Pub Date : 2025-03-27DOI: 10.1109/OAJPE.2025.3573961
Jian Zhang;Yigang He
High penetration of electrical vehicles (EVs) and renewable distributed generators (DGs) into active distribution networks (ADNs) lead to frequent, rapid and fierce voltages magnitudes violations. A novel two-timescale coordination scheme for different types of adjustable devices in ADNs is put forward in this article by organically integrating data-driven deep reinforce-ment learning (DRL) into physical convex model. A Markov Decision Process (MDP) is formulated on slow timescale, in which ratios/statuses of on load transformer changers (OLTCs) and switchable capacitors reactors (SCRs) and ESSs charging/ discharging power are set hourly to optimize network losses while regulating voltages magnitudes. An improved DRL with relaxation-prediction-correction strategies is proposed for eradicating discrete action components dimension curses. Whereas, on fast timescale (e.g., several seconds or minutes), the optimal reactive power of DGs inverters and static VAR compensators (SVCs) in balanced and unbalanced ADNs are set with physical convex optimization to minimize network losses while respecting physical constraints. Five simulations cases with IEEE 33-node balanced and 123-node unbalanced feeders are carried out to verify capabilities of put forward method.
{"title":"Two-Timescale Coordination of Discretely and Continuously Adjustable Devices in ADNs With DRL and Physical Convex Optimization","authors":"Jian Zhang;Yigang He","doi":"10.1109/OAJPE.2025.3573961","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3573961","url":null,"abstract":"High penetration of electrical vehicles (EVs) and renewable distributed generators (DGs) into active distribution networks (ADNs) lead to frequent, rapid and fierce voltages magnitudes violations. A novel two-timescale coordination scheme for different types of adjustable devices in ADNs is put forward in this article by organically integrating data-driven deep reinforce-ment learning (DRL) into physical convex model. A Markov Decision Process (MDP) is formulated on slow timescale, in which ratios/statuses of on load transformer changers (OLTCs) and switchable capacitors reactors (SCRs) and ESSs charging/ discharging power are set hourly to optimize network losses while regulating voltages magnitudes. An improved DRL with relaxation-prediction-correction strategies is proposed for eradicating discrete action components dimension curses. Whereas, on fast timescale (e.g., several seconds or minutes), the optimal reactive power of DGs inverters and static VAR compensators (SVCs) in balanced and unbalanced ADNs are set with physical convex optimization to minimize network losses while respecting physical constraints. Five simulations cases with IEEE 33-node balanced and 123-node unbalanced feeders are carried out to verify capabilities of put forward method.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"391-403"},"PeriodicalIF":3.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11016130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1109/OAJPE.2025.3573958
Ignacio Aravena;Chih-Che Sun;Ranyu Shi;Subir Majumder;Weihang Yan;Jhi-Young Joo;Le Xie;Jiyu Wang
A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.
{"title":"Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications","authors":"Ignacio Aravena;Chih-Che Sun;Ranyu Shi;Subir Majumder;Weihang Yan;Jhi-Young Joo;Le Xie;Jiyu Wang","doi":"10.1109/OAJPE.2025.3573958","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3573958","url":null,"abstract":"A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"353-365"},"PeriodicalIF":3.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11015807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to the energy transition, which involves phasing out base load power plants such as coal, there is a need to establish storage systems within the energy system to compensate for fluctuations of renewable energies. Batteries are suitable for day-night cycles and particularly for short-cycle applications. To address the problem of dark-doldrums, when neither wind nor solar energy is available, gas and, in the more distant future, hydrogen power plants are to be used. By combining batteries and hydrogen power plants in a hybrid energy storage system, further advantages and application possibilities arise regarding grid stability and system design. This work illustrates interrelationships between the subsystems, optimizes proportions, and demonstrates logical system sizes, technologies, and their costs. A central part of the work are the self-derived methods for system design and the justification of these. Storage pressure, running times, availability time, annual cycles and design of the subsystems are described. Systems of this scale are difficult to imagine. A program developed as part of this work to implement the methods, visualizes the system, displays the system parameters, and shows the best-case and worst-case capital expenditures. An optimized system design is presented. Different combinations in the system design show the effects on capital expenditures. Starting from 2 to 4 hours of availability time, the hybrid system becomes cheaper than a pure battery system in terms of capital expenditures.
