Pub Date : 2024-07-27DOI: 10.1177/0309524x241259946
M. M. Akheel, B. Sankar, K. Boopathi, D. Reddy Prasad, N. Prabhu Shankar, N. Rajkumar
This study explores modifications to the blade airfoil cross-sections aimed at improving the efficiency of a 10 kW Bergey EXCEL horizontal axis small wind turbine. Specifically, the research focuses on altering the camber and thickness of the turbine’s baseline airfoil, designated as SG6043. Using advanced aerodynamic analysis tools like QBlade, the performance of the modified airfoils EY05-10 and EY08-9 is evaluated. The findings show that these modified airfoils achieve a higher lift-to-drag ratio compared to the baseline. These improved airfoils are then incorporated into the turbine’s blade geometry using the WT_Perf software. The enhanced turbine’s power generation capabilities are subsequently assessed with FAST (Fatigue, Aerodynamics, Structures, and Turbulence) version 8. Results reveal that at a wind speed of 15 m/s, the turbine with the modified blades produces 6.7% more power and 20.47% more annual energy than the original turbine.
{"title":"Optimizing efficiency and analyzing performance: Enhanced airfoil cross-sections for horizontal axis small wind turbines","authors":"M. M. Akheel, B. Sankar, K. Boopathi, D. Reddy Prasad, N. Prabhu Shankar, N. Rajkumar","doi":"10.1177/0309524x241259946","DOIUrl":"https://doi.org/10.1177/0309524x241259946","url":null,"abstract":"This study explores modifications to the blade airfoil cross-sections aimed at improving the efficiency of a 10 kW Bergey EXCEL horizontal axis small wind turbine. Specifically, the research focuses on altering the camber and thickness of the turbine’s baseline airfoil, designated as SG6043. Using advanced aerodynamic analysis tools like QBlade, the performance of the modified airfoils EY05-10 and EY08-9 is evaluated. The findings show that these modified airfoils achieve a higher lift-to-drag ratio compared to the baseline. These improved airfoils are then incorporated into the turbine’s blade geometry using the WT_Perf software. The enhanced turbine’s power generation capabilities are subsequently assessed with FAST (Fatigue, Aerodynamics, Structures, and Turbulence) version 8. Results reveal that at a wind speed of 15 m/s, the turbine with the modified blades produces 6.7% more power and 20.47% more annual energy than the original turbine.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798280","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 : 2024-07-27DOI: 10.1177/0309524x241263518
Omar Makram Kamel, I. Elzein, Mohamed Metwally Mahmoud, A. Abdelaziz, Mahmoud M. Hussein, A. Z. Zaki Diab
The current widespread support of decarbonization and green energy has led to a notable increase in the incorporation of clean energy sources (CESs) in microgrids (MGs). CESs are intermittent, and if they become more widely used in MG, managing uncertainty will become more difficult. This is true even with the environmental and financial advantages of CESs. In this paper, the operation of a DC/AC MG, which integrates solar photovoltaics (PVs), wind farms, fuel cells (FCs), and battery chargers (BCs), is investigated and analyzed under uncertain conditions. The MG’s main energy source is thought to be the PV, while the FC and BC assist in maintaining the MG’s stability. A variable AC load and an electric vehicle charging system are fed by the MG. Two control system approaches have been designed and evaluated. The first is a new design of fuzzy logic controller (FLC), which is provided and applied to provide an adequate energy management system (EMS) for the investigated MG considering uncertainties of CESs. Moreover, JAYA-based optimal control has been developed. The proposed EMS is utilized to adapt the fuel consumption for the FC and the charging concept of Li-ions and to provide a constant load bus voltage. In order to demonstrate the effectiveness of the suggested technique, the proposed novel design of FLC and JAYA-based controllers’ performance is tested under partial shadowing of the PV with abrupt load fluctuations of 25% and contrasted with the PI controller methodology, where it is designed using the Ziglar Nicolas technique. The obtained findings show how the suggested control technique improves the system and the MG’s dynamic performance. A MATLABSimulink simulation is carried out, and the outcomes demonstrate the effectiveness and superiority of the suggested strategy in managing uncertainty.
