Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146050
: A microgrid is an appropriate concept for urban areas with high penetration of renewable power generation, which improves the reliability and efficiency of the distribution network at the consumer premises to meet various loads such as domestic, industrial, and agricultural types. Microgrids comprising inverter-based and synchronous generator-based distribution generators can lead to the instability of the system during the islanded mode of operation. This paper presents a study on designing stable microgrids to facilitate higher penetration of solar power generation into a distribution network. A generalized small signal model is derived for a microgrid with static loads, dynamic loads, energy storages, solar photovoltaic (PV) systems, and diesel generators, incorporating the features of dynamic systems. The model is validated by comparing the transient curves given by the model and a transient simulator subjected to step changes. The result shows that full dynamic models of complex systems of microgrids can be built accurately, and the proposed microgrid is stable for all the considered loading situations and solar PV penetration levels according to the small signal stability analysis.
{"title":"Robust microgrids for distribution systems with high solar photovoltaic penetration","authors":"","doi":"10.24425/aee.2023.146050","DOIUrl":"https://doi.org/10.24425/aee.2023.146050","url":null,"abstract":": A microgrid is an appropriate concept for urban areas with high penetration of renewable power generation, which improves the reliability and efficiency of the distribution network at the consumer premises to meet various loads such as domestic, industrial, and agricultural types. Microgrids comprising inverter-based and synchronous generator-based distribution generators can lead to the instability of the system during the islanded mode of operation. This paper presents a study on designing stable microgrids to facilitate higher penetration of solar power generation into a distribution network. A generalized small signal model is derived for a microgrid with static loads, dynamic loads, energy storages, solar photovoltaic (PV) systems, and diesel generators, incorporating the features of dynamic systems. The model is validated by comparing the transient curves given by the model and a transient simulator subjected to step changes. The result shows that full dynamic models of complex systems of microgrids can be built accurately, and the proposed microgrid is stable for all the considered loading situations and solar PV penetration levels according to the small signal stability analysis.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146040
: At present, the back-propagation (BP) network algorithm widely used in the short-term output prediction of photovoltaic power stations has the disadvantage of ignoring meteorological factors and weather conditions in the input. The existing traditional BP prediction model lacks a variety of numerical optimization algorithms, such that the prediction error is large. The back-propagation (BP) neural network is easy to fall into local optimization thus reducing the prediction accuracy in photovoltaic power prediction. In order to solve this problem, an improved grey wolf optimization (GWO) algorithm is proposed to optimize the photovoltaic power prediction model of the BP neural network. So, an improved grey wolf optimization algorithm optimized BP neural network for a photovoltaic (PV) power prediction model is proposed. Dynamic weight strategy, tent mapping and particle swarm optimization (PSO) are introduced in the standard grey wolf optimization (GWO) to construct the PSO–GWO model. The relative error of the PSO–GWO–BP model predicted data is less than that of the BP model predicted data. The average relative error of PSO–GWO–BP and GWO–BP models is smaller, the average relative error of PSO–GWO–BP model is the smallest, and the prediction stability of the PSO–GWO–BP model is the best. The model stability and prediction accuracy of PSO–GWO–BP are better than those of GWO–BP and BP
{"title":"Photovoltaic power prediction based on improved grey wolf algorithm optimized back propagation","authors":"","doi":"10.24425/aee.2023.146040","DOIUrl":"https://doi.org/10.24425/aee.2023.146040","url":null,"abstract":": At present, the back-propagation (BP) network algorithm widely used in the short-term output prediction of photovoltaic power stations has the disadvantage of ignoring meteorological factors and weather conditions in the input. The existing traditional BP prediction model lacks a variety of numerical optimization algorithms, such that the prediction error is large. The back-propagation (BP) neural network is easy to fall into local optimization thus reducing the prediction accuracy in photovoltaic power prediction. In order to solve this problem, an improved grey wolf optimization (GWO) algorithm is proposed to optimize the photovoltaic power prediction model of the BP neural network. So, an improved grey wolf optimization algorithm optimized BP neural network for a photovoltaic (PV) power prediction model is proposed. Dynamic weight strategy, tent mapping and particle swarm optimization (PSO) are introduced in the standard grey wolf optimization (GWO) to construct the PSO–GWO model. The relative error of the PSO–GWO–BP model predicted data is less than that of the BP model predicted data. The average relative error of PSO–GWO–BP and GWO–BP models is smaller, the average relative error of PSO–GWO–BP model is the smallest, and the prediction stability of the PSO–GWO–BP model is the best. The model stability and prediction accuracy of PSO–GWO–BP are better than those of GWO–BP and BP","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146042