{"title":"Design of Large-Scale Hybrid, Hydrogen and Battery, and Energy Storage Systems for Grid Applications","authors":"Marvin Dorn;Jonas Lotze;Uwe Këhnapfel;André Weber;Veit Hagenmeyer","doi":"10.1109/OAJPE.2025.3572590","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3572590","url":null,"abstract":"Due to the energy transition, which involves phasing out base load power plants such as coal, there is a need to establish storage systems within the energy system to compensate for fluctuations of renewable energies. Batteries are suitable for day-night cycles and particularly for short-cycle applications. To address the problem of dark-doldrums, when neither wind nor solar energy is available, gas and, in the more distant future, hydrogen power plants are to be used. By combining batteries and hydrogen power plants in a hybrid energy storage system, further advantages and application possibilities arise regarding grid stability and system design. This work illustrates interrelationships between the subsystems, optimizes proportions, and demonstrates logical system sizes, technologies, and their costs. A central part of the work are the self-derived methods for system design and the justification of these. Storage pressure, running times, availability time, annual cycles and design of the subsystems are described. Systems of this scale are difficult to imagine. A program developed as part of this work to implement the methods, visualizes the system, displays the system parameters, and shows the best-case and worst-case capital expenditures. An optimized system design is presented. Different combinations in the system design show the effects on capital expenditures. Starting from 2 to 4 hours of availability time, the hybrid system becomes cheaper than a pure battery system in terms of capital expenditures.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"341-352"},"PeriodicalIF":3.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-22DOI: 10.1109/OAJPE.2025.3572718
Tharmini Thavaratnam;Bala Venkatesh
Deep electrification by 2050 is expected to increase distribution systems by three to five times and include innumerable distributed energy resources (DERs). Robust methods for operations will be required. Reconfigurations, well researched for 50+ years, are created given the size and importance of present distribution systems. This paper proposes a network configuration method which is significantly dense, heavily loaded, societally important, and has innumerable loads and DERs. This method reduces sections of feeders with DERs to equivalent reduced Pi-Model representations. It then uses a regression model to correlate loading scenarios of the distribution to reduced Pi-Model parameters feeder sections. A regression model yields reduced Pi-Models of feeder sections, and they are used to construct a complete distribution system representation, with this reduced model used for reconfiguration. The proposed method was tested on modified 33-, 69- and 123-Bus data networks and reduced the number of buses to around 50%. Computing time was reduced by 26.30%, 58.54% and 67.33%, respectively while providing accuracy of 97.35%, 97.30%, and 99.05%, respectively. The computation time was lowered by 46.45% when the methodology was expanded to the North Dakota 880-Bus network. As the method scales for larger distribution systems, it should increasingly perform better.
{"title":"Data Driven Reduced Pi-Model of Feeders for Distribution Network Representation With DERs for Fast Reconfiguration","authors":"Tharmini Thavaratnam;Bala Venkatesh","doi":"10.1109/OAJPE.2025.3572718","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3572718","url":null,"abstract":"Deep electrification by 2050 is expected to increase distribution systems by three to five times and include innumerable distributed energy resources (DERs). Robust methods for operations will be required. Reconfigurations, well researched for 50+ years, are created given the size and importance of present distribution systems. This paper proposes a network configuration method which is significantly dense, heavily loaded, societally important, and has innumerable loads and DERs. This method reduces sections of feeders with DERs to equivalent reduced Pi-Model representations. It then uses a regression model to correlate loading scenarios of the distribution to reduced Pi-Model parameters feeder sections. A regression model yields reduced Pi-Models of feeder sections, and they are used to construct a complete distribution system representation, with this reduced model used for reconfiguration. The proposed method was tested on modified 33-, 69- and 123-Bus data networks and reduced the number of buses to around 50%. Computing time was reduced by 26.30%, 58.54% and 67.33%, respectively while providing accuracy of 97.35%, 97.30%, and 99.05%, respectively. The computation time was lowered by 46.45% when the methodology was expanded to the North Dakota 880-Bus network. As the method scales for larger distribution systems, it should increasingly perform better.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"330-340"},"PeriodicalIF":3.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a comprehensive, robust and efficient solver platform that incorporates phasor domain short circuit models of grid-forming (GFM) and grid-following (GFL) IBRs for fundamental frequency fault calculations considering various IBR controls. The proposed approach is verified through cross examination against detailed electromagnetic transient (EMT) modeling and simulations using a modified IEEE 39 bus system with multiple IBRs. The solver platform enables protection engineers to perform rapid and accurate short-circuit computations and protective relay studies in power systems with high penetration of IBRs, facilitating the assessment of fault-ride-through strategies and compliance with grid codes. This paper integrates a recently proposed derivative solution into modified augmented nodal analysis (MANA) formulation for improved numerical convergence under IBRs while treating both GFL and GFM IBR models to provide new insights and results.
