Smart Grid Opportunities and Challenges in Integrating Renewable Energies

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Cover image for research topic "Smart Grid Opportunities and Challenges in Integrating Renewable Energies"
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5
Muhammad Faizan Tahir
South China University of Technology
Salah Kamel
Aswan University
Jose Luis Domínguez-García
Energy Research Institute of Catalonia (IREC)
Khalid Mehmood Cheema
Fatima Jinnah Women University
Kashif Mehmood
Southeast University
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However, practically it becomes a challenging task because of the presence of harmonic distortions. In this study, a parameter estimation of the power system harmonics is investigated through swarm intelligence–based optimization strength of the cuckoo search algorithm. The performance evaluation is conducted in detail for different generations and particle sizes and for different signal-to-noise ratios. The simulation results reveal that the cuckoo search optimization heuristic accurately estimates the amplitude and phase parameters of the power system harmonics and is robust against different signal-to-noise ratios.","htmlAbstract":"\u003cp\u003eThe accurate estimation of power signal parameters allows smart grids to optimize power delivery efficiency, improve equipment utilization, and control power flow among generation nodes and loads. However, practically it becomes a challenging task because of the presence of harmonic distortions. In this study, a parameter estimation of the power system harmonics is investigated through swarm intelligence\u0026#x2013;based optimization strength of the cuckoo search algorithm. The performance evaluation is conducted in detail for different generations and particle sizes and for different signal-to-noise ratios. The simulation results reveal that the cuckoo search optimization heuristic accurately estimates the amplitude and phase parameters of the power system harmonics and is robust against different signal-to-noise ratios.\u003c/p\u003e","authors":[{"fullName":"Naveed Ahmed Malik","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Graduate School of Engineering Science and Technology","address":null},"affiliations":[{"name":"Graduate School of Engineering Science and Technology","address":null}],"nessieId":null},{"fullName":"Ching-Lung Chang","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Computer Science and Information Engineering","address":null},"affiliations":[{"name":"Department of Computer Science and Information Engineering","address":null}],"nessieId":null},{"fullName":"Naveed Ishtiaq Chaudhary","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/2005707/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/2005707/overview","affiliation":{"name":"Future Technology Research Center","address":null},"affiliations":[{"name":"Future Technology Research Center","address":null}],"nessieId":"249108634609"},{"fullName":"Zeshan Aslam Khan","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical and Computer Engineering","address":null},"affiliations":[{"name":"Department of Electrical and Computer Engineering","address":null}],"nessieId":null},{"fullName":"Muhammad Asif Zahoor Raja","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/959308/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/959308/overview","affiliation":{"name":"Future Technology Research Center","address":null},"affiliations":[{"name":"Future Technology Research Center","address":null}],"nessieId":"738735023499"},{"fullName":"Adiqa Kausar Kiani","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1836702/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1836702/overview","affiliation":{"name":"Future Technology Research Center","address":null},"affiliations":[{"name":"Future Technology Research Center","address":null}],"nessieId":"266288631124"},{"fullName":"Ahmed H. Milyani","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1308489/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1308489/overview","affiliation":{"name":"Department of Electrical and Computer Engineering","address":null},"affiliations":[{"name":"Department of Electrical and Computer Engineering","address":null}],"nessieId":"42950174480"},{"fullName":"Abdullah Ahmed Azhari","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"The Applied College","address":null},"affiliations":[{"name":"The Applied College","address":null}],"nessieId":null}],"dates":{"acceptedDate":"2022-10-25","recentDate":"2022-11-15"},"doi":"10.3389/fenrg.2022.1059132","frontiersExtra":{"articleType":"Original Research","impact":{"citations":9,"crossrefCitations":0,"downloads":406,"frontiersViews":0,"pmcDownloads":0,"pmcViews":0,"scopusCitations":0,"views":2339},"isPartOfResearchTopic":true,"isPublished":true,"section":"Smart Grids"},"guid":1059132,"images":[{"height":125,"url":"https://www.frontiersin.org/files/myhome article library/1059132/1059132_Thumb_400.jpg","width":400,"caption":null},{"height":702,"url":"https://www.frontiersin.org/files/Articles/1059132/fenrg-10-1059132-HTML/image_m/fenrg-10-1059132-g001.jpg","width":726,"caption":"Process flow structure of the CSO algorithm."