Pub Date : 2023-04-10DOI: 10.1177/0309524X231162638
Zhaoliang Guo, Li Xu, Guanhao Zhou, Kaijun Zhang
Wind farm wake modeling is of great significance for wind turbine layout optimization design and yaw control strategy. In this work, we combine deep neural network (DNN) with spectral proper orthogonal decomposition (SPOD) to discover dynamic characteristics of wake under different inflow conditions. Then an assessment of the proposed SPOD-DNN surrogate modeling method of parameterized fluid is performed by comparing the predicted results. Meanwhile, we demonstrate the robustness of the SPOD-DNN through a comparison with POD-DNN, where SPOD produces fewer modes than POD but can achieve the same cumulative contribution rate and wake prediction accuracy. In the end, the method is developed to predict the wake of single wind turbine in untrained inflow condition and Wake of six wind turbines with different yaw angles. The results reveals that the model has good generalization performance and can robustly reconstruct the wake of multiple wind turbines in different directions.
{"title":"A non-intrusive reduced-order model for wind farm wake analysis based on SPOD-DNN","authors":"Zhaoliang Guo, Li Xu, Guanhao Zhou, Kaijun Zhang","doi":"10.1177/0309524X231162638","DOIUrl":"https://doi.org/10.1177/0309524X231162638","url":null,"abstract":"Wind farm wake modeling is of great significance for wind turbine layout optimization design and yaw control strategy. In this work, we combine deep neural network (DNN) with spectral proper orthogonal decomposition (SPOD) to discover dynamic characteristics of wake under different inflow conditions. Then an assessment of the proposed SPOD-DNN surrogate modeling method of parameterized fluid is performed by comparing the predicted results. Meanwhile, we demonstrate the robustness of the SPOD-DNN through a comparison with POD-DNN, where SPOD produces fewer modes than POD but can achieve the same cumulative contribution rate and wake prediction accuracy. In the end, the method is developed to predict the wake of single wind turbine in untrained inflow condition and Wake of six wind turbines with different yaw angles. The results reveals that the model has good generalization performance and can robustly reconstruct the wake of multiple wind turbines in different directions.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"18 1","pages":"852 - 866"},"PeriodicalIF":1.5,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90691567","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 : 2023-04-01DOI: 10.1177/0309524X231165480
S. Tounsi
This paper presents an average model based on justified simplifications dedicated to the design and optimization of wind energy systems. Indeed, the classic models of wind energy systems are complex and their use is not efficient for the optimal design of the components of the power chain given the complexity, the significant time of resolution and the strong correlation of the physical parameters of these models. For these reasons, a model based on the theory of average values with reduced simulation time of a wind turbine structure is developed. This model is validated against the classic model of the wind chain using the SimPowerSystem library of power component models integrated under the Matlab-Simulink simulation environment.
{"title":"Average model of wind energy system dedicated to optimal design of the global system","authors":"S. Tounsi","doi":"10.1177/0309524X231165480","DOIUrl":"https://doi.org/10.1177/0309524X231165480","url":null,"abstract":"This paper presents an average model based on justified simplifications dedicated to the design and optimization of wind energy systems. Indeed, the classic models of wind energy systems are complex and their use is not efficient for the optimal design of the components of the power chain given the complexity, the significant time of resolution and the strong correlation of the physical parameters of these models. For these reasons, a model based on the theory of average values with reduced simulation time of a wind turbine structure is developed. This model is validated against the classic model of the wind chain using the SimPowerSystem library of power component models integrated under the Matlab-Simulink simulation environment.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"83 1","pages":"821 - 832"},"PeriodicalIF":1.5,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78238445","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 : 2023-04-01DOI: 10.1177/0309524X231165484
Md Imran Hasan Tusar, B. Sarker
Offshore wind turbines can capture more wind than onshore because of their larger structure and location. This higher yield even fails to reduce the high installation and maintenance cost of an offshore wind farm (OWF). Appropriate turbine parameters and installation site selection may maximize the power generation which is a way to trade off these costs. Knowing the wind thrust force, air density, and power coefficient beforehand can help select an appropriate site for turbine location. Once the site is selected, the optimal value of turbine variables such as height and radius can contribute to higher power yield. In this paper, a MINLP (Mixed Integer Non-Linear Programing) model is formulated with these important variables and the optimal values of these variables are determined to maximize the annual power production ( E prod ) from offshore wind farm. The estimated power production, E prod , is calculated using two methods, mathematical programing method and simulation method. Computational result indicates that mathematical programing method is time consuming but more accurate whereas the accuracy of simulation method is proportional to the number of iterations. Although the result of a simulation can be improved to some extent, it cannot be as accurate as mathematical modeling for this study. These study results have great impact on the managerial decision and long range strategic and technical planning for maximizing power generation from an offshore wind farm.