{"title":"Efficient, Robust, and Comprehensive Fault Calculation of IBR-Rich Systems Considering Diverse Controls","authors":"Xinquan Chen;Aboutaleb Haddadi;Zhe Yang;Evangelos Farantatos;Ilhan Kocar","doi":"10.1109/OAJPE.2025.3572769","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3572769","url":null,"abstract":"This paper proposes a comprehensive, robust and efficient solver platform that incorporates phasor domain short circuit models of grid-forming (GFM) and grid-following (GFL) IBRs for fundamental frequency fault calculations considering various IBR controls. The proposed approach is verified through cross examination against detailed electromagnetic transient (EMT) modeling and simulations using a modified IEEE 39 bus system with multiple IBRs. The solver platform enables protection engineers to perform rapid and accurate short-circuit computations and protective relay studies in power systems with high penetration of IBRs, facilitating the assessment of fault-ride-through strategies and compliance with grid codes. This paper integrates a recently proposed derivative solution into modified augmented nodal analysis (MANA) formulation for improved numerical convergence under IBRs while treating both GFL and GFM IBR models to provide new insights and results.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"378-390"},"PeriodicalIF":3.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144206022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-21DOI: 10.1109/OAJPE.2025.3571108
Sander Lid Skogen;José Luis Rueda Torres
As the integration of renewable energy accelerates, ensuring power system stability becomes increasingly critical. This research utilized a Root Mean Square (RMS) synthetic model of the future 380 kV Dutch power system towards 2050 to analyze its oscillatory stability under high renewable penetration and the impact of grid-forming converters under various parametrizations. The presented case study shows that grid-forming (GFM) converters significantly improve frequency stability and damping performance across different perturbations, particularly at higher GFM penetration levels, improving frequency and damping parameters. However, various oscillatory modes present potential stability risks at high penetration levels. The case study also shows minimal differences in controller selection in large-scale models, except under certain conditions. Additionally, the analysis of controller parameters highlighted the critical importance of tuning active power parameters to ensure system stability. The investigation provides essential insights for future power systems, where large-scale integration of renewable energy will necessitate the implementation of converters able to provide ancillary services. The findings emphasize the importance of optimizing GFM converter settings and penetration levels to maintain system resilience, offering valuable guidance for future system planning and regulatory frameworks.
{"title":"Assessing Oscillatory Stability With Dominant Grid-Forming Power Systems for Active Power Imbalances","authors":"Sander Lid Skogen;José Luis Rueda Torres","doi":"10.1109/OAJPE.2025.3571108","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3571108","url":null,"abstract":"As the integration of renewable energy accelerates, ensuring power system stability becomes increasingly critical. This research utilized a Root Mean Square (RMS) synthetic model of the future 380 kV Dutch power system towards 2050 to analyze its oscillatory stability under high renewable penetration and the impact of grid-forming converters under various parametrizations. The presented case study shows that grid-forming (GFM) converters significantly improve frequency stability and damping performance across different perturbations, particularly at higher GFM penetration levels, improving frequency and damping parameters. However, various oscillatory modes present potential stability risks at high penetration levels. The case study also shows minimal differences in controller selection in large-scale models, except under certain conditions. Additionally, the analysis of controller parameters highlighted the critical importance of tuning active power parameters to ensure system stability. The investigation provides essential insights for future power systems, where large-scale integration of renewable energy will necessitate the implementation of converters able to provide ancillary services. The findings emphasize the importance of optimizing GFM converter settings and penetration levels to maintain system resilience, offering valuable guidance for future system planning and regulatory frameworks.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"318-329"},"PeriodicalIF":3.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11008671","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-20DOI: 10.1109/OAJPE.2025.3553408
Elmer O. Hancco Catata;Marcelo Vinícius De Paula;Ernesto Ruppert Filho;Tárcio André Dos Santos Barros
An efficient switching method is proposed for Direct Instantaneous Torque Control (DITC) in Switched Reluctance Generators (SRG) operating at low speeds, aiming to enhance system efficiency and reduce torque ripple. In the traditional DITC strategy, the magnetization state in the outgoing phase is enabled at low operating speeds, leading to decreased efficiency and unnecessary torque ripple. The proposed DITC strategy improves efficiency at low speeds while maintaining low torque ripple levels. It prioritizes the freewheeling and demagnetization states during the outgoing period. When the back electromotive force (back EMF) is small, the magnetization state is disabled, using the freewheeling state to smoothly increase torque and the demagnetization state to decrease torque. The magnetization state is reintroduced as the back EMF increases. To implement the modified DITC, an artificial neural network is used to estimate electromagnetic torque. Experimental tests were conducted for both fixed and variable SRG speeds. The proposed method is compared with other methods in the literature. Experimental tests carried out at fixed and variable SRG speeds show that the proposed method significantly enhances efficiency by up to 20% and reduces torque ripple by up to 21% compared to existing methods.