},{"height":603,"url":"https://www.frontiersin.org/files/Articles/1059132/fenrg-10-1059132-HTML/image_m/fenrg-10-1059132-g002.jpg","width":768,"caption":"Convergence plots of Example 1: (A) G = 500, (B) G = 500, (C) G = 500, and (D) G = 500."},{"height":598,"url":"https://www.frontiersin.org/files/Articles/1059132/fenrg-10-1059132-HTML/image_m/fenrg-10-1059132-g003.jpg","width":768,"caption":"Convergence plots of Example 1: (A) G = 500, (B) G = 500, (C) G = 500, and (D) G = 500."}],"journal":{"guid":626,"name":"Frontiers in Energy Research","link":null,"nessieId":null,"palette":null,"publisher":"Frontiers Media","images":null,"isOnline":null,"isDeleted":null,"isDisabled":null,"issn":null},"link":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1059132","pubDate":"2022-11-15","score":14.510445407962237,"title":"Parameter estimation of harmonics arising in electrical instruments of smart grids using cuckoo search heuristics","topics":["parameter estimation","harmonics","Smart Grid","cuckoo search","swarm optimization"],"pdfUrl":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1059132/pdf"},{"__typename":"Feed_Article","_id":"680910683f397a5f12756ec8","abstract":"Given the greater penetration of wind power, the impact of wind generators on grid electricity reliability imposes additional requirements. One of the most common technologies in wind power generating schemes is the permanent magnet synchronous generator (PMSG) converter. However, the controller calculation is difficult due to the nonlinear dynamical and time-varying characteristics of this type of conversion system. This study develops a unique intelligent controller approach based on the passivity notion that tracks velocity and maintains it functioning at the optimum torque. To address the robustness issues encountered by traditional generator-side converter (MSC) strategies such as proportional-integral (PI), this suggested scheme integrates a passivity-based procedure with a fuzzy logic control (FLC) methodology for a PMSG-based wind power converter. The suggested controller is distinguished by the fact that the nonlinear features are compensated in a damped manner rather than canceled. To achieve the required dynamic, the fuzzy controller is used, which ensures quick convergence and global stability of the closed loop system. The development of the maximum power collected, the lowered fixed gains, and the real-time application of the control method are the primary contributions and novelties. The primary objectives of this project are to manage DC voltage and attain adequate reactive power levels in order to provide dependable and efficient electricity to the grid. The proposed scheme is being used to regulate the MSC, while the grid-side employs a traditional proportional-integral method. The efficiency of the suggested technique is investigated numerically using MATLAB/Simulink software. Furthermore, the processor-in-the-loop (PIL) tests are carried out to demonstrate that the suggested regulator is practically implementable.","htmlAbstract":"\u003cp\u003eGiven the greater penetration of wind power, the impact of wind generators on grid electricity reliability imposes additional requirements. One of the most common technologies in wind power generating schemes is the permanent magnet synchronous generator (PMSG) converter. However, the controller calculation is difficult due to the nonlinear dynamical and time-varying characteristics of this type of conversion system. This study develops a unique intelligent controller approach based on the passivity notion that tracks velocity and maintains it functioning at the optimum torque. To address the robustness issues encountered by traditional generator-side converter (MSC) strategies such as proportional-integral (PI), this suggested scheme integrates a passivity-based procedure with a fuzzy logic control (FLC) methodology for a PMSG-based wind power converter. The suggested controller is distinguished by the fact that the nonlinear features are compensated in a damped manner rather than canceled. To achieve the required dynamic, the fuzzy controller is used, which ensures quick convergence and global stability of the closed loop system. The development of the maximum power collected, the lowered fixed gains, and the real-time application of the control method are the primary contributions and novelties. The primary objectives of this project are to manage DC voltage and attain adequate reactive power levels in order to provide dependable and efficient electricity to the grid. The proposed scheme is being used to regulate the MSC, while the grid-side employs a traditional proportional-integral method. The efficiency of the suggested technique is investigated numerically using MATLAB/Simulink software. Furthermore, the processor-in-the-loop (PIL) tests are carried out to demonstrate that the suggested regulator is practically implementable.