Pub Date : 2020-12-07DOI: 10.1109/PECon48942.2020.9314390
H. Zeynal, Z. Zakaria, Ahmad Kor, Ahmad Yaghoobi
Non-Linear control is a significant part of every industry’s control process. A number of methods have been introduced to model the nonlinearity existed in the control model. Predictive control which is a model-based control method is one of the advanced control methods in practical applications because it can be implemented in time-domain, and easy constraint handling during the design process, as well as the capability of implementing multi-variable systems. A linearized Volterra model for NMC can be proposed to convert the nonlinearity of the system into a series of linearly equivalent expressions. Obtained results show that linearized Volterra series can effectively model dynamic non-linear systems which further allowed employing the proposed model for predictive control. The results reiterate that the use of the Volterra series is comparatively simple and promising in terms of non-stable system modeling.
{"title":"An Efficient Linearized Volterra Series for Nonlinear Model Predictive Control in Dynamic Systems","authors":"H. Zeynal, Z. Zakaria, Ahmad Kor, Ahmad Yaghoobi","doi":"10.1109/PECon48942.2020.9314390","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314390","url":null,"abstract":"Non-Linear control is a significant part of every industry’s control process. A number of methods have been introduced to model the nonlinearity existed in the control model. Predictive control which is a model-based control method is one of the advanced control methods in practical applications because it can be implemented in time-domain, and easy constraint handling during the design process, as well as the capability of implementing multi-variable systems. A linearized Volterra model for NMC can be proposed to convert the nonlinearity of the system into a series of linearly equivalent expressions. Obtained results show that linearized Volterra series can effectively model dynamic non-linear systems which further allowed employing the proposed model for predictive control. The results reiterate that the use of the Volterra series is comparatively simple and promising in terms of non-stable system modeling.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"60 1","pages":"415-419"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84462748","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 : 2020-12-07DOI: 10.1109/pecon48942.2020.9314301
{"title":"PECon 2020 Cover Page","authors":"","doi":"10.1109/pecon48942.2020.9314301","DOIUrl":"https://doi.org/10.1109/pecon48942.2020.9314301","url":null,"abstract":"","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80189140","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314467
Altwallbah Neda Mahmod Mohammad, Mohd Amran Mohd Radzi, N. Azis, S. Shafie, Muhammad Ammirrul Atiqi Mohd
Efficient extraction of maximum available power from photovoltaic (PV) systems can be deteriorated due to the vulnerability to weather conditions, especially, under partial shading conditions (PSCs). This paper presents a robust maximum power point tracking (MPPT) algorithm which is able to work under any level of PSC efficiently, accurately, rapidly and with no increase in complexity. The proposed algorithm employs the composite trapezoidal rule to locate the actual maximum power based on trapezoidal area estimation concept, with the assist of adaptable step size perturbation and observation (P&O) algorithm. Complex PSC levels have been chosen to guarantee the validity of the suggested algorithm to perform under any shading level. The simulation results approve the effectivity of the algorithm under three various cases of complex PSCs, and compared with performance of the conventional Perturbation and Observation (P&O) and Incremental Conductance (IC) MPPT algorithms. The results indicate the success of the proposed algorithm, and the weakness of the conventional algorithms in seeking the actual maximum power under PSC which is the global maximum power point (GMPP).
