Pub Date : 2024-01-03DOI: 10.1177/0309524x231211315
Moein Sarbandi, Hamid Khaloozadeh
Wind turbines (WTs) are complex systems with multiple interacting components, posing challenges in identifying factors affecting power output (PO). Sensors play an important role; however, sensor precision can result in measured values differing from actual values. Analyzing the impact of sensor precision on PO is essential. In this study, we employ sensitivity analysis (SA) via Monte Carlo (MC) simulation, offering a novel approach to quantify the influence of sensor precision on the PO of a 4.8 MW WT. We focus on evaluations under 5–20 m/s wind profiles, representing partial and full load regions that portray normal operation. Based on mean squared error (MSE) and parameter sensitivity (PS) index analyses, findings show the generator speed sensor’s precision significantly impacts PO. Therefore, designers should prioritize high-impact sensors like the generator speed, while sensorless strategies may be considered as alternatives to low-impact sensors like the blade pitch angle sensor, where appropriate.
{"title":"Quantifying the impact of sensor precision on power output of a wind turbine: A sensitivity analysis via Monte Carlo simulation study","authors":"Moein Sarbandi, Hamid Khaloozadeh","doi":"10.1177/0309524x231211315","DOIUrl":"https://doi.org/10.1177/0309524x231211315","url":null,"abstract":"Wind turbines (WTs) are complex systems with multiple interacting components, posing challenges in identifying factors affecting power output (PO). Sensors play an important role; however, sensor precision can result in measured values differing from actual values. Analyzing the impact of sensor precision on PO is essential. In this study, we employ sensitivity analysis (SA) via Monte Carlo (MC) simulation, offering a novel approach to quantify the influence of sensor precision on the PO of a 4.8 MW WT. We focus on evaluations under 5–20 m/s wind profiles, representing partial and full load regions that portray normal operation. Based on mean squared error (MSE) and parameter sensitivity (PS) index analyses, findings show the generator speed sensor’s precision significantly impacts PO. Therefore, designers should prioritize high-impact sensors like the generator speed, while sensorless strategies may be considered as alternatives to low-impact sensors like the blade pitch angle sensor, where appropriate.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139388402","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 : 2023-12-22DOI: 10.1177/0309524x231216648
Xiaoju Yin, Qi Zheng Mu, Guo Ce Shao, Shiyu Lu
Addressing the challenge of rehearsing large-scale equipment assembly, particularly for oversized components like wind turbine towers, hubs, nacelles, and blades, which often face quality issues such as substandard workmanship and wide tolerances during on-site assembly, a system has been developed for simulating wind turbine assembly. This system enables digital wind turbine assembly by creating virtual and production process models and employing intelligent database analysis. It resolves the problem of the absence of pre-production for large-scale equipment, meets the batch production needs of the wind turbine manufacturing industry, enhances the safety of wind turbine operations, improves operator assembly skills, and boosts production efficiency. This platform has already been implemented in the wind turbine manufacturing industry, yielding significant economic benefits.
{"title":"Design and realization of a pre-production platform for wind turbine manufacturing","authors":"Xiaoju Yin, Qi Zheng Mu, Guo Ce Shao, Shiyu Lu","doi":"10.1177/0309524x231216648","DOIUrl":"https://doi.org/10.1177/0309524x231216648","url":null,"abstract":"Addressing the challenge of rehearsing large-scale equipment assembly, particularly for oversized components like wind turbine towers, hubs, nacelles, and blades, which often face quality issues such as substandard workmanship and wide tolerances during on-site assembly, a system has been developed for simulating wind turbine assembly. This system enables digital wind turbine assembly by creating virtual and production process models and employing intelligent database analysis. It resolves the problem of the absence of pre-production for large-scale equipment, meets the batch production needs of the wind turbine manufacturing industry, enhances the safety of wind turbine operations, improves operator assembly skills, and boosts production efficiency. This platform has already been implemented in the wind turbine manufacturing industry, yielding significant economic benefits.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139163666","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}
Wind power prediction is vital in renewable energy. Correct forecasts enable utility companies to optimize production and minimize costs. However, due to the intricate nature of wind patterns, making precise predictions is challenging. This article introduces a novel model combining Quantile Regression and Decision Tree Regression for forecasting wind energy. Trained on historical wind speed and output data, the model’s efficacy is assessed using metrics like mean absolute error and root mean squared error. The model is evaluated using the SCADA Turkey dataset, a prominent benchmark in wind forecasting. Preliminary results demonstrate the combined model’s superior predictive accuracy over traditional regression models, highlighting its potential for enhanced wind energy forecasting.