{"title":"Energy-Efficient Direct Instantaneous Torque Control of Switched Reluctance Generator at Low Speeds","authors":"Elmer O. Hancco Catata;Marcelo Vinícius De Paula;Ernesto Ruppert Filho;Tárcio André Dos Santos Barros","doi":"10.1109/OAJPE.2025.3553408","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3553408","url":null,"abstract":"An efficient switching method is proposed for Direct Instantaneous Torque Control (DITC) in Switched Reluctance Generators (SRG) operating at low speeds, aiming to enhance system efficiency and reduce torque ripple. In the traditional DITC strategy, the magnetization state in the outgoing phase is enabled at low operating speeds, leading to decreased efficiency and unnecessary torque ripple. The proposed DITC strategy improves efficiency at low speeds while maintaining low torque ripple levels. It prioritizes the freewheeling and demagnetization states during the outgoing period. When the back electromotive force (back EMF) is small, the magnetization state is disabled, using the freewheeling state to smoothly increase torque and the demagnetization state to decrease torque. The magnetization state is reintroduced as the back EMF increases. To implement the modified DITC, an artificial neural network is used to estimate electromagnetic torque. Experimental tests were conducted for both fixed and variable SRG speeds. The proposed method is compared with other methods in the literature. Experimental tests carried out at fixed and variable SRG speeds show that the proposed method significantly enhances efficiency by up to 20% and reduces torque ripple by up to 21% compared to existing methods.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"171-180"},"PeriodicalIF":3.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10935298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-16DOI: 10.1109/OAJPE.2025.3570834
Felipe B. B. Rolim;Fernanda C. L. Trindade;Vinicius C. Cunha
Smart meters are essential for distribution utilities as they provide valuable data that enable efficient management of distribution systems and informed decision-making processes. A critical application of this data is identifying abnormal system operations, such as non-technical losses and high impedance faults, which can affect power quality, safety, and utility revenue. However, there is currently no consensus on how to address these issues. This study proposes a composite index that uses smart meter data, and statistical concepts to simultaneously detect and locate anomalous system operations. This index is called the “Anomaly Intensity Index” and relies on tests that evaluate local and system-wide measurements, ranking customers according to the expected anomaly intensity. The proposed approach successfully identified abnormal demand as low as 0.2 kW per phase in test cases and estimated deviated energy with less than 1% error.
{"title":"Composite Index for Identifying Anomalies in Low Voltage Systems Using Smart Meter Measurement Data","authors":"Felipe B. B. Rolim;Fernanda C. L. Trindade;Vinicius C. Cunha","doi":"10.1109/OAJPE.2025.3570834","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3570834","url":null,"abstract":"Smart meters are essential for distribution utilities as they provide valuable data that enable efficient management of distribution systems and informed decision-making processes. A critical application of this data is identifying abnormal system operations, such as non-technical losses and high impedance faults, which can affect power quality, safety, and utility revenue. However, there is currently no consensus on how to address these issues. This study proposes a composite index that uses smart meter data, and statistical concepts to simultaneously detect and locate anomalous system operations. This index is called the “Anomaly Intensity Index” and relies on tests that evaluate local and system-wide measurements, ranking customers according to the expected anomaly intensity. The proposed approach successfully identified abnormal demand as low as 0.2 kW per phase in test cases and estimated deviated energy with less than 1% error.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"306-317"},"PeriodicalIF":3.3,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144170810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-12DOI: 10.1109/OAJPE.2025.3569302
Muneki Masuda;Hayato Satoh
Japan aims to achieve carbon neutrality by 2050, with a target of 100% sale of electric vehicles (EVs) by 2035. An increase in EV charging demand changes the characteristics of load demand and in turn, affects power system stability. Therefore, a load model that considers EV charger characteristics is required. We had developed and verified an EV charger model through a root mean square analysis following balanced faults. To an extent, this model represents the voltage and frequency responses caused by balanced faults. However, it is based on only one representative manufacturer, and the model’s versatility and practicality need improvement. This study experimentally investigated the responses of EV chargers manufactured by several manufacturers. Each EV charger’s response was characterized. The developed model was improved to represent the response of each EV charger. The model parameters for each charger type were identified by comparing and validating the measured and simulated responses following balanced faults. An excellent match between the measured and simulated responses demonstrated that the developed model and the identified parameters accurately simulated the response following balanced faults. This model and the identified parameters can enable a more accurate assessment of EV charger impact on power system stability.
{"title":"Enhanced Root Mean Square Model for Electric Vehicle Chargers: Addressing Balanced Faults With Multi-Manufacturer Variability","authors":"Muneki Masuda;Hayato Satoh","doi":"10.1109/OAJPE.2025.3569302","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3569302","url":null,"abstract":"Japan aims to achieve carbon neutrality by 2050, with a target of 100% sale of electric vehicles (EVs) by 2035. An increase in EV charging demand changes the characteristics of load demand and in turn, affects power system stability. Therefore, a load model that considers EV charger characteristics is required. We had developed and verified an EV charger model through a root mean square analysis following balanced faults. To an extent, this model represents the voltage and frequency responses caused by balanced