{"title":"Composite Trapezoidal Rule-based maximum power point tracking algorithm for photovoltaic systems under complex shading conditions","authors":"Altwallbah Neda Mahmod Mohammad, Mohd Amran Mohd Radzi, N. Azis, S. Shafie, Muhammad Ammirrul Atiqi Mohd","doi":"10.1109/PECon48942.2020.9314467","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314467","url":null,"abstract":"Efficient extraction of maximum available power from photovoltaic (PV) systems can be deteriorated due to the vulnerability to weather conditions, especially, under partial shading conditions (PSCs). This paper presents a robust maximum power point tracking (MPPT) algorithm which is able to work under any level of PSC efficiently, accurately, rapidly and with no increase in complexity. The proposed algorithm employs the composite trapezoidal rule to locate the actual maximum power based on trapezoidal area estimation concept, with the assist of adaptable step size perturbation and observation (P&O) algorithm. Complex PSC levels have been chosen to guarantee the validity of the suggested algorithm to perform under any shading level. The simulation results approve the effectivity of the algorithm under three various cases of complex PSCs, and compared with performance of the conventional Perturbation and Observation (P&O) and Incremental Conductance (IC) MPPT algorithms. The results indicate the success of the proposed algorithm, and the weakness of the conventional algorithms in seeking the actual maximum power under PSC which is the global maximum power point (GMPP).","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"11 1","pages":"270-275"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75419615","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314395
J. Yunas, N. H. Mohd Yunus, J. Sampe, A. Nandiyanto
This paper describes the design and fabrication of MEMS patch antenna fabricated on glass substrate for RF energy harvester system. The idea was derived from the great property of glass, such as transparency, high mechanical surface strength and good dielectric property that is predicted to replace the conventional and silicon semiconductor material as the substrate for an RF energy capture. Aim of the study is to develop MEMS patch antenna that should be compatible with 180 nm CMOS process. The antenna device consists of a substrate, slotted petal conductor, ground plane and impedance matched output slot. The substrate is made of pyrex glass and fabricated using a surface micromachine process technique. The fabricated device is then measured in an anechoic chamber and compared with other antenna made of silicon and standard conventional antenna substrate. The results show that the patch antenna on glass performs similar to the conventional antenna fabricated on RT/Duroid that show very promising alternative substrate material for an energy harvester system where size, weight, cost, performance, ease of installation and fabrication are constrains.
{"title":"Design and Fabrication of Glass based MEMS Patch Antenna for Energy Harvester","authors":"J. Yunas, N. H. Mohd Yunus, J. Sampe, A. Nandiyanto","doi":"10.1109/PECon48942.2020.9314395","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314395","url":null,"abstract":"This paper describes the design and fabrication of MEMS patch antenna fabricated on glass substrate for RF energy harvester system. The idea was derived from the great property of glass, such as transparency, high mechanical surface strength and good dielectric property that is predicted to replace the conventional and silicon semiconductor material as the substrate for an RF energy capture. Aim of the study is to develop MEMS patch antenna that should be compatible with 180 nm CMOS process. The antenna device consists of a substrate, slotted petal conductor, ground plane and impedance matched output slot. The substrate is made of pyrex glass and fabricated using a surface micromachine process technique. The fabricated device is then measured in an anechoic chamber and compared with other antenna made of silicon and standard conventional antenna substrate. The results show that the patch antenna on glass performs similar to the conventional antenna fabricated on RT/Duroid that show very promising alternative substrate material for an energy harvester system where size, weight, cost, performance, ease of installation and fabrication are constrains.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"180 1","pages":"362-365"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77355486","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314429
Praveen Kumar, Lovesh B. Xaxa, R. Srivastava
The capability of Linear Permanent Magnet (LPM) machines to produce high thrust and power density are being utilized in industrial and defense sectors these days. However, the reluctance variation faced by secondary magnet flux due to primary slotting and end effects produces detent or cogging force, which results in high force ripples, noise and vibrations. This effects the smooth starting and controllability of the machine in accurate positioning applications. This paper proposes some design modifications in the primary slots and slot-openings of LPM machines for detent force minimization. The effect of various design modifications on cogging force, average electromagnetic force and force ripple has been studied using 3-D Finite Element analysis. The analysis results are also compared with that obtained using some existing cogging reduction techniques.