\u003c/p\u003e","authors":[{"fullName":"Ashish Jaiswal","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Youcef Belkhier","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1462341/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1462341/overview","affiliation":{"name":"Centre for Ocean Energy Research","address":null},"affiliations":[{"name":"Centre for Ocean Energy Research","address":null}],"nessieId":"618475944656"},{"fullName":"Subhash Chandra","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Anurag Priyadarshi","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Mohit Bajaj","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1589398/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1589398/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":"34360381990"},{"fullName":"Mukesh Pushkarna","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Elmazeg Elgamli","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1771796/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1771796/overview","affiliation":{"name":"Wolfson Centre for Magnetics","address":null},"affiliations":[{"name":"Wolfson Centre for Magnetics","address":null}],"nessieId":null},{"fullName":"Mokhtar Shouran","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1770092/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1770092/overview","affiliation":{"name":"Wolfson Centre for Magnetics","address":null},"affiliations":[{"name":"Wolfson Centre for Magnetics","address":null}],"nessieId":null},{"fullName":"Salah Kamel","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/923973/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/923973/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":"42950326297"}],"dates":{"acceptedDate":"2022-07-12","recentDate":"2022-09-28"},"doi":"10.3389/fenrg.2022.966975","frontiersExtra":{"articleType":"Original Research","impact":{"citations":11,"crossrefCitations":0,"downloads":3,"frontiersViews":0,"pmcDownloads":0,"pmcViews":0,"scopusCitations":0,"views":2819},"isPartOfResearchTopic":true,"isPublished":true,"section":"Smart Grids"},"guid":966975,"images":[{"height":246,"url":"https://www.frontiersin.org/files/myhome article library/966975/966975_Thumb_400.jpg","width":400,"caption":null},{"height":402,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g001.jpg","width":809,"caption":"Wind power system."},{"height":840,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g002.jpg","width":941,"caption":"Schematic of the proposed controller."},{"height":234,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g003.jpg","width":512,"caption":"Desired torque computation."},{"height":619,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g004.jpg","width":803,"caption":"Fuzzy rules. (A) Function’s inputs (B) Outputs function."},{"height":875,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g005.jpg","width":941,"caption":"GSC PI controller schematic."},{"height":241,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g006.jpg","width":512,"caption":"Wind speed."},{"height":263,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g007.jpg","width":512,"caption":"DC-link voltage."},{"height":276,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g008.jpg","width":512,"caption":"DC-link response compared with conventional controls."},{"height":548,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g009.jpg","width":512,"caption":"Reactive power response of the tested controls."},{"height":256,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g010.jpg","width":512,"caption":"Zoom on convergence speed of the reactive power."},{"height":273,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g011.jpg","width":512,"caption":"Electromagnetic torque under parameter changes."},{"height":286,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g012.jpg","width":512,"caption":"DC-link voltage under parameter changes."},{"height":248,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g013.jpg","width":512,"caption":"Reactive power response under parameter changes."},{"height":580,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g014.jpg","width":512,"caption":"DC-link response of the tested controls under parameter changes."},{"height":276,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g015.jpg","width":512,"caption":"Reactive power response of the tested controls under parameter changes."},{"height":440,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g016.jpg","width":899,"caption":"Zoom on reactive power response of the tested controls under parameter changes"},{"height":234,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g017.jpg","width":512,"caption":"Active and reactive powers response."},{"height":496,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g018.jpg","width":809,"caption":"Experimental Step."},{"height":195,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g019.jpg","width":512,"caption":"Wind profile used for the PIL experiment."