目前，人们普遍支持去碳化和绿色能源，这导致在微电网（MG）中采用清洁能源（CES）的情况明显增加。CES 具有间歇性，如果它们在微电网中得到更广泛的应用，管理不确定性将变得更加困难。即使 CES 具有环境和财务优势，情况也是如此。本文研究和分析了在不确定条件下，集成了太阳能光伏（PV）、风力发电场、燃料电池（FC）和电池充电器（BC）的直流/交流 MG 的运行情况。我们认为 MG 的主要能源是光伏，而 FC 和 BC 则协助维持 MG 的稳定性。可变交流负载和电动汽车充电系统由 MG 供电。设计并评估了两种控制系统方法。第一种是新设计的模糊逻辑控制器 (FLC)，考虑到 CES 的不确定性，提供并应用于为所研究的 MG 提供适当的能源管理系统 (EMS)。此外，还开发了基于 JAYA 的优化控制。建议的 EMS 用于调整 FC 的燃料消耗和锂离子充电概念，并提供恒定的负载总线电压。为了证明所建议技术的有效性，在光伏部分遮挡、负载突然波动 25% 的情况下，测试了所建议的 FLC 和基于 JAYA 控制器的新型设计性能，并与使用 Ziglar Nicolas 技术设计的 PI 控制器方法进行了对比。结果表明，建议的控制技术改善了系统和 MG 的动态性能。此外，还进行了 MATLAB/Simulink 仿真，结果证明了所建议的策略在管理不确定性方面的有效性和优越性。
{"title":"Effective energy management strategy with a novel design of fuzzy logic and JAYA-based controllers in isolated DC/AC microgrids: A comparative analysis","authors":"Omar Makram Kamel, I. Elzein, Mohamed Metwally Mahmoud, A. Abdelaziz, Mahmoud M. Hussein, A. Z. Zaki Diab","doi":"10.1177/0309524x241263518","DOIUrl":"https://doi.org/10.1177/0309524x241263518","url":null,"abstract":"The current widespread support of decarbonization and green energy has led to a notable increase in the incorporation of clean energy sources (CESs) in microgrids (MGs). CESs are intermittent, and if they become more widely used in MG, managing uncertainty will become more difficult. This is true even with the environmental and financial advantages of CESs. In this paper, the operation of a DC/AC MG, which integrates solar photovoltaics (PVs), wind farms, fuel cells (FCs), and battery chargers (BCs), is investigated and analyzed under uncertain conditions. The MG’s main energy source is thought to be the PV, while the FC and BC assist in maintaining the MG’s stability. A variable AC load and an electric vehicle charging system are fed by the MG. Two control system approaches have been designed and evaluated. The first is a new design of fuzzy logic controller (FLC), which is provided and applied to provide an adequate energy management system (EMS) for the investigated MG considering uncertainties of CESs. Moreover, JAYA-based optimal control has been developed. The proposed EMS is utilized to adapt the fuel consumption for the FC and the charging concept of Li-ions and to provide a constant load bus voltage. In order to demonstrate the effectiveness of the suggested technique, the proposed novel design of FLC and JAYA-based controllers’ performance is tested under partial shadowing of the PV with abrupt load fluctuations of 25% and contrasted with the PI controller methodology, where it is designed using the Ziglar Nicolas technique. The obtained findings show how the suggested control technique improves the system and the MG’s dynamic performance. A MATLABSimulink simulation is carried out, and the outcomes demonstrate the effectiveness and superiority of the suggested strategy in managing uncertainty.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798465","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 : 2024-07-27DOI: 10.1177/0309524x241263591
L. Saihi, F. Ferroudji, K. Roummani, K. Koussa, L. Djilali
This research introduces a resilient Sensor-Less 1st Sliding Mode (SL-FOSM) approach employing a novel observer, the Artificial Neural Network with Model Reference Adaptive System-Adaptive (Neural-MRAS), for wind turbine chains. The proposed model is implemented on a Doubly Powered Induction Generator (DPIG) operating under genuine variable speed conditions in the Adrar region in Algeria. The control objective is to independently regulate the active and reactive power of the DPIG stator, achieved through decoupling using the field-oriented control technique and control application via FOSM-C. Notably, this methodology reduces both the control scheme cost and the DPIG size by eliminating the need for a speed sensor (encoder). To enhance the MRAS-PI, an Artificial Neural Network (ANN) is suggested to replace the typical classical Proportional-Integral (PI) controller in the adaptation mechanism of MRAS. The rotor position estimation is scrutinized and discussed across various load conditions in low, zero, and high-speed regions. Optimal controller parameters are determined through particle swarm optimization (PSO). The results demonstrate that the proposed observer (Neural-MRAS) exhibits compelling attributes, including guaranteed finite time convergence, robust performance in response to speed variations, high resilience against machine parameter fluctuations, and adaptability to load variations when compared to the MRAS-PI. Consequently, the estimated rotor speed converges to its actual value, showcasing the capability to accurately estimate position across different speed regions (low/zero/high).