{"title":"Analysis of wind power curve modeling using multi-model regression","authors":"Vivek Kumar Patidar, Rajesh Wadhvani, Muktesh Gupta","doi":"10.1177/0309524x231214141","DOIUrl":"https://doi.org/10.1177/0309524x231214141","url":null,"abstract":"Wind power prediction is vital in renewable energy. Correct forecasts enable utility companies to optimize production and minimize costs. However, due to the intricate nature of wind patterns, making precise predictions is challenging. This article introduces a novel model combining Quantile Regression and Decision Tree Regression for forecasting wind energy. Trained on historical wind speed and output data, the model’s efficacy is assessed using metrics like mean absolute error and root mean squared error. The model is evaluated using the SCADA Turkey dataset, a prominent benchmark in wind forecasting. Preliminary results demonstrate the combined model’s superior predictive accuracy over traditional regression models, highlighting its potential for enhanced wind energy forecasting.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139164705","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 : 2023-12-09DOI: 10.1177/0309524x231212638
Muhammad Saif Ullah Khalid, Priscila Scarlet Portocarrero Mendoza, D. Wood, A. Hemmati
This study explored the aerodynamics of a new multi-stage co-axial vertical-axis wind turbine based on bio-inspiration from natural swimming habit of fish. The turbine was formed from a conventional straight-bladed vertical axis turbine (VAWT) with an additional small inner rotor, also of three blades. The azimuthal and radial locations of the inner rotor were varied. Using numerical simulations, performance of the proposed new design was evaluated over a range of tip-speed ratios. The preliminary results identified a 600% increase in power output for multi-stage VAWTs at tip-speed ratios [Formula: see text], and a substantial drop in power coefficient at [Formula: see text]. The wake dynamics analyses revealed that the increase was due to interactions between the blades of one rotor and the other. This reduced the unsteady separation from the outer rotor, which produced most of the power. A detailed parametric study was also completed, which showed the implications of geometric and kinematic details on the performance of the proposed multistage VAWT.
{"title":"On the aerodynamics of dual-stage co-axial vertical-axis wind turbines","authors":"Muhammad Saif Ullah Khalid, Priscila Scarlet Portocarrero Mendoza, D. Wood, A. Hemmati","doi":"10.1177/0309524x231212638","DOIUrl":"https://doi.org/10.1177/0309524x231212638","url":null,"abstract":"This study explored the aerodynamics of a new multi-stage co-axial vertical-axis wind turbine based on bio-inspiration from natural swimming habit of fish. The turbine was formed from a conventional straight-bladed vertical axis turbine (VAWT) with an additional small inner rotor, also of three blades. The azimuthal and radial locations of the inner rotor were varied. Using numerical simulations, performance of the proposed new design was evaluated over a range of tip-speed ratios. The preliminary results identified a 600% increase in power output for multi-stage VAWTs at tip-speed ratios [Formula: see text], and a substantial drop in power coefficient at [Formula: see text]. The wake dynamics analyses revealed that the increase was due to interactions between the blades of one rotor and the other. This reduced the unsteady separation from the outer rotor, which produced most of the power. A detailed parametric study was also completed, which showed the implications of geometric and kinematic details on the performance of the proposed multistage VAWT.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138585439","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 : 2023-11-29DOI: 10.1177/0309524x231201656
S. Tounsi
In this work, an optimal control scheme based on the Maximum Power Point tracking for the Wind Energy Conversion System using Permanent Magnet Synchronous Generator (PMSG) is proposed and also modeled. The system studied in this paper consists of wind energy system powering a battery using a buck-boost converter as an interface. By modifying the buck-boost duty cycle, we vary the reflected voltage at PMSG, and accordingly its speed. It is controlled with Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) approach. The overall system is simulated with MATLAB/SIMULINK.