{"title":"Modelling of Li-Ion battery state-of-health with Gaussian processes","authors":"","doi":"10.24425/aee.2023.146042","DOIUrl":"https://doi.org/10.24425/aee.2023.146042","url":null,"abstract":"","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146045
: The effective design of energy-saving electric motors with efficiency class IE4 and higher requires the use of material characteristics that take into account the core shaping process. Therefore, it becomes necessary to use analytical or numerical models that take into account the change of local properties of Fe-Si material. The aim of the work is to indicate a useful analytical model for estimating the local magnetic permeability of the material, as well as to understand the reasons for these changes. For this purpose, low-loss ferromagnetic materials cut with a guillotine and a laser were tested. Rectangular samples, cut at an angle of 0 degrees in relation to the rolling direction, were subjected to macroscopic and microscopic examinations. Finally, the main reasons for changes in material characteristics for both cutting technologies were indicated. Therefore, the proposed model takes into account not only the cutting technology used, but also the current width of the tested strip, for which the material characteristics are to be determined. The parameters of the analytical model are determined on the basis of a limited number of measurements carried out on samples of a simple geometric shape.
{"title":"Investigation of local properties of the Fe-Si alloy subjected to mechanical and laser cutting","authors":"","doi":"10.24425/aee.2023.146045","DOIUrl":"https://doi.org/10.24425/aee.2023.146045","url":null,"abstract":": The effective design of energy-saving electric motors with efficiency class IE4 and higher requires the use of material characteristics that take into account the core shaping process. Therefore, it becomes necessary to use analytical or numerical models that take into account the change of local properties of Fe-Si material. The aim of the work is to indicate a useful analytical model for estimating the local magnetic permeability of the material, as well as to understand the reasons for these changes. For this purpose, low-loss ferromagnetic materials cut with a guillotine and a laser were tested. Rectangular samples, cut at an angle of 0 degrees in relation to the rolling direction, were subjected to macroscopic and microscopic examinations. Finally, the main reasons for changes in material characteristics for both cutting technologies were indicated. Therefore, the proposed model takes into account not only the cutting technology used, but also the current width of the tested strip, for which the material characteristics are to be determined. The parameters of the analytical model are determined on the basis of a limited number of measurements carried out on samples of a simple geometric shape.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146041
: Different buried permanent magnet arrangements in rotors are compared based on electrical machines found in literature regarding high-speed capability. An analytical approachispresentedtoanalyticallycalculatemechanicalstressesinthebilateralandcentral bridge of V arrangements in order to determine the achievable circumferential velocity of a rotor geometry. The mechanical model is coupled to an analytical model which can determine the flux density in the main air gap under consideration of flux leakage within the rotor. The multi-domain model enables the analytical design of high-speed rotors with buried permanent magnets in V-arrangement.
{"title":"Multi-domain analytical rotor model with buried permanent magnets in V-arrangement for high-speed applications","authors":"","doi":"10.24425/aee.2023.146041","DOIUrl":"https://doi.org/10.24425/aee.2023.146041","url":null,"abstract":": Different buried permanent magnet arrangements in rotors are compared based on electrical machines found in literature regarding high-speed capability. An analytical approachispresentedtoanalyticallycalculatemechanicalstressesinthebilateralandcentral bridge of V arrangements in order to determine the achievable circumferential velocity of a rotor geometry. The mechanical model is coupled to an analytical model which can determine the flux density in the main air gap under consideration of flux leakage within the rotor. The multi-domain model enables the analytical design of high-speed rotors with buried permanent magnets in V-arrangement.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146051
: The grid integration of large-scale wind power will alter the dynamic characteristics of the original system and the power distribution among synchronous machines. Meanwhile, the interaction between wind turbines and synchronous machines will affect the damping oscillation characteristics of the system. The additional damping control of traditional synchronous generators provides an important means for wind turbines to enhance the damping characteristics of the system. To improve the low frequency oscillation characteristics of wind power grid-connected power systems, this paper adds a parallel virtual impedance link to the traditional damping controller and designs a DFIG-PSS-VI controller. In the designed controller, the turbine active power difference is chosen as the input signal based on residual analysis, and the output signal is fed back to the reactive power control loop to obtain the rotor voltage quadrature component. With DigSILENT/PowerFactory, the influence of the controller parameters is analyzed. In addition, based on different tie-line transmission powers, the impact of the controller on the low-frequency oscillation characteristics of the power system is examined through utilizing the characteristic root and time domain simulation analysis.