{"title":"PSO-optimized sensor-less sliding mode control for variable speed wind turbine chains based on DPIG with neural-MRAS observer","authors":"L. Saihi, F. Ferroudji, K. Roummani, K. Koussa, L. Djilali","doi":"10.1177/0309524x241263591","DOIUrl":"https://doi.org/10.1177/0309524x241263591","url":null,"abstract":"This research introduces a resilient Sensor-Less 1st Sliding Mode (SL-FOSM) approach employing a novel observer, the Artificial Neural Network with Model Reference Adaptive System-Adaptive (Neural-MRAS), for wind turbine chains. The proposed model is implemented on a Doubly Powered Induction Generator (DPIG) operating under genuine variable speed conditions in the Adrar region in Algeria. The control objective is to independently regulate the active and reactive power of the DPIG stator, achieved through decoupling using the field-oriented control technique and control application via FOSM-C. Notably, this methodology reduces both the control scheme cost and the DPIG size by eliminating the need for a speed sensor (encoder). To enhance the MRAS-PI, an Artificial Neural Network (ANN) is suggested to replace the typical classical Proportional-Integral (PI) controller in the adaptation mechanism of MRAS. The rotor position estimation is scrutinized and discussed across various load conditions in low, zero, and high-speed regions. Optimal controller parameters are determined through particle swarm optimization (PSO). The results demonstrate that the proposed observer (Neural-MRAS) exhibits compelling attributes, including guaranteed finite time convergence, robust performance in response to speed variations, high resilience against machine parameter fluctuations, and adaptability to load variations when compared to the MRAS-PI. Consequently, the estimated rotor speed converges to its actual value, showcasing the capability to accurately estimate position across different speed regions (low/zero/high).","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798915","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 : 2024-07-27DOI: 10.1177/0309524x241259945
H. Nezzar, F. Ferroudji, T. Outtas
A Vertical Axis Wind Turbine (VAWT) comprises multiple parts constructed from different materials. This complexity presents challenges in designing the blade structure. In this study, we investigated a structural optimization of a small-scale blade for a VAWT, with Finite Element Analysis (FEA) model. The purpose is to minimize the blade mass while adhering to a suite of critical wind conditions according to the IEC 61400-2 Standard. The structure made from Aluminum material simulates structure’s global behavior to determine maximum stress and deflection levels. The same structure is modeled using Glass/Epoxy composite for optimizing its design. Twenty combinations of Glass/Epoxy layers, varying in ply thickness and orientation, are simulated to find the most suitable combination. Results demonstrated that the optimization case [45°/90°/0°/−45°] obtained the minimum values of stress and deflection, is 59% lighter than Aluminum blade (initial design). The designed Glass/Epoxy composite blade is acceptable and recommended for structural safety.