{"title":"Location and turbine parameter selection for offshore wind power maximization","authors":"Md Imran Hasan Tusar, B. Sarker","doi":"10.1177/0309524X231165484","DOIUrl":"https://doi.org/10.1177/0309524X231165484","url":null,"abstract":"Offshore wind turbines can capture more wind than onshore because of their larger structure and location. This higher yield even fails to reduce the high installation and maintenance cost of an offshore wind farm (OWF). Appropriate turbine parameters and installation site selection may maximize the power generation which is a way to trade off these costs. Knowing the wind thrust force, air density, and power coefficient beforehand can help select an appropriate site for turbine location. Once the site is selected, the optimal value of turbine variables such as height and radius can contribute to higher power yield. In this paper, a MINLP (Mixed Integer Non-Linear Programing) model is formulated with these important variables and the optimal values of these variables are determined to maximize the annual power production ( E prod ) from offshore wind farm. The estimated power production, E prod , is calculated using two methods, mathematical programing method and simulation method. Computational result indicates that mathematical programing method is time consuming but more accurate whereas the accuracy of simulation method is proportional to the number of iterations. Although the result of a simulation can be improved to some extent, it cannot be as accurate as mathematical modeling for this study. These study results have great impact on the managerial decision and long range strategic and technical planning for maximizing power generation from an offshore wind farm.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"40 1","pages":"833 - 851"},"PeriodicalIF":1.5,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81376670","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 : 2023-03-29DOI: 10.1177/0309524X231163823
Cheng Zhong, Husai Wang, Zhifu Jiang, Dechi Tian
This paper proposed a unified active power optimization control of wind farms under wake effect. It takes the sum of the kinetic energy variation and pitch angle variation as the optimization objective and used the particle swarm algorithm to achieve the optimization results. The main feature of the proposed method is that it unifies the kinetic energy optimization under a low wind speed area, the pitch angle and kinetic energy trade-off optimization under a medium wind speed area, and the pitch angle optimization under a high wind speed area. Combined with the de-loaded power constraint, it can flexibly reach various optimal operating states of the wind farm. The simulation results show that the proposed method optimizes the rotor speed and pitch angle in different wind speed areas, and releases kinetic energy and/or increases the output power of the wind farm to provide frequency support by switching the operating states.
{"title":"A unified optimization control of wind farms considering wake effect for grid frequency support","authors":"Cheng Zhong, Husai Wang, Zhifu Jiang, Dechi Tian","doi":"10.1177/0309524X231163823","DOIUrl":"https://doi.org/10.1177/0309524X231163823","url":null,"abstract":"This paper proposed a unified active power optimization control of wind farms under wake effect. It takes the sum of the kinetic energy variation and pitch angle variation as the optimization objective and used the particle swarm algorithm to achieve the optimization results. The main feature of the proposed method is that it unifies the kinetic energy optimization under a low wind speed area, the pitch angle and kinetic energy trade-off optimization under a medium wind speed area, and the pitch angle optimization under a high wind speed area. Combined with the de-loaded power constraint, it can flexibly reach various optimal operating states of the wind farm. The simulation results show that the proposed method optimizes the rotor speed and pitch angle in different wind speed areas, and releases kinetic energy and/or increases the output power of the wind farm to provide frequency support by switching the operating states.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"47 1","pages":"783 - 798"},"PeriodicalIF":1.5,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86931695","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 : 2023-03-29DOI: 10.1177/0309524X231163825
S. Mozafari, K. Dykes, J. Rinker, P. Veers
The variability of the wind turbine loads complicates fatigue assessment in the design phase, as performing simulations covering the entire lifetime is computationally expensive. The current work provides important information for assessing the uncertainty in fatigue damage estimation due to finite data. We study the sample size effect on mean, variance, and skewness of damage in each wind bin, identify the important wind bins, and study the uncertainty propagation from each wind bin to the lifetime damage using 3600 aeroelastic simulations and bootstrapping. To achieve less than 1% error in the damage estimation across all load channels in the current case study, at least 100 turbulence seeds are needed. Damage in different wind bins follows a lognormal distribution when using the conventional approach of six seeds. The provided insights and information allow the designer to achieve a specific level of accuracy for a given computational cost using strategic bin sampling.