{"title":"Innovative maximum power point tracking technique for wind energy conversion system","authors":"S. Tounsi","doi":"10.1177/0309524x231201656","DOIUrl":"https://doi.org/10.1177/0309524x231201656","url":null,"abstract":"In this work, an optimal control scheme based on the Maximum Power Point tracking for the Wind Energy Conversion System using Permanent Magnet Synchronous Generator (PMSG) is proposed and also modeled. The system studied in this paper consists of wind energy system powering a battery using a buck-boost converter as an interface. By modifying the buck-boost duty cycle, we vary the reflected voltage at PMSG, and accordingly its speed. It is controlled with Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) approach. The overall system is simulated with MATLAB/SIMULINK.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139215094","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 : 2023-11-27DOI: 10.1177/0309524x231210266
Ameer Faisal, N. Anwer
The welfare of the villages is one of the primary objectives of the rural electrification programmes. Compared to electrifying urban regions, electrifying rural areas is more expensive. Energy requirements in rural areas can be met using hybrid energy technologies. This study proposes a cost-effective power solution to reduce the net present cost (NPC), cost of energy (COE), unmet loads and CO2 emissions. Grey Wolf Optimizer (GWO) and Homer Pro are used to optimize the size of the components of the system. The combination of solar, wind and biogas with a battery storage system is cost-effective with zero unmet loads. Of the three combinations considered, the values of COE and NPC for combination-1 were 0.156 ($/kWh) and $2.05 M respectively. The comparative analysis of optimization between the GWO technique and Homer Pro carried out shows that the value of COE and NPC are reduced by 5.45% and 3.30% respectively.
农村的福利是农村电气化计划的主要目标之一。与城市地区的电气化相比，农村地区的电气化成本更高。使用混合能源技术可以满足农村地区的能源需求。本研究提出了一种具有成本效益的电力解决方案，以降低净现值成本 (NPC)、能源成本 (COE)、未满足的负荷和二氧化碳排放量。灰狼优化器（GWO）和 Homer Pro 用于优化系统组件的大小。太阳能、风能和沼气与蓄电池储能系统的组合具有成本效益，未满足的负荷为零。在考虑的三种组合中，组合-1 的 COE 值和 NPC 值分别为 0.156（美元/千瓦时）和 205 万美元。GWO 技术与 Homer Pro 的优化对比分析表明，COE 和 NPC 值分别降低了 5.45% 和 3.30%。
{"title":"Optimization and techno-economic analysis of hybrid renewable energy systems for the electrification of remote areas","authors":"Ameer Faisal, N. Anwer","doi":"10.1177/0309524x231210266","DOIUrl":"https://doi.org/10.1177/0309524x231210266","url":null,"abstract":"The welfare of the villages is one of the primary objectives of the rural electrification programmes. Compared to electrifying urban regions, electrifying rural areas is more expensive. Energy requirements in rural areas can be met using hybrid energy technologies. This study proposes a cost-effective power solution to reduce the net present cost (NPC), cost of energy (COE), unmet loads and CO2 emissions. Grey Wolf Optimizer (GWO) and Homer Pro are used to optimize the size of the components of the system. The combination of solar, wind and biogas with a battery storage system is cost-effective with zero unmet loads. Of the three combinations considered, the values of COE and NPC for combination-1 were 0.156 ($/kWh) and $2.05 M respectively. The comparative analysis of optimization between the GWO technique and Homer Pro carried out shows that the value of COE and NPC are reduced by 5.45% and 3.30% respectively.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139229935","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 : 2023-11-22DOI: 10.1177/0309524x231206560
Yunlong Wang, Xinshuang Yao
To build a new type of power system, the proportion of renewable energy sources with wind and solar energy as the main body has increased into the power grid. Due to the strong randomness and volatility of renewable energy as a power source, thermal power units need to fluctuate frequently to respond to system power requirements. To ensure the smooth operation of the thermal power units, a variable period day scheduling strategy considering spectrum analysis is proposed. Firstly, different dispatching periods are divided according to the characteristics of system net load fluctuation, secondly, to minimize the total cost, the joint dispatching model of wind power, solar energy, thermal power, and energy storage is established to form a day-ahead dispatching plan with variable time period. Finally, an example shows that this strategy can increase the smooth operation of thermal power units and improve the utilization rate of pumped storage units.