{"title":"Numerical investigation of the structural-response analysis of a glass/epoxy composite blade for small-scale vertical-axis wind turbine","authors":"H. Nezzar, F. Ferroudji, T. Outtas","doi":"10.1177/0309524x241259945","DOIUrl":"https://doi.org/10.1177/0309524x241259945","url":null,"abstract":"A Vertical Axis Wind Turbine (VAWT) comprises multiple parts constructed from different materials. This complexity presents challenges in designing the blade structure. In this study, we investigated a structural optimization of a small-scale blade for a VAWT, with Finite Element Analysis (FEA) model. The purpose is to minimize the blade mass while adhering to a suite of critical wind conditions according to the IEC 61400-2 Standard. The structure made from Aluminum material simulates structure’s global behavior to determine maximum stress and deflection levels. The same structure is modeled using Glass/Epoxy composite for optimizing its design. Twenty combinations of Glass/Epoxy layers, varying in ply thickness and orientation, are simulated to find the most suitable combination. Results demonstrated that the optimization case [45°/90°/0°/−45°] obtained the minimum values of stress and deflection, is 59% lighter than Aluminum blade (initial design). The designed Glass/Epoxy composite blade is acceptable and recommended for structural safety.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798317","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 : 2024-07-23DOI: 10.1177/0309524x241260061
E. Möllerström, P. Gipe, F. Ottermo
Wind power only received occasional attention since the introduction of electricity until the 1970s, when a revived interest in alternative energy sources spurred the development thread that led to today’s wind turbines. Although attention and financial support at the time were directed toward government-funded MW-scale wind turbines, the small models developed in the late 1970s for the Danish market were ultimately the way forward. The wind industry has since matured, as evidenced by the lower specific power and higher capacity factors of recent turbine models and the similarity between their power curve shapes. Moreover, this study highlights two historical accomplishments by Europeans that are sometimes incorrectly credited to Americans: the first wind turbine to generate electricity was built in 1883 by Austrian Josef Friedländer and the Danish Agricco (1919) became the first public grid-connected wind turbine.
{"title":"Wind power development: A historical review","authors":"E. Möllerström, P. Gipe, F. Ottermo","doi":"10.1177/0309524x241260061","DOIUrl":"https://doi.org/10.1177/0309524x241260061","url":null,"abstract":"Wind power only received occasional attention since the introduction of electricity until the 1970s, when a revived interest in alternative energy sources spurred the development thread that led to today’s wind turbines. Although attention and financial support at the time were directed toward government-funded MW-scale wind turbines, the small models developed in the late 1970s for the Danish market were ultimately the way forward. The wind industry has since matured, as evidenced by the lower specific power and higher capacity factors of recent turbine models and the similarity between their power curve shapes. Moreover, this study highlights two historical accomplishments by Europeans that are sometimes incorrectly credited to Americans: the first wind turbine to generate electricity was built in 1883 by Austrian Josef Friedländer and the Danish Agricco (1919) became the first public grid-connected wind turbine.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810137","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 : 2024-07-23DOI: 10.1177/0309524x241256955
Avulamanda Siva Nagaraju, Rajat Gupta, S. Bhowmik
This study examines how adjusting aspect ratio (AR) and adding triangular dimples to the airfoil can enhance H-type Darrieus wind rotor (H-rotor) performance under low wind speeds (4, 6, and 8 m/s) using wind tunnel testing. Results show optimal performance at an AR of 1.0 for both standard and Triangular dimple airfoil H-rotors, with variations at different wind speeds for other aspect ratios. Triangular dimple-equipped H-rotors demonstrate improved self-starting capability and a wider operational range of tip speed ratio (TSR) compared to standard rotors, ensuring reliability across diverse wind conditions. Moreover, the triangular dimple rotor achieves a nearly 13.6% increase in maximum coefficient of power ([Formula: see text]) compared to the dimple-free H-rotor at 4 m/s wind speed. This study underscores the efficacy of adjusting AR and integrating triangular dimple blades to enhance H-rotor performance, particularly in low wind speeds.