},{"height":300,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g020.jpg","width":512,"caption":"PIL testing DC voltage."},{"height":287,"url":"https://www.frontiersin.org/files/Articles/966975/fenrg-10-966975-HTML/image_m/fenrg-10-966975-g021.jpg","width":512,"caption":"PIL testing grid powers."}],"journal":{"guid":626,"name":"Frontiers in Energy Research","link":null,"nessieId":null,"palette":null,"publisher":"Frontiers Media","images":null,"isOnline":null,"isDeleted":null,"isDisabled":null,"issn":null},"link":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.966975","pubDate":"2022-09-28","score":17.640914465904704,"title":"Design and implementation of energy reshaping based fuzzy logic control for optimal power extraction of PMSG wind energy converter","topics":["Renewable energy systems","Nonlinear Control","Fuzzy logic control","Power extraction","processor-in-the loop (PIL) experiments"],"pdfUrl":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.966975/pdf"},{"__typename":"Feed_Article","_id":"680910683f397a5f12756ec1","abstract":"Electric power industry is continually adopting new techniques to improve the reliability and efficiency of the energy system and to cope with the increasing energy demand and the associated technical challenges. In recent years, the maturation of Artificial Intelligence (AI) led researchers to solve various problems in the power system by using AI techniques. Voltage Source Converter is the result of advancements in the field of power electronics and semiconductors technology, which holds a promising future for the realization of smart grid, renewable energy integration, and HVDC transmission system. Usually hit and trial method or the design engineer’s experience is used for the manual tuning of the PI controllers, which cannot yield superior performance. The process becomes more complicated when multiple grids are involved, such as in VSC-based MTDC grids. This research article use a deep learning optimization technique for the tuning of the VSC controllers, which resulted in quick settling time, better slew rate, less undershoot and low overshoot. The deep learning neural network is trained through the Particle Swarm Optimization (PSO) algorithm to produce the best possible tuned or optimally tuned parameters for the controllers. The optimal tuning of the controller will result in an overall better performance of the converter and the grid. A four-layered deep learning neural network and a three-terminal MTDC grid were designed and simulated in MATLAB/SIMULINK environment.","htmlAbstract":"\u003cp\u003eElectric power industry is continually adopting new techniques to improve the reliability and efficiency of the energy system and to cope with the increasing energy demand and the associated technical challenges. In recent years, the maturation of Artificial Intelligence (AI) led researchers to solve various problems in the power system by using AI techniques. Voltage Source Converter is the result of advancements in the field of power electronics and semiconductors technology, which holds a promising future for the realization of smart grid, renewable energy integration, and HVDC transmission system. Usually hit and trial method or the design engineer\u0026#x2019;s experience is used for the manual tuning of the PI controllers, which cannot yield superior performance. The process becomes more complicated when multiple grids are involved, such as in VSC-based MTDC grids. This research article use a deep learning optimization technique for the tuning of the VSC controllers, which resulted in quick settling time, better slew rate, less undershoot and low overshoot. The deep learning neural network is trained through the Particle Swarm Optimization (PSO) algorithm to produce the best possible tuned or optimally tuned parameters for the controllers. The optimal tuning of the controller will result in an overall better performance of the converter and the grid. A four-layered deep learning neural network and a three-terminal MTDC grid were designed and simulated in MATLAB/SIMULINK environment.\u003c/p\u003e","authors":[{"fullName":"Shahid Aziz Khan","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1955839/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1955839/overview","affiliation":{"name":"Department of Electrical and Computer Engineering","address":null},"affiliations":[{"name":"Department of Electrical and Computer Engineering","address":null}],"nessieId":null},{"fullName":"Jamshed Ahmed Ansari","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1959183/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1959183/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Rashid Hussain Chandio","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Hafiz Mudassir Munir","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1588980/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1588980/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":"876173855484"},{"fullName":"Mohammed