{"title":"Effects of finite sampling on fatigue damage estimation of wind turbine components: A statistical study","authors":"S. Mozafari, K. Dykes, J. Rinker, P. Veers","doi":"10.1177/0309524X231163825","DOIUrl":"https://doi.org/10.1177/0309524X231163825","url":null,"abstract":"The variability of the wind turbine loads complicates fatigue assessment in the design phase, as performing simulations covering the entire lifetime is computationally expensive. The current work provides important information for assessing the uncertainty in fatigue damage estimation due to finite data. We study the sample size effect on mean, variance, and skewness of damage in each wind bin, identify the important wind bins, and study the uncertainty propagation from each wind bin to the lifetime damage using 3600 aeroelastic simulations and bootstrapping. To achieve less than 1% error in the damage estimation across all load channels in the current case study, at least 100 turbulence seeds are needed. Damage in different wind bins follows a lognormal distribution when using the conventional approach of six seeds. The provided insights and information allow the designer to achieve a specific level of accuracy for a given computational cost using strategic bin sampling.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"55 1","pages":"799 - 820"},"PeriodicalIF":1.5,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82649539","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 : 2023-03-25DOI: 10.1177/0309524X231158707
L. Saihi, B. Berbaoui, F. Ferroudji, Y. Bakou, Elhassen Benfriha
The current study proposed a robust sensor-less sliding mode second-order based on a super twisting algorithm (STA-SMSO) approach using a new observer Model Reference Adaptive System-Adaptative Neuro-Fuzzy Inference System (MRAS-ANFIS). This model was applied to a doubly fed induction generator (DFIG) wind turbine running under variable wind speed and DFIG fed with a power voltage source without a speed sensor, while the control objective was used to regulate independently, the active and reactive power DFIG stator were decoupled by using the field-oriented control technique. Additionally, this process reduced the cost of the control scheme and the size of DFIG by eliminating the speed sensor (encoder). In order to improve the traditional MRAS, the MRAS-ANFIS observer was proposed to replace the usual PI controller in the adaptation mechanism of MRAS with an Adaptative Neuro-Fuzzy Inference System (ANFIS) controller. The estimation of rotor position was tested and discussed under varying load conditions in low, zero, and high-speed region. The results mentioned that the proposed observer (MRAS-ANFIS) presented an attractive feature, such as guarantees finite time convergence, good response on speed wind variations, high robustness against machine parameter variations, and load variations compared to the conventional MRAS observer and MRAS-Fuzzy. Hence, the estimated rotor speed converged to their actual value has the capacity for estimating position in deferent region (low/zero/high) of speed.
{"title":"Robust sensor-less sliding mode of second-order control of doubly fed induction generators in variable speed wind turbine systems based on a novel MRAS-ANFIS observer","authors":"L. Saihi, B. Berbaoui, F. Ferroudji, Y. Bakou, Elhassen Benfriha","doi":"10.1177/0309524X231158707","DOIUrl":"https://doi.org/10.1177/0309524X231158707","url":null,"abstract":"The current study proposed a robust sensor-less sliding mode second-order based on a super twisting algorithm (STA-SMSO) approach using a new observer Model Reference Adaptive System-Adaptative Neuro-Fuzzy Inference System (MRAS-ANFIS). This model was applied to a doubly fed induction generator (DFIG) wind turbine running under variable wind speed and DFIG fed with a power voltage source without a speed sensor, while the control objective was used to regulate independently, the active and reactive power DFIG stator were decoupled by using the field-oriented control technique. Additionally, this process reduced the cost of the control scheme and the size of DFIG by eliminating the speed sensor (encoder). In order to improve the traditional MRAS, the MRAS-ANFIS observer was proposed to replace the usual PI controller in the adaptation mechanism of MRAS with an Adaptative Neuro-Fuzzy Inference System (ANFIS) controller. The estimation of rotor position was tested and discussed under varying load conditions in low, zero, and high-speed region. The results mentioned that the proposed observer (MRAS-ANFIS) presented an attractive feature, such as guarantees finite time convergence, good response on speed wind variations, high robustness against machine parameter variations, and load variations compared to the conventional MRAS observer and MRAS-Fuzzy. Hence, the estimated rotor speed converged to their actual value has the capacity for estimating position in deferent region (low/zero/high) of speed.