本研究通过风洞试验，探讨了在低风速（4、6 和 8 米/秒）条件下，调整高宽比（AR）和在机翼上添加三角窝如何提高 H 型达里厄斯风转子（H 型转子）的性能。结果表明，在 AR 值为 1.0 时，标准 H 型转子和三角窝翼 H 型转子的性能最佳，而在不同风速下，其他纵横比的性能会有所变化。与标准转子相比，配备三角窝的 H 型转子具有更强的自启动能力和更宽的翼尖速比 (TSR) 工作范围，从而确保了在各种风况下的可靠性。此外，在 4 米/秒的风速下，三角形凹槽转子的最大功率系数（[计算公式：见正文]）比无凹槽 H 型转子提高了近 13.6%。这项研究强调了调整 AR 和集成三角窝叶片以提高 H 型转子性能的有效性，尤其是在低风速条件下。
{"title":"Effects of the influence of triangular dimple and aspect ratio on NACA 4412 airfoil on the overall performance of H-Darrieus wind rotor: An experimental investigation","authors":"Avulamanda Siva Nagaraju, Rajat Gupta, S. Bhowmik","doi":"10.1177/0309524x241256955","DOIUrl":"https://doi.org/10.1177/0309524x241256955","url":null,"abstract":"This study examines how adjusting aspect ratio (AR) and adding triangular dimples to the airfoil can enhance H-type Darrieus wind rotor (H-rotor) performance under low wind speeds (4, 6, and 8 m/s) using wind tunnel testing. Results show optimal performance at an AR of 1.0 for both standard and Triangular dimple airfoil H-rotors, with variations at different wind speeds for other aspect ratios. Triangular dimple-equipped H-rotors demonstrate improved self-starting capability and a wider operational range of tip speed ratio (TSR) compared to standard rotors, ensuring reliability across diverse wind conditions. Moreover, the triangular dimple rotor achieves a nearly 13.6% increase in maximum coefficient of power ([Formula: see text]) compared to the dimple-free H-rotor at 4 m/s wind speed. This study underscores the efficacy of adjusting AR and integrating triangular dimple blades to enhance H-rotor performance, particularly in low wind speeds.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141812949","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 : 2024-07-23DOI: 10.1177/0309524x241256956
M. Mosaad
While the direct power control (DPC) approach has proven effective in improving the efficiency of wind energy conversion systems (WECS) using doubly fed induction generators (DFIG), its applicability is currently confined to a single usage and has not been extended to meet numerous applications. This work aimed to modify the implementation of DPC in WECS-DFIG for several objectives. This is accomplished by updating the reference power of the conventional DPC method into an adapted one to achieve two goals independently. The first objective is to track the maximum power during wind speed variations. This tracking is performed by updating the reference power to match the maximum available power at the current wind speed. The second purpose is to ensure that the WECS remains connected to the grid and continues to operate smoothly even in the event of faults; supporting fault-ride through (FRT) capability. That is achieved by reducing the reference power during these faults. The discrimination between these two objectives is based on the voltage level at the point of connecting WECS to the grid. The controller provided is an improved fractional order PI controller developed using arithmetic optimization technique (AOA). A comparison between the AOA and cuckoo search is presented. The results demonstrate the efficacy of the suggested configuration and regulator in enhancing the performance of integrating DFIG into the WECS in the presence of wind fluctuations and short circuit faults occurring. It is worth noting that AOA is better than cuckoo search in fine-tuning the settings of the FOPI controller.