Alharbi","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1913036/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1913036/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Abdulaziz Alkuhayli","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null}],"dates":{"acceptedDate":"2022-08-17","recentDate":"2022-09-23"},"doi":"10.3389/fenrg.2022.1008099","frontiersExtra":{"articleType":"Original Research","impact":{"citations":7,"crossrefCitations":0,"downloads":3,"frontiersViews":0,"pmcDownloads":0,"pmcViews":0,"scopusCitations":0,"views":2475},"isPartOfResearchTopic":true,"isPublished":true,"section":"Smart Grids"},"guid":1008099,"images":[{"height":176,"url":"https://www.frontiersin.org/files/myhome article 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in Energy Research","link":null,"nessieId":null,"palette":null,"publisher":"Frontiers Media","images":null,"isOnline":null,"isDeleted":null,"isDisabled":null,"issn":null},"link":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1008099","pubDate":"2022-09-23","score":12.836815135987468,"title":"AI based controller optimization for VSC-MTDC grids","topics":["optimization","artificial intelligence","deep learning","Smart Grid","Smartgrid","particle swarm optimization (PSO)","Voltage Source Converter"],"pdfUrl":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1008099/pdf"},{"__typename":"Feed_Article","_id":"680910683f397a5f12756ec4","abstract":"Many studies have been made on the double-fed induction generator wind turbine system (DFIG-WTS) in recent decades due to its power management capability, speed control operation, low converter cost, and minimized energy losses. In contrast, induction machine control is a more complex task because of its multivariable and nonlinear nature. In this work, a new robust nonlinear generalized predictive control (RNGPC) is developed to maximize the extracted energy from the wind without the use of aerodynamic torque measurements or an observer. The aim of the predictive control is to produce an anticipated impact by employing explicit knowledge of the present condition. By revisiting the cost function of the conventional nonlinear generalized predictive control (NGPC), which is based on Taylor series expansion, in that way, the resilience of the system is improved. An integral action is included in the nonlinear predictive controller. As a result, if the closed loop system is stable, the suggested controller totally eliminates the steady state error, even if unknown perturbations and mismatched parameters are present. The output locating error’s convergence to the source is utilized to show the locked system’s stability. Simulation results demonstrate and verify the efficiency, the good performance, and robustness of this proposed control technique.","htmlAbstract":"\u003cp\u003eMany studies have been made on the double-fed induction generator wind turbine system (DFIG-WTS) in recent decades due to its power management capability, speed control operation, low converter cost, and minimized energy losses. In contrast, induction machine control is a more complex task because of its multivariable and nonlinear nature. In this work, a new robust nonlinear generalized predictive control (RNGPC) is developed to maximize the extracted energy from the wind without the use of aerodynamic torque measurements or an observer. The aim of the predictive control is to produce an anticipated impact by employing explicit knowledge of the present condition. By revisiting the cost function of the conventional nonlinear generalized predictive control (NGPC), which is based on Taylor series expansion, in that way, the resilience of the system is improved. An integral action is included in the nonlinear predictive controller. As a result, if the closed loop system is stable, the suggested controller totally eliminates the steady state error, even if unknown perturbations and mismatched parameters are present. The output locating error\u0026#x2019;s convergence to the source is utilized to show the locked system\u0026#x2019;s stability. Simulation results demonstrate and verify the efficiency, the good performance, and robustness of this proposed control technique.\u003c/p\u003e","authors":[{"fullName":"Kamel Ouari","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1924694/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1924694/overview","affiliation":{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null},"affiliations":[{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null}],"nessieId":"695785237718"},{"fullName":"Youcef Belkhier","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1462341/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1462341/overview","affiliation":{"name":"Centre for Ocean Energy Research","address":null},"affiliations":[{"name":"Centre for Ocean Energy Research","address":null}],"nessieId":"618475944656"},{"fullName":"Hafidh