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"155 1","pages":"766 - 782"},"PeriodicalIF":1.5,"publicationDate":"2023-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88705106","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 : 2023-02-17DOI: 10.1177/0309524X231154841
Anupam Kumar, Arun Rathore, S. Singh, A. H. Bhat
In this paper an islanded microgrid fed through the wind and solar energy resources is presented. The power flow within the microgrid is controlled using a Neutral Point Clamped Dual Active Bridge (NPC-DAB) converter. In the proposed dc microgrid, the solar energy source is associated at the low voltage (LV) bus and the wind energy source is connected at the high voltage (HV) bus. A permanent magnet synchronous generator (PMSG) machine is used in wind energy conversion system. The real time solar radiation and wind speed data of Rupangarh, Rajasthan, India is used as an input for renewable energy resource. The NPC-DAB will work as a power electronics juncture for expediting the energy exchange in the islanded DC Microgrid. The proposed closed loop controller based on the capacitor voltage and load voltage will expedite a complete automatic operation of the islanded DC-microgrid considering various load changes. The system is studied without storage element as the automatic control of energy generation and load feeding is carried out by the NPC-DAB, also this makes the scheme cost effective. The optimum duty ratios for NPC-DAB operation are obtained and thus the increased load demand is met. The modeling of PMSG, NPC-DAB and wind energy system is discussed in details in this work. The proposed system is studied in MATLAB/Simulink environment and results are obtained for different load variations. All the wind control parameters, NPC-DAB waveforms, load waveforms are also plotted using MATLAB.
{"title":"Modeling and control of islanded DC microgrid fed by intermittent generating resources","authors":"Anupam Kumar, Arun Rathore, S. Singh, A. H. Bhat","doi":"10.1177/0309524X231154841","DOIUrl":"https://doi.org/10.1177/0309524X231154841","url":null,"abstract":"In this paper an islanded microgrid fed through the wind and solar energy resources is presented. The power flow within the microgrid is controlled using a Neutral Point Clamped Dual Active Bridge (NPC-DAB) converter. In the proposed dc microgrid, the solar energy source is associated at the low voltage (LV) bus and the wind energy source is connected at the high voltage (HV) bus. A permanent magnet synchronous generator (PMSG) machine is used in wind energy conversion system. The real time solar radiation and wind speed data of Rupangarh, Rajasthan, India is used as an input for renewable energy resource. The NPC-DAB will work as a power electronics juncture for expediting the energy exchange in the islanded DC Microgrid. The proposed closed loop controller based on the capacitor voltage and load voltage will expedite a complete automatic operation of the islanded DC-microgrid considering various load changes. The system is studied without storage element as the automatic control of energy generation and load feeding is carried out by the NPC-DAB, also this makes the scheme cost effective. The optimum duty ratios for NPC-DAB operation are obtained and thus the increased load demand is met. The modeling of PMSG, NPC-DAB and wind energy system is discussed in details in this work. The proposed system is studied in MATLAB/Simulink environment and results are obtained for different load variations. All the wind control parameters, NPC-DAB waveforms, load waveforms are also plotted using MATLAB.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"23 1","pages":"688 - 705"},"PeriodicalIF":1.5,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83260070","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 : 2023-02-17DOI: 10.1177/0309524X231156451
Reginaldo N Silva, D. Fantini, Rafael CF Mendes, Marlos Guimarães, T. Oliveira, A. B. Brasil Junior
This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.