{"title":"Application of DPC to improve the integration of DFIG into wind energy conversion systems using FOPI controller","authors":"M. Mosaad","doi":"10.1177/0309524x241256956","DOIUrl":"https://doi.org/10.1177/0309524x241256956","url":null,"abstract":"While the direct power control (DPC) approach has proven effective in improving the efficiency of wind energy conversion systems (WECS) using doubly fed induction generators (DFIG), its applicability is currently confined to a single usage and has not been extended to meet numerous applications. This work aimed to modify the implementation of DPC in WECS-DFIG for several objectives. This is accomplished by updating the reference power of the conventional DPC method into an adapted one to achieve two goals independently. The first objective is to track the maximum power during wind speed variations. This tracking is performed by updating the reference power to match the maximum available power at the current wind speed. The second purpose is to ensure that the WECS remains connected to the grid and continues to operate smoothly even in the event of faults; supporting fault-ride through (FRT) capability. That is achieved by reducing the reference power during these faults. The discrimination between these two objectives is based on the voltage level at the point of connecting WECS to the grid. The controller provided is an improved fractional order PI controller developed using arithmetic optimization technique (AOA). A comparison between the AOA and cuckoo search is presented. The results demonstrate the efficacy of the suggested configuration and regulator in enhancing the performance of integrating DFIG into the WECS in the presence of wind fluctuations and short circuit faults occurring. It is worth noting that AOA is better than cuckoo search in fine-tuning the settings of the FOPI controller.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810344","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 : 2024-06-13DOI: 10.1177/0309524x241250057
Z. Tahir, Ammara Kanwal, Muhammad Zeeshan Jamil, Imran Amin, Muhammad Abdullah, U. Saeed, Tariq Ali
Wind resource assessment of 12 sites in low-wind regions of Pakistan was conducted, focusing on wind data characteristics and wind speed distributions. A comparative performance evaluation of Power Law (PL) and Logarithmic Law (LogL) for interpolation (at 60 m) and extrapolation (at 80 m) of wind speed was performed. Performance analysis of over 500 commercial wind turbines was carried out in terms of Net Capacity Factor (NCF). The wind power density of all sites at 50 m, ranges from 33 to 244 W/m2, categorizing wind power class as either poor or marginal. The performance evaluation shows that PL and LogL perform better for interpolation and extrapolation respectively, at the same height. A turbine with cut-in and rated speed of 1.0 and 10 m/s respectively, achieves maximum NCF across all sites due to lowest cut-in speed. The NCF of the turbine for marginal wind power class sites ranged from 53% to 58%.
{"title":"Performance assessment of commercial wind turbines for low wind speed regions","authors":"Z. Tahir, Ammara Kanwal, Muhammad Zeeshan Jamil, Imran Amin, Muhammad Abdullah, U. Saeed, Tariq Ali","doi":"10.1177/0309524x241250057","DOIUrl":"https://doi.org/10.1177/0309524x241250057","url":null,"abstract":"Wind resource assessment of 12 sites in low-wind regions of Pakistan was conducted, focusing on wind data characteristics and wind speed distributions. A comparative performance evaluation of Power Law (PL) and Logarithmic Law (LogL) for interpolation (at 60 m) and extrapolation (at 80 m) of wind speed was performed. Performance analysis of over 500 commercial wind turbines was carried out in terms of Net Capacity Factor (NCF). The wind power density of all sites at 50 m, ranges from 33 to 244 W/m2, categorizing wind power class as either poor or marginal. The performance evaluation shows that PL and LogL perform better for interpolation and extrapolation respectively, at the same height. A turbine with cut-in and rated speed of 1.0 and 10 m/s respectively, achieves maximum NCF across all sites due to lowest cut-in speed. The NCF of the turbine for marginal wind power class sites ranged from 53% to 58%.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141348613","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 : 2024-06-12DOI: 10.1177/0309524x241254364
F. Menzri, T. Boutabba, I. Benlaloui, Haneen Bawayan, Mohmed I. Mosaad, Mohamed Metwally Mahmoud
Green energy sources (GESs) in electrical systems have become widely included in electrical networks for their significant subnational impacts on the economy and the environment. Regrettably, the power generating capacity of these GESs is significantly influenced by environmental circumstances, such as temperature and sun irradiation for PV systems and wind speed for WT systems. Environmental changes impact the power capacity of the electrical system since the maximum amount of power that can be generated will only be achieved by implementing control measures. This research aims to enhance the efficiency of a standalone renewable power system by optimizing the energy output from GESs using the MPPT technique, considering the impact of climate fluctuations. The standalone hybrid GESs combines PV and WT technologies with a BSS. For the PV and WT, a combinatorial MPPT technique is proposed to modify the control settings for this system optimally. This method is based on the SMC and FLC. The FLC plays a role in achieving the MPPT target by utilizing membership functions designed to handle uncertainties caused by shifting environmental conditions. Whereas for the BSS, an energy management plan is developed to optimize the performance of the HRES. The system under study outfitted with the MPPT technology, functions in tandem with a BSS. In case of failure or insufficient power generation from primary sources, a DC/DC bidirectional converter is employed to adjust the charging and discharging of the BSS, ensuring a stable supply of DC power. The system’s response in different climates is examined, and the proposed combination controller’s intended effectiveness is confirmed using MATLABSimulink. The investigated structure can achieve approximately 99.213% efficacy with the support of the proposed SMC-FLC method, which is 19.874% greater than the widely used P&O method.