Djouadi","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1851109/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1851109/overview","affiliation":{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null},"affiliations":[{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null}],"nessieId":null},{"fullName":"Amel Kasri","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1925312/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1925312/overview","affiliation":{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null},"affiliations":[{"name":"Laboratory of Industrial and Information Technology (LTII)","address":null}],"nessieId":"523986535823"},{"fullName":"Mohit Bajaj","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1589398/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1589398/overview","affiliation":{"name":"Department of Electrical and Electronics Engineering","address":null},"affiliations":[{"name":"Department of Electrical and Electronics Engineering","address":null},{"name":"Department of Electrical Engineering","address":null}],"nessieId":"34360381990"},{"fullName":"Mohammad Alsharef","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Ehab E. Elattar","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":null},{"fullName":"Salah Kamel","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/923973/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/923973/overview","affiliation":{"name":"Electrical Engineering Department","address":null},"affiliations":[{"name":"Electrical Engineering Department","address":null}],"nessieId":"42950326297"}],"dates":{"acceptedDate":"2022-08-01","recentDate":"2022-09-23"},"doi":"10.3389/fenrg.2022.996206","frontiersExtra":{"articleType":"Original Research","impact":{"citations":15,"crossrefCitations":0,"downloads":10,"frontiersViews":0,"pmcDownloads":0,"pmcViews":0,"scopusCitations":0,"views":2386},"isPartOfResearchTopic":true,"isPublished":true,"section":"Smart Grids"},"guid":996206,"images":[{"height":256,"url":"https://www.frontiersin.org/files/myhome article library/996206/996206_Thumb_400.jpg","width":400,"caption":null},{"height":318,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g001.jpg","width":754,"caption":"DFIG-based wind energy converter."},{"height":220,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g002.jpg","width":401,"caption":"Power coefficient Cp (λ, β)."},{"height":282,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g003.jpg","width":457,"caption":"Voltage and flux vectors settings."},{"height":530,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g004.jpg","width":754,"caption":"Block Diagram of the proposed RNGPC applied to the RSC."},{"height":313,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g005.jpg","width":457,"caption":"Wind speed profile."},{"height":290,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g006.jpg","width":457,"caption":"Rotor speed response."},{"height":297,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g007.jpg","width":457,"caption":"Electromagnetic torque."},{"height":291,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g008.jpg","width":457,"caption":"DFIG slip."},{"height":278,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g009.jpg","width":457,"caption":"DFIG active power."},{"height":284,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g010.jpg","width":457,"caption":"DFIG reactive power."},{"height":601,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g011.jpg","width":941,"caption":"(A) Rotor voltage and current, (B) sub-synchronous mode, (C) synchronous mode, and (D) super-synchronous mode."},{"height":323,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g012.jpg","width":1079,"caption":"Speed tracking underprediction horizon change: (A) for Tp2 = 15 ms and (B) for Tp2 = 1.5 ms."},{"height":337,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g013.jpg","width":1079,"caption":"Speed tracking error under prediction horizon change: (A) for Tp2 = 15 ms and (B) for Tp2 = 1 ms."},{"height":358,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g014.jpg","width":1079,"caption":"Electromagnetic torque tracking underprediction horizon change: (A) for Tp2 = 15 ms and (B) for Tp2 = 1.5 ms."},{"height":355,"url":"https://www.frontiersin.org/files/Articles/996206/fenrg-10-996206-HTML/image_m/fenrg-10-996206-g015.jpg","width":1079,"caption":"Electromagnetic torque tracking error underprediction horizon change: (A) for Tp2 = 15 ms and (B) for Tp2 = 1.5 ms."