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Extended state observer-based primary load frequency controller for power systems with ultra-high wind-energy penetration 基于扩展状态观测器的一次负载频率控制器，适用于风能渗透率超高的电力系统
IF 1.5
Wind Engineering Pub Date : 2024-01-11 DOI: 10.1177/0309524x231221242
Tummala Slv Ayyarao, Ramakrishna S. S. Nuvvula, Polamarasetty P. Kumar, Ilhami Colak, Hasan Koten, Ahmed Ali, Baseem Khan
{"title":"Extended state observer-based primary load frequency controller for power systems with ultra-high wind-energy penetration","authors":"Tummala Slv Ayyarao, Ramakrishna S. S. Nuvvula, Polamarasetty P. Kumar, Ilhami Colak, Hasan Koten, Ahmed Ali, Baseem Khan","doi":"10.1177/0309524x231221242","DOIUrl":"https://doi.org/10.1177/0309524x231221242","url":null,"abstract":"In this paper, a novel extended state observer-based (ESO) load frequency control is implemented. Specifically, the proposed control law focuses on the incorporation of wind energy injection as one of the disturbances, treating it as an additional state within the system. The proposed ESO is designed to estimate both the system states and the net disturbance, thereby enhancing its ability to regulate the overall load frequency performance. The proposed control strategy hinges on the judicious selection of control gains and disturbance gain. The estimated disturbance is then effectively compensated to regulate the load frequency. To evaluate the efficacy of the proposed controller, tests are conducted on both single and three area systems. The results demonstrate superior performance, even under conditions involving load and parameter variations.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"4 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139438488","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}
引用次数: 0
Quantifying the impact of sensor precision on power output of a wind turbine: A sensitivity analysis via Monte Carlo simulation study 量化传感器精度对风力涡轮机功率输出的影响：通过蒙特卡罗模拟研究进行敏感性分析
IF 1.5
Wind Engineering Pub Date : 2024-01-03 DOI: 10.1177/0309524x231211315
Moein Sarbandi, Hamid Khaloozadeh
{"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":"31 7","pages":""},"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}
引用次数: 0
Design and realization of a pre-production platform for wind turbine manufacturing 风力涡轮机制造预生产平台的设计与实现
IF 1.5
Wind Engineering Pub Date : 2023-12-22 DOI: 10.1177/0309524x231216648
Xiaoju Yin, Qi Zheng Mu, Guo Ce Shao, Shiyu Lu
{"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":"86 4","pages":""},"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}
引用次数: 0
Analysis of wind power curve modeling using multi-model regression 利用多模型回归分析风能曲线建模
IF 1.5
Wind Engineering Pub Date : 2023-12-22 DOI: 10.1177/0309524x231214141
Vivek Kumar Patidar, Rajesh Wadhvani, Muktesh Gupta
{"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":"46 5","pages":""},"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}
引用次数: 0
On the aerodynamics of dual-stage co-axial vertical-axis wind turbines 双级同轴垂直轴风力涡轮机的空气动力学研究
IF 1.5
Wind Engineering Pub Date : 2023-12-09 DOI: 10.1177/0309524x231212638
Muhammad Saif Ullah Khalid, Priscila Scarlet Portocarrero Mendoza, D. Wood, A. Hemmati
{"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":"20 8","pages":""},"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}
引用次数: 0
Innovative maximum power point tracking technique for wind energy conversion system 风能转换系统的创新型最大功率点跟踪技术
IF 1.5
Wind Engineering Pub Date : 2023-11-29 DOI: 10.1177/0309524x231201656
S. Tounsi
{"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":"1 1","pages":""},"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}
引用次数: 0
Optimization and techno-economic analysis of hybrid renewable energy systems for the electrification of remote areas 用于偏远地区电气化的混合可再生能源系统的优化和技术经济分析
IF 1.5
Wind Engineering Pub Date : 2023-11-27 DOI: 10.1177/0309524x231210266
Ameer Faisal, N. Anwer
{"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":"20 1","pages":""},"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}
引用次数: 0
A variable-time day-ahead scheduling strategy considering spectrum analysis 考虑频谱分析的变时日前调度策略
IF 1.5
Wind Engineering Pub Date : 2023-11-22 DOI: 10.1177/0309524x231206560
Yunlong Wang, Xinshuang Yao
{"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":"96 ","pages":""},"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}
引用次数: 0
A Bayesian deep learning framework for reliable fault diagnosis in wind turbine gearboxes under various operating conditions 贝叶斯深度学习框架，用于在各种运行条件下对风力涡轮机齿轮箱进行可靠的故障诊断
IF 1.5
Wind Engineering Pub Date : 2023-11-18 DOI: 10.1177/0309524x231206723
Abdelrahman Amin, A. Bibo, Meghashyam Panyam, Phanindra Tallapragada
{"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":"62 1","pages":""},"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}
引用次数: 0
High performance of variable-pitch wind system based on a direct matrix converter-fed DFIG using third order sliding mode control 利用三阶滑模控制，基于直接矩阵变换器供电的双馈变流器的高性能变桨距风力系统
IF 1.5
Wind Engineering Pub Date : 2023-11-17 DOI: 10.1177/0309524x231199435
A. Dendouga, A. Dendouga, N. Essounbouli
{"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":"11 4","pages":""},"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}
引用次数: 0
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