{"title":"Applications of hybrid SMC and FLC for augmentation of MPPT method in a wind-PV-battery configuration","authors":"F. Menzri, T. Boutabba, I. Benlaloui, Haneen Bawayan, Mohmed I. Mosaad, Mohamed Metwally Mahmoud","doi":"10.1177/0309524x241254364","DOIUrl":"https://doi.org/10.1177/0309524x241254364","url":null,"abstract":"Green energy sources (GESs) in electrical systems have become widely included in electrical networks for their significant subnational impacts on the economy and the environment. Regrettably, the power generating capacity of these GESs is significantly influenced by environmental circumstances, such as temperature and sun irradiation for PV systems and wind speed for WT systems. Environmental changes impact the power capacity of the electrical system since the maximum amount of power that can be generated will only be achieved by implementing control measures. This research aims to enhance the efficiency of a standalone renewable power system by optimizing the energy output from GESs using the MPPT technique, considering the impact of climate fluctuations. The standalone hybrid GESs combines PV and WT technologies with a BSS. For the PV and WT, a combinatorial MPPT technique is proposed to modify the control settings for this system optimally. This method is based on the SMC and FLC. The FLC plays a role in achieving the MPPT target by utilizing membership functions designed to handle uncertainties caused by shifting environmental conditions. Whereas for the BSS, an energy management plan is developed to optimize the performance of the HRES. The system under study outfitted with the MPPT technology, functions in tandem with a BSS. In case of failure or insufficient power generation from primary sources, a DC/DC bidirectional converter is employed to adjust the charging and discharging of the BSS, ensuring a stable supply of DC power. The system’s response in different climates is examined, and the proposed combination controller’s intended effectiveness is confirmed using MATLABSimulink. The investigated structure can achieve approximately 99.213% efficacy with the support of the proposed SMC-FLC method, which is 19.874% greater than the widely used P&O method.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353385","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 : 2024-06-10DOI: 10.1177/0309524x241257429
Fei Tang
Accurate short-term wind power prediction is of great significance for the scheduling and management of wind farms. This paper proposes a model for short-term wind power prediction. Firstly, on the basis of traditional long short-term memory network, the peephole connections is added. The improved long short-term memory network is more stable compared to traditional long short-term memory neural networks and is suitable for regression prediction. Secondly, chaotic mapping, adaptive weights, Cauchy mutation, and opposition-based learning strategies are introduced to improve the sparrow search algorithm, and applied to optimize the four hyper-parameters of the long short-term memory network, greatly improving the prediction accuracy of the network. The effectiveness of the model is validated using two short-term wind power datasets with sampling times of 10 and 30 minutes respectively, combined with some fitting curves and performance indicators. The comparison results indicate that the proposed short-term wind power prediction model has high prediction accuracy.
{"title":"Short-term wind power prediction based on improved sparrow search algorithm optimized long short-term memory with peephole connections","authors":"Fei Tang","doi":"10.1177/0309524x241257429","DOIUrl":"https://doi.org/10.1177/0309524x241257429","url":null,"abstract":"Accurate short-term wind power prediction is of great significance for the scheduling and management of wind farms. This paper proposes a model for short-term wind power prediction. Firstly, on the basis of traditional long short-term memory network, the peephole connections is added. The improved long short-term memory network is more stable compared to traditional long short-term memory neural networks and is suitable for regression prediction. Secondly, chaotic mapping, adaptive weights, Cauchy mutation, and opposition-based learning strategies are introduced to improve the sparrow search algorithm, and applied to optimize the four hyper-parameters of the long short-term memory network, greatly improving the prediction accuracy of the network. The effectiveness of the model is validated using two short-term wind power datasets with sampling times of 10 and 30 minutes respectively, combined with some fitting curves and performance indicators. The comparison results indicate that the proposed short-term wind power prediction model has high prediction accuracy.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141362266","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：