}],"journal":{"guid":626,"name":"Frontiers in Energy Research","link":null,"nessieId":null,"palette":null,"publisher":"Frontiers Media","images":null,"isOnline":null,"isDeleted":null,"isDisabled":null,"issn":null},"link":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.996206","pubDate":"2022-09-23","score":20.60741032715814,"title":"Improved nonlinear generalized model predictive control for robustness and power enhancement of a DFIG-based wind energy converter","topics":["Wind","Doubly fed induction generator","controller","DFIG wind turbine systems","robust generalized predictive control"],"pdfUrl":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.996206/pdf"},{"__typename":"Feed_Article","_id":"680910683f397a5f12756ec3","abstract":"Sustainable, inexhaustible, economical, and clean energy has become a vital prerequisite to replace fossil fuel sources for power production. In such a context, countries like Pakistan, which are heavily skewed towards fossil fuel-fired plants, are diverting attention to install more and more indigenous renewable energy sources projects such as solar-photovoltaic and wind turbine power plants. In order to harness the maximum energy of wind turbines, it is crucial to factually and precisely assess system performance, which is traditionally inferred by energy analysis (first law analysis). Nevertheless, this analysis only computes the nominal power generation output and ignores the effect of meteorological variables that can lead to some serious errors during the energy planning phase. Consequently, this case study presents both the energy and exergy analysis of a wind farm located in Gharo town of Thatta District along the coastline of the Indus Delta. Energy analysis is carried out to quantify energy efficiency, while exergy analysis computes exergy efficiency by taking into account the effect of pressure, temperature, and wind speed. Comparisons of both efficiencies are provided, and the result substantiates that exergy efficiency turns out to be lower than energy efficiency. However, exergy is a more viable index due to the inclusion of exergy destruction, and in comparison to the energy indicator, it presents the actual performance of a thermodynamic system. The monthly energy and exergy efficiency of the general electric wind turbines are maximum in July having values of 0.5 and 0.41, respectively.","htmlAbstract":"\u003cp\u003eSustainable, inexhaustible, economical, and clean energy has become a vital prerequisite to replace fossil fuel sources for power production. In such a context, countries like Pakistan, which are heavily skewed towards fossil fuel-fired plants, are diverting attention to install more and more indigenous renewable energy sources projects such as solar-photovoltaic and wind turbine power plants. In order to harness the maximum energy of wind turbines, it is crucial to factually and precisely assess system performance, which is traditionally inferred by energy analysis (first law analysis). Nevertheless, this analysis only computes the nominal power generation output and ignores the effect of meteorological variables that can lead to some serious errors during the energy planning phase. Consequently, this case study presents both the energy and exergy analysis of a wind farm located in Gharo town of Thatta District along the coastline of the Indus Delta. Energy analysis is carried out to quantify energy efficiency, while exergy analysis computes exergy efficiency by taking into account the effect of pressure, temperature, and wind speed. Comparisons of both efficiencies are provided, and the result substantiates that exergy efficiency turns out to be lower than energy efficiency. However, exergy is a more viable index due to the inclusion of exergy destruction, and in comparison to the energy indicator, it presents the actual performance of a thermodynamic system. The monthly energy and exergy efficiency of the general electric wind turbines are maximum in July having values of 0.5 and 0.41, respectively.\u003c/p\u003e","authors":[{"fullName":"Muhammad Faizan Tahir","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1783960/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1783960/overview","affiliation":{"name":"School of Electric Power","address":null},"affiliations":[{"name":"School of Electric Power","address":null}],"nessieId":"137439612343"},{"fullName":"Chen Haoyong","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"School of Electric Power","address":null},"affiliations":[{"name":"School of Electric Power","address":null}],"nessieId":null},{"fullName":"Han Guangze","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"School of Physics and Optoelectronics","address":null},"affiliations":[{"name":"School of Physics and Optoelectronics","address":null}],"nessieId":null},{"fullName":"Kashif Mehmood","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1070761/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1070761/overview","affiliation":{"name":"Department of Electrical Engineering","address":null},"affiliations":[{"name":"Department of Electrical Engineering","address":null}],"nessieId":"695785249054"}],"dates":{"acceptedDate":"2022-08-22","recentDate":"2022-09-20"},"doi":"10.3389/fenrg.2022.1008989","frontiersExtra":{"articleType":"Original Research","impact":{"citations":4,"crossrefCitations":0,"downloads":2,"frontiersViews":0,"pmcDownloads":0,"pmcViews":0,"scopusCitations":0,"views":5332},"isPartOfResearchTopic":true,"isPublished":true,"section":"Smart Grids"},"guid":1008989,"images":[{"height":223,"url":"https://www.frontiersin.org/files/myhome article library/1008989/1008989_Thumb_400.jpg","width":401,"caption":null},{"height":443,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g001.jpg","width":754,"caption":"Wind farm location map."