{"title":"Research on improving low-frequency oscillation characteristics of wind power grid-connected power system with doubly-fed wind generator based on virtual impedance power system stabilizer","authors":"","doi":"10.24425/aee.2023.146051","DOIUrl":"https://doi.org/10.24425/aee.2023.146051","url":null,"abstract":": The grid integration of large-scale wind power will alter the dynamic characteristics of the original system and the power distribution among synchronous machines. Meanwhile, the interaction between wind turbines and synchronous machines will affect the damping oscillation characteristics of the system. The additional damping control of traditional synchronous generators provides an important means for wind turbines to enhance the damping characteristics of the system. To improve the low frequency oscillation characteristics of wind power grid-connected power systems, this paper adds a parallel virtual impedance link to the traditional damping controller and designs a DFIG-PSS-VI controller. In the designed controller, the turbine active power difference is chosen as the input signal based on residual analysis, and the output signal is fed back to the reactive power control loop to obtain the rotor voltage quadrature component. With DigSILENT/PowerFactory, the influence of the controller parameters is analyzed. In addition, based on different tie-line transmission powers, the impact of the controller on the low-frequency oscillation characteristics of the power system is examined through utilizing the characteristic root and time domain simulation analysis.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2021.137579
: Economic dispatch (ED) is an essential part of any power system network. ED is howtoscheduletherealpoweroutputsfromtheavailablegeneratorstogettheminimumcost while satisfying all constraints of the network. Moreover, it may be explained as allocating generation among the committed units with the most effective minimum way in accordance with all constraints of the system. There are many traditional methods for solving ED, e.g., Newton-Raphson method Lambda-Iterative technique, Gaussian-Seidel method, etc. All these traditional methods need the generators’ incremental fuel cost curves to be increasing linearly. But practically the input-output characteristics of a generator are highly non-linear. This causes a challenging non-convex optimization problem. Recent techniques like genetic algorithms, artificial intelligence, dynamic programming and particle swarm optimization solve nonconvex optimization problems in a powerful way and obtain a rapid and near global optimum solution. In addition, renewable energy resources as wind and solar are a promising option due to the environmental concerns as the fossil fuels reserves are being consumed and fuel price increases rapidly and emissions are getting higher. Therefore, the world tends to replace the old power stations into renewable ones or hybrid stations. In this paper, it is attempted to enhance the operation of electrical power system networks via economic dispatch. An ED problem is solved using various techniques, e.g., Particle Swarm Optimization (PSO) technique and Sine-Cosine Algorithm (SCA). Afterwards, the results are compared. Moreover, case studies are executed using a photovoltaic-based distributed generator with constant penetration level on the IEEE 14 bus system and results are observed. All the analyses are performed on MATLAB software.
