/10.1177/0309524x231225965","url":null,"abstract":"This document delves into evaluating wind power potential within Morocco’s Oriental region, encompassing an extensive study of 23 locations over 43 years. The analysis was conducted using the advanced MERRA2 data reanalysis system coupled with MATLAB software. Our comprehensive study aims to map the wind energy capabilities across these sites. We employed eight distinct algorithms to adapt the Weibull distribution for the wind speed data. Additionally, the research includes an analysis of the wind rose and assesses the Capacity Factor ([Formula: see text]) to determine the most efficient periods for wind energy production. Our findings highlight that sites S4, S7, and S11 create an ideal geographic formation for wind farm placement. Within this formation, site S8, boasting a ([Formula: see text]) of 36.97%, emerges as a critical location, especially when paired with the EWT DW54 500 wind turbine model. This investigation opens new avenues for advancing wind energy in the region.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139774174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.1177/0309524x241229169
Mujahid Shaik, Balaji Subramanian
A computational investigation of New MEXICO test cases operating under axial flow conditions is reported. Three wind speed cases (10, 15, 24 m/s) corresponding to three different tip speed ratios (10, 6.67, 4.17) when the turbine operates at 425.1 rpm were considered. ANSYS CFX 2021R1 was employed to perform simulations using Single Reference Frame (SRF) and Multiple Reference Frame (MRF) approaches. The flow field is computed by solving unsteady Reynolds Averaged Navier-Stokes (uRANS) equations coupled with SST k-ω turbulence model and Gamma-Theta transition model. Validation involved comparing CFD-predicted integral quantities, static pressure distributions, and loads with corresponding experimental values demonstrating reasonably good agreement at all three wind speeds. Overall, SRF exhibited slightly better wake predictions (hypothetical), while MRF predictions were closer to measurements for integral quantities, static pressure and loads. This study demonstrates the utility of uRANS-based 3D CFD computations in wind turbine aerodynamics studies.
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