},{"height":464,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g002.jpg","width":505,"caption":"Side view of the horizontal axis three-blade wind turbine."},{"height":307,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g003.jpg","width":512,"caption":"2.3 MW general electric wind turbine power curve."},{"height":355,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g004.jpg","width":754,"caption":"Average temperature and pressure of the Gharo site."},{"height":391,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g005.jpg","width":754,"caption":"Wind variation for the Gharo site."},{"height":450,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g006.jpg","width":754,"caption":"Monthly energy and exergy efficiency quantification of GE-wind turbine."},{"height":434,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g007.jpg","width":754,"caption":"Exergy efficiency variation with changing temperature, pressure, and wind speed."},{"height":389,"url":"https://www.frontiersin.org/files/Articles/1008989/fenrg-10-1008989-HTML/image_m/fenrg-10-1008989-g008.jpg","width":699,"caption":"Monthly exergy destruction variation."}],"journal":{"guid":626,"name":"Frontiers in Energy Research","link":null,"nessieId":null,"palette":null,"publisher":"Frontiers Media","images":null,"isOnline":null,"isDeleted":null,"isDisabled":null,"issn":null},"link":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1008989","pubDate":"2022-09-20","score":16.60070949940892,"title":"Energy and exergy analysis of wind power plant: A case study of Gharo, Pakistan","topics":["Efficiency","Pakistan","Renewable Energy","wind energy","Energy analysis and exergy analysis"],"pdfUrl":"https://www.frontiersin.org/articles/10.3389/fenrg.2022.1008989/pdf"},{"__typename":"Feed_Article","_id":"680910683f397a5f12756ec5","abstract":"This paper presents the performances of an artificial intelligent fuzzy logic controller (FLC) based maximum power point tracking (MPPT) and a conventional perturb and observe (P\u0026O) based MPPT controller is presented for a stand-alone PV system and tested in an emulated test bench experimentation. The studied system is composed of a DC power supply emulating the PV panel, a DC/DC boost converter, a variable resistive load and a real-time MPPT controller implemented in the dSPACE DS1104 controller. To verify the performance of the FLC proposed, several simulations have been performed in Matlab/Simulink environment. The proposed method outperforms the P\u0026O method in terms of global search capability and dynamic performance, according to the comparison with the P\u0026O method. To verify the practical implementation of the proposed method, the control of the emulated PV source and the MPPT algorithms are designed using the simulink/Matlab environment and implemented on dSPACE DS1104 controller. Experimental results confirm the efficiency of the proposed method and its high accuracy to handle the resistance varying.","htmlAbstract":"\u003cp\u003eThis paper presents the performances of an artificial intelligent fuzzy logic controller (FLC) based maximum power point tracking (MPPT) and a conventional perturb and observe (P\u0026amp;O) based MPPT controller is presented for a stand-alone PV system and tested in an emulated test bench experimentation. The studied system is composed of a DC power supply emulating the PV panel, a DC/DC boost converter, a variable resistive load and a real-time MPPT controller implemented in the dSPACE DS1104 controller. To verify the performance of the FLC proposed, several simulations have been performed in Matlab/Simulink environment. The proposed method outperforms the P\u0026amp;O method in terms of global search capability and dynamic performance, according to the comparison with the P\u0026amp;O method. To verify the practical implementation of the proposed method, the control of the emulated PV source and the MPPT algorithms are designed using the simulink/Matlab environment and implemented on dSPACE DS1104 controller. Experimental results confirm the efficiency of the proposed method and its high accuracy to handle the resistance varying.\u003c/p\u003e","authors":[{"fullName":"Fatah Yahiaoui","firstName":null,"middleName":null,"lastName":null,"image":{"height":null,"url":"https://loop.frontiersin.org/images/profile/1872693/70","width":null,"caption":null},"loopProfileUrl":"https://loop.frontiersin.org/people/1872693/overview","affiliation":{"name":"Laboratoire de Technologie Industrielle et de l’Information (LTII)","address":null},"affiliations":[{"name":"Laboratoire de Technologie Industrielle et de l’Information (LTII)","address":null}],"nessieId":null},{"fullName":"Ferhat Chabour","firstName":null,"middleName":null,"lastName":null,"image":null,"loopProfileUrl":null,"affiliation":{"name":"GREAH Laboratory","address":null},"affiliations":[{"name":"GREAH Laboratory","address":null}],"nessieId":null},{"fullName":"Ouahib 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