{"title":"A variable-time day-ahead scheduling strategy considering spectrum analysis","authors":"Yunlong Wang, Xinshuang Yao","doi":"10.1177/0309524x231206560","DOIUrl":"https://doi.org/10.1177/0309524x231206560","url":null,"abstract":"To build a new type of power system, the proportion of renewable energy sources with wind and solar energy as the main body has increased into the power grid. Due to the strong randomness and volatility of renewable energy as a power source, thermal power units need to fluctuate frequently to respond to system power requirements. To ensure the smooth operation of the thermal power units, a variable period day scheduling strategy considering spectrum analysis is proposed. Firstly, different dispatching periods are divided according to the characteristics of system net load fluctuation, secondly, to minimize the total cost, the joint dispatching model of wind power, solar energy, thermal power, and energy storage is established to form a day-ahead dispatching plan with variable time period. Finally, an example shows that this strategy can increase the smooth operation of thermal power units and improve the utilization rate of pumped storage units.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139247739","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 : 2023-11-18DOI: 10.1177/0309524x231206723
Abdelrahman Amin, A. Bibo, Meghashyam Panyam, Phanindra Tallapragada
Vibration-based fault diagnostics combined with deep learning approaches has promising applications in detecting and diagnosing faults in wind turbine gearboxes. Specifically when time series vibration data is transformed to a 2-dimensional cyclic spectral coherence maps, the accuracy of deep neural networks in classifying faults increases. Nevertheless, standard deep learning techniques are vulnerable to inaccurate predictions when tested with new data originating from unseen faults or unusual operating conditions. To address some of these shortcomings in the context of wind turbine gearboxes, this paper investigates fault diagnostics using Bayesian convolutional neural network which provide accurate results with uncertainty bounds reducing wrong overconfident classifications. The performance of Bayesian and standard neural networks is compared using a simulation-based dataset of acceleration signals generated from a multibody dynamic model of a 5 MW wind turbine. The framework proposed in this paper has relevance to fault detection and diagnosis in other rotating machinery applications.