{"title":"Economic dispatch in power system networks including renewable energy resources using various optimization techniques","authors":"","doi":"10.24425/aee.2021.137579","DOIUrl":"https://doi.org/10.24425/aee.2021.137579","url":null,"abstract":": Economic dispatch (ED) is an essential part of any power system network. ED is howtoscheduletherealpoweroutputsfromtheavailablegeneratorstogettheminimumcost while satisfying all constraints of the network. Moreover, it may be explained as allocating generation among the committed units with the most effective minimum way in accordance with all constraints of the system. There are many traditional methods for solving ED, e.g., Newton-Raphson method Lambda-Iterative technique, Gaussian-Seidel method, etc. All these traditional methods need the generators’ incremental fuel cost curves to be increasing linearly. But practically the input-output characteristics of a generator are highly non-linear. This causes a challenging non-convex optimization problem. Recent techniques like genetic algorithms, artificial intelligence, dynamic programming and particle swarm optimization solve nonconvex optimization problems in a powerful way and obtain a rapid and near global optimum solution. In addition, renewable energy resources as wind and solar are a promising option due to the environmental concerns as the fossil fuels reserves are being consumed and fuel price increases rapidly and emissions are getting higher. Therefore, the world tends to replace the old power stations into renewable ones or hybrid stations. In this paper, it is attempted to enhance the operation of electrical power system networks via economic dispatch. An ED problem is solved using various techniques, e.g., Particle Swarm Optimization (PSO) technique and Sine-Cosine Algorithm (SCA). Afterwards, the results are compared. Moreover, case studies are executed using a photovoltaic-based distributed generator with constant penetration level on the IEEE 14 bus system and results are observed. All the analyses are performed on MATLAB software.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146049
: This paper studies the influence of different cooling technologies on the power density of a traction machine for heavy-duty distribution transport. A prototype induction machine is built with a housing cooling jacket, potted end-windings, entire winding cooling, andshaftcooling.Electromagneticfiniteelementandthermallumped-parametermodelsare parameterized and verified using test bench measurements. The influence of each thermal resistance along the heat paths is studied and discussed. The results are used for studying different cooling technologies. The results indicate an improvement of the continuous power density up to 108% using shaft cooling and up to 15.6% using entire winding cooling.
{"title":"Influence of winding and shaft cooling on the thermal characteristics of a traction machine for heavy-duty distribution transport","authors":"","doi":"10.24425/aee.2023.146049","DOIUrl":"https://doi.org/10.24425/aee.2023.146049","url":null,"abstract":": This paper studies the influence of different cooling technologies on the power density of a traction machine for heavy-duty distribution transport. A prototype induction machine is built with a housing cooling jacket, potted end-windings, entire winding cooling, andshaftcooling.Electromagneticfiniteelementandthermallumped-parametermodelsare parameterized and verified using test bench measurements. The influence of each thermal resistance along the heat paths is studied and discussed. The results are used for studying different cooling technologies. The results indicate an improvement of the continuous power density up to 108% using shaft cooling and up to 15.6% using entire winding cooling.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.24425/aee.2023.146043
: This paper presents a novel fault detection algorithm for a three-phase interleaved DC–DC boost converter integrated in a photovoltaic system. Interleaved DC–DC converters have been used widely due to their advantages in terms of efficiency, ripple reductions, modularity and small filter components. The fault detection algorithm depends on the input current waveform as a fault indicator and does not require any additional sensors in the system. To guarantee service continuity, a fault tolerant topology is achieved by connecting a redundant switch to the interleaved converter. The proposed fault detection algorithm is validated under different scenarios by the obtained results.
{"title":"Study of an open-switch fault detection algorithm for a three-phase interleaved DC–DC boost converter in a photovoltaic system","authors":"","doi":"10.24425/aee.2023.146043","DOIUrl":"https://doi.org/10.24425/aee.2023.146043","url":null,"abstract":": This paper presents a novel fault detection algorithm for a three-phase interleaved DC–DC boost converter integrated in a photovoltaic system. Interleaved DC–DC converters have been used widely due to their advantages in terms of efficiency, ripple reductions, modularity and small filter components. The fault detection algorithm depends on the input current waveform as a fault indicator and does not require any additional sensors in the system. To guarantee service continuity, a fault tolerant topology is achieved by connecting a redundant switch to the interleaved converter. The proposed fault detection algorithm is validated under different scenarios by the obtained results.","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.24425/aee.2023.147415
{"title":"147415","authors":"","doi":"10.24425/aee.2023.147415","DOIUrl":"https://doi.org/10.24425/aee.2023.147415","url":null,"abstract":"","PeriodicalId":45464,"journal":{"name":"Archives of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81406151","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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