{"title":"Design Modifications for Cogging Force Reduction in Linear Permanent Magnet Machines","authors":"Praveen Kumar, Lovesh B. Xaxa, R. Srivastava","doi":"10.1109/PECon48942.2020.9314429","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314429","url":null,"abstract":"The capability of Linear Permanent Magnet (LPM) machines to produce high thrust and power density are being utilized in industrial and defense sectors these days. However, the reluctance variation faced by secondary magnet flux due to primary slotting and end effects produces detent or cogging force, which results in high force ripples, noise and vibrations. This effects the smooth starting and controllability of the machine in accurate positioning applications. This paper proposes some design modifications in the primary slots and slot-openings of LPM machines for detent force minimization. The effect of various design modifications on cogging force, average electromagnetic force and force ripple has been studied using 3-D Finite Element analysis. The analysis results are also compared with that obtained using some existing cogging reduction techniques.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"39 1","pages":"392-397"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73680984","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314474
Anggraini Puspita Sari, Hiroshi Suzuki, T. Kitajima, T. Yasuno, D. A. Prasetya, Nachrowie Nachrowie
This paper proposes the prediction model of wind speed and direction using convolutional neural network - long short-term memory (CNN-LSTM). The proposed prediction model combines CNN, LSTM, and fully connected neural networks (FCNN) which are useful for getting high prediction accuracy of wind speed and direction for wind power. Performances of the prediction models are evaluated by using root mean square error (RMSE) between actual measurement data and predicted data. To verify the effectiveness of the proposed prediction model in comparison with that using FCNN, CNN, or LSTM model. The usefulness of the proposed prediction model is evaluated from the improvement of prediction accuracy for each season. The proposed prediction model using CNN-LSTM can improve 27.95 – 42.16% for wind speed and 28.71 – 35.15% for wind direction depending on the season in comparison with using the FCNN that is a higher accuracy than CNN and LSTM models, and also it indicates the strongest prediction model.
{"title":"Prediction Model of Wind Speed and Direction using Convolutional Neural Network - Long Short Term Memory","authors":"Anggraini Puspita Sari, Hiroshi Suzuki, T. Kitajima, T. Yasuno, D. A. Prasetya, Nachrowie Nachrowie","doi":"10.1109/PECon48942.2020.9314474","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314474","url":null,"abstract":"This paper proposes the prediction model of wind speed and direction using convolutional neural network - long short-term memory (CNN-LSTM). The proposed prediction model combines CNN, LSTM, and fully connected neural networks (FCNN) which are useful for getting high prediction accuracy of wind speed and direction for wind power. Performances of the prediction models are evaluated by using root mean square error (RMSE) between actual measurement data and predicted data. To verify the effectiveness of the proposed prediction model in comparison with that using FCNN, CNN, or LSTM model. The usefulness of the proposed prediction model is evaluated from the improvement of prediction accuracy for each season. The proposed prediction model using CNN-LSTM can improve 27.95 – 42.16% for wind speed and 28.71 – 35.15% for wind direction depending on the season in comparison with using the FCNN that is a higher accuracy than CNN and LSTM models, and also it indicates the strongest prediction model.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"187 1","pages":"356-361"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76570836","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314293
N. A. Mohd Fadzil, M. Hairi, F. Hanaffi, M. Kamarudin, M. F. Mohamed, S. A. Sobri
The modern electrical grid portrays an increase in Distributed Generation (DG) application in order to satisfy the demand of electricity. These DG infiltrations altered the classical grid architecture hence affecting the grid protection structure specifically in related to the islanding situation. Unintentional islanding brings serious threat to the maintenance personnel in charge of the islanded grid, electrical instruments as well as the DG connected in the microgrid. A lot of researches were already conducted and continuously done in the chase of an ideal anti-islanding strategy, whilst the ideal one is yet to be acquired. This paper proposes an islanding detection strategy based on monitoring the rate of change of positive sequence of voltage (ROCOPV). Simulations are conducted for several islanding situations that include the deficit, surplus, and balanced islanding cases, hence the output procured is promising. The ROCOPV efficiently detect all demonstrated islanding cases within 0.05 s without any non-detection zone (NDZ).