{"title":"A Bayesian deep learning framework for reliable fault diagnosis in wind turbine gearboxes under various operating conditions","authors":"Abdelrahman Amin, A. Bibo, Meghashyam Panyam, Phanindra Tallapragada","doi":"10.1177/0309524x231206723","DOIUrl":"https://doi.org/10.1177/0309524x231206723","url":null,"abstract":"Vibration-based fault diagnostics combined with deep learning approaches has promising applications in detecting and diagnosing faults in wind turbine gearboxes. Specifically when time series vibration data is transformed to a 2-dimensional cyclic spectral coherence maps, the accuracy of deep neural networks in classifying faults increases. Nevertheless, standard deep learning techniques are vulnerable to inaccurate predictions when tested with new data originating from unseen faults or unusual operating conditions. To address some of these shortcomings in the context of wind turbine gearboxes, this paper investigates fault diagnostics using Bayesian convolutional neural network which provide accurate results with uncertainty bounds reducing wrong overconfident classifications. The performance of Bayesian and standard neural networks is compared using a simulation-based dataset of acceleration signals generated from a multibody dynamic model of a 5 MW wind turbine. The framework proposed in this paper has relevance to fault detection and diagnosis in other rotating machinery applications.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262367","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 : 2023-11-17DOI: 10.1177/0309524x231199435
A. Dendouga, A. Dendouga, N. Essounbouli
In this paper, a full nonlinear control of a variable-pitch wind system (VPWS) based on the doubly fed induction generator (DFIG) fed by a direct matrix converter (DMC) has been presented. In this context, The MPPT has been implemented using the third order sliding mode control (TOSMC) in order to ensure maximum power provided by the wind turbine on the one side, on the other side the pitch control has been implemented in order to limit the power extracted to its nominal value. Moreover, a TOSMC has been incorporated into the direct flied-oriented control (DFOC) to ensure high-performance control of the active and reactive power of DFIG. To examine the performance of the TOSMC, a comparative study was performed between this last type and the first and second order sliding mode controllers. The obtained results affirmed the high performance provided by the TOSMC compared to lower order sliding mode controllers.
{"title":"High performance of variable-pitch wind system based on a direct matrix converter-fed DFIG using third order sliding mode control","authors":"A. Dendouga, A. Dendouga, N. Essounbouli","doi":"10.1177/0309524x231199435","DOIUrl":"https://doi.org/10.1177/0309524x231199435","url":null,"abstract":"In this paper, a full nonlinear control of a variable-pitch wind system (VPWS) based on the doubly fed induction generator (DFIG) fed by a direct matrix converter (DMC) has been presented. In this context, The MPPT has been implemented using the third order sliding mode control (TOSMC) in order to ensure maximum power provided by the wind turbine on the one side, on the other side the pitch control has been implemented in order to limit the power extracted to its nominal value. Moreover, a TOSMC has been incorporated into the direct flied-oriented control (DFOC) to ensure high-performance control of the active and reactive power of DFIG. To examine the performance of the TOSMC, a comparative study was performed between this last type and the first and second order sliding mode controllers. The obtained results affirmed the high performance provided by the TOSMC compared to lower order sliding mode controllers.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139265978","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 : 2023-11-04DOI: 10.1177/0309524x231206559
Gbubemi Kevin Akporhonor, Smith Orode Otuagoma, Temisan Arnold Akporhonor
This review paper evaluates the current status of the Nigeria wind energy sector to identify the available Wind Energy Potential, Installed Wind Energy Capacity and Renewable Energy Policies in a bid to provide accurate information to aid the exploration and exploitation of wind energy across Nigeria. Consequently, the huge expanse between the wind energy Potential across Cities in Nigeria, the poor numbers of installed wind capacity and Nigeria’s Renewable Energy policies show low interest in Wind Energy in comparison to other RE sources. All this calls for further investment in the Nigerian wind energy sector
{"title":"Nigerian wind energy status","authors":"Gbubemi Kevin Akporhonor, Smith Orode Otuagoma, Temisan Arnold Akporhonor","doi":"10.1177/0309524x231206559","DOIUrl":"https://doi.org/10.1177/0309524x231206559","url":null,"abstract":"This review paper evaluates the current status of the Nigeria wind energy sector to identify the available Wind Energy Potential, Installed Wind Energy Capacity and Renewable Energy Policies in a bid to provide accurate information to aid the exploration and exploitation of wind energy across Nigeria. Consequently, the huge expanse between the wind energy Potential across Cities in Nigeria, the poor numbers of installed wind capacity and Nigeria’s Renewable Energy policies show low interest in Wind Energy in comparison to other RE sources. All this calls for further investment in the Nigerian wind energy sector","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135773687","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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