{"title":"Assessment of wind resource considering local turbulence based on data acquisition with SODAR","authors":"Reginaldo N Silva, D. Fantini, Rafael CF Mendes, Marlos Guimarães, T. Oliveira, A. B. Brasil Junior","doi":"10.1177/0309524X231156451","DOIUrl":"https://doi.org/10.1177/0309524X231156451","url":null,"abstract":"This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"136 1","pages":"747 - 765"},"PeriodicalIF":1.5,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89020358","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 : 2023-02-16DOI: 10.1177/0309524X231155549
H. Boudounit, M. Tarfaoui, D. Saifaoui
In the past 30 years, wind turbine blades (WTB) have undergone significant development, increasing their size and introducing composites into manufacturing processes and using numerical simulation to assess their strength and structural integrity, helped increasing the number of installed wind turbine units as well as reducing the cost of wind generated energy. In this paper a DLoad subroutine was developed to assess monitor and evaluate the structural integrity of a large wind turbine blade under numerous static load scenarios. The fatigue study was carried using the finite element method, and the DLoad subroutine developed was used with ABAQUS finite Element analysis Software, and performed perfectly. The results show that the proposed layup parameters and the chosen composite materials gives to the wind turbine the desired structural strength. Furthermore, the DLoad subroutine for the fatigue study shows that the higher is the applied force the faster the blade fail. While, Hashin Criterion shows that the distribution of damage for the matrix and the fiber is all over the blade, but the failure only occurs after reaching an energy threshold which depends on the composite materials and the layup parameters used. Therefore, the chosen layup model will allow the wind turbine blade to withstand the extreme climatic conditions in the sea.
{"title":"Fatigue analysis of wind turbine composite blade using finite element method","authors":"H. Boudounit, M. Tarfaoui, D. Saifaoui","doi":"10.1177/0309524X231155549","DOIUrl":"https://doi.org/10.1177/0309524X231155549","url":null,"abstract":"In the past 30 years, wind turbine blades (WTB) have undergone significant development, increasing their size and introducing composites into manufacturing processes and using numerical simulation to assess their strength and structural integrity, helped increasing the number of installed wind turbine units as well as reducing the cost of wind generated energy. In this paper a DLoad subroutine was developed to assess monitor and evaluate the structural integrity of a large wind turbine blade under numerous static load scenarios. The fatigue study was carried using the finite element method, and the DLoad subroutine developed was used with ABAQUS finite Element analysis Software, and performed perfectly. The results show that the proposed layup parameters and the chosen composite materials gives to the wind turbine the desired structural strength. Furthermore, the DLoad subroutine for the fatigue study shows that the higher is the applied force the faster the blade fail. While, Hashin Criterion shows that the distribution of damage for the matrix and the fiber is all over the blade, but the failure only occurs after reaching an energy threshold which depends on the composite materials and the layup parameters used. Therefore, the chosen layup model will allow the wind turbine blade to withstand the extreme climatic conditions in the sea.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"41 1","pages":"706 - 721"},"PeriodicalIF":1.5,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73901499","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 : 2023-02-13DOI: 10.1177/0309524X221150491
Man Mohan, N. Alom, U. Saha
The use of metropolitan wind power by small-scale wind turbines has become an emerging technique to reduce the battle among growing energy needs. However, the available technical designs are not yet adequate to develop a reliable and distributed wind energy converter for low wind speed conditions. The Savonius wind turbine rotor, or simply Savonius rotor, seems to be particularly promising for such conditions, however, it suffers from low power coefficient. The blade profile/shape is an important aspect of designing the Savonius rotor. In this context, the use of optimization techniques (OTs) along with soft-computing techniques (SCTs) can significantly help to arrive at the intended design parameters. The selection of rotor blades developed through OTs and SCTs can significantly improve the rotor performance. This review study aims to summarize the OTs and SCTs used till date in the blade design of Savonius rotors.
{"title":"Role of optimization and soft-computing techniques in the design and development of futuristic Savonius wind turbine blades: A review","authors":"Man Mohan, N. Alom, U. Saha","doi":"10.1177/0309524X221150491","DOIUrl":"https://doi.org/10.1177/0309524X221150491","url":null,"abstract":"The use of metropolitan wind power by small-scale wind turbines has become an emerging technique to reduce the battle among growing energy needs. However, the available technical designs are not yet adequate to develop a reliable and distributed wind energy converter for low wind speed conditions. The Savonius wind turbine rotor, or simply Savonius rotor, seems to be particularly promising for such conditions, however, it suffers from low power coefficient. The blade profile/shape is an important aspect of designing the Savonius rotor. In this context, the use of optimization techniques (OTs) along with soft-computing techniques (SCTs) can significantly help to arrive at the intended design parameters. The selection of rotor blades developed through OTs and SCTs can significantly improve the rotor performance. This review study aims to summarize the OTs and SCTs used till date in the blade design of Savonius rotors.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"111 1","pages":"722 - 744"},"PeriodicalIF":1.5,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79282917","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}
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