{"title":"Utilising Rate of Change of Positive Sequence of Voltage as an Anti-Islanding Strategy for Distributed Generation","authors":"N. A. Mohd Fadzil, M. Hairi, F. Hanaffi, M. Kamarudin, M. F. Mohamed, S. A. Sobri","doi":"10.1109/PECon48942.2020.9314293","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314293","url":null,"abstract":"The modern electrical grid portrays an increase in Distributed Generation (DG) application in order to satisfy the demand of electricity. These DG infiltrations altered the classical grid architecture hence affecting the grid protection structure specifically in related to the islanding situation. Unintentional islanding brings serious threat to the maintenance personnel in charge of the islanded grid, electrical instruments as well as the DG connected in the microgrid. A lot of researches were already conducted and continuously done in the chase of an ideal anti-islanding strategy, whilst the ideal one is yet to be acquired. This paper proposes an islanding detection strategy based on monitoring the rate of change of positive sequence of voltage (ROCOPV). Simulations are conducted for several islanding situations that include the deficit, surplus, and balanced islanding cases, hence the output procured is promising. The ROCOPV efficiently detect all demonstrated islanding cases within 0.05 s without any non-detection zone (NDZ).","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"30 1","pages":"176-181"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82069667","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314535
Foo Kheng Hong, Wong Jee Keen Raymond, Oon Kheng Heong, Tze Mei Kuan
With the proliferation of distributed generation (DG), the distributed network had become more complex. Such complexity will lead to difficulty for fault location in the distributed network. It may degrade the precision of existing fault location methods. Therefore, this paper will investigate the impact of distributed generation toward machine learning (ML) based fault location. Three categories of fault location had been tested which is fault type prediction, fault section prediction, and fault distance prediction with and without DG presence. The accuracy of machine learning based fault location is verified in IEEE 16 bus network and the impact due to the presence of DG, represented using photovoltaic (PV) generator is discussed in detail.
{"title":"Fault Classification and Location for Distribution Generation Using Artificial Neural Networks","authors":"Foo Kheng Hong, Wong Jee Keen Raymond, Oon Kheng Heong, Tze Mei Kuan","doi":"10.1109/PECon48942.2020.9314535","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314535","url":null,"abstract":"With the proliferation of distributed generation (DG), the distributed network had become more complex. Such complexity will lead to difficulty for fault location in the distributed network. It may degrade the precision of existing fault location methods. Therefore, this paper will investigate the impact of distributed generation toward machine learning (ML) based fault location. Three categories of fault location had been tested which is fault type prediction, fault section prediction, and fault distance prediction with and without DG presence. The accuracy of machine learning based fault location is verified in IEEE 16 bus network and the impact due to the presence of DG, represented using photovoltaic (PV) generator is discussed in detail.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"18 1","pages":"315-320"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78327093","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314525
Ibraheem Mohammed Khalil AL- Jafeary, N. Tan
The sinusoidal pulse-width modulation (SPWM) technique is typically used for three-phase voltage source inverter (VSI) in low-voltage motor drives due to its simplicity and reliability. However, these VSI face increasing challenge to minimize electromagnetic interference (EMI) and increase power quality. This paper proposes a new SPWM switching based on a Bat-like reference signal that has the advantages of minimizing the output-voltage total harmonics distortion (THDv), lowering the switch rate of change in voltage (dv/dt), reducing the number of switching transitions, and increasing the peak and r.m.s. ac output voltage of the three-phase VSI. The proposed switching technique is verified using Matlab/Simulik on a 2-kW, 300-V three-phase VSI connected to an RL load. This technique shows improvement in reducing the output-voltage THDv by 36% and lowering the number of switching transition by 60% as compared to SPWM switching that is based on singlefrequency signal. Moreover, the dv/dt is low and the peak output voltage is increase by approximately 17%.
{"title":"Design of a Novel SPWM Based on Bat-Like Reference Signal Technique for EV Applications","authors":"Ibraheem Mohammed Khalil AL- Jafeary, N. Tan","doi":"10.1109/PECon48942.2020.9314525","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314525","url":null,"abstract":"The sinusoidal pulse-width modulation (SPWM) technique is typically used for three-phase voltage source inverter (VSI) in low-voltage motor drives due to its simplicity and reliability. However, these VSI face increasing challenge to minimize electromagnetic interference (EMI) and increase power quality. This paper proposes a new SPWM switching based on a Bat-like reference signal that has the advantages of minimizing the output-voltage total harmonics distortion (THDv), lowering the switch rate of change in voltage (dv/dt), reducing the number of switching transitions, and increasing the peak and r.m.s. ac output voltage of the three-phase VSI. The proposed switching technique is verified using Matlab/Simulik on a 2-kW, 300-V three-phase VSI connected to an RL load. This technique shows improvement in reducing the output-voltage THDv by 36% and lowering the number of switching transition by 60% as compared to SPWM switching that is based on singlefrequency signal. Moreover, the dv/dt is low and the peak output voltage is increase by approximately 17%.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"38 1","pages":"71-76"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79394610","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 : 2020-12-07DOI: 10.1109/PECon48942.2020.9314500
Khlid Ben Hamad, Mohamed Salem, D. Luta
This research deals with the design of an LCL filter for a grid tied megawatt fuel cell stack. In the adopted configuration, the LCL filter links a three-level neutral clamped point inverter with the grid. A typical inverter is a source of harmonics as in general its output is not a pure sinewave. Standards such each IEEE 519 and IEC 61000-3-6 define the allowable harmonics distortion for both the current and the voltage in a power system based on the current level and the voltage level respectively. This paper aims to design an LCL filter to reduce harmonics produced by a three-level inverter serving as interface between a fuel cell stack and a grid and meet the abovementioned standards. The input of the grid tied inverter is connected to a 1.4 MW solid oxide fuel cell stack at 1400 V. The inverter is modelled and controlled to deliver 1.2 MW at 600 V between phases. To evaluate the performance of the designed filter, the system including the 1.4 MW fuel cell stack, the inverter, the LCL filter, a grid and a load is simulated using Matlab/Simulink environment. The results show that the designed filter reduces the total harmonics distortion to 0.46 % and 24.87 % for the voltage and the current, respectively.
{"title":"Harmonic mitigation for a megawatt grid-tied fuel cell system","authors":"Khlid Ben Hamad, Mohamed Salem, D. Luta","doi":"10.1109/PECon48942.2020.9314500","DOIUrl":"https://doi.org/10.1109/PECon48942.2020.9314500","url":null,"abstract":"This research deals with the design of an LCL filter for a grid tied megawatt fuel cell stack. In the adopted configuration, the LCL filter links a three-level neutral clamped point inverter with the grid. A typical inverter is a source of harmonics as in general its output is not a pure sinewave. Standards such each IEEE 519 and IEC 61000-3-6 define the allowable harmonics distortion for both the current and the voltage in a power system based on the current level and the voltage level respectively. This paper aims to design an LCL filter to reduce harmonics produced by a three-level inverter serving as interface between a fuel cell stack and a grid and meet the abovementioned standards. The input of the grid tied inverter is connected to a 1.4 MW solid oxide fuel cell stack at 1400 V. The inverter is modelled and controlled to deliver 1.2 MW at 600 V between phases. To evaluate the performance of the designed filter, the system including the 1.4 MW fuel cell stack, the inverter, the LCL filter, a grid and a load is simulated using Matlab/Simulink environment. The results show that the designed filter reduces the total harmonics distortion to 0.46 % and 24.87 % for the voltage and the current, respectively.","PeriodicalId":6768,"journal":{"name":"2020 IEEE International Conference on Power and Energy (PECon)","volume":"37 1","pages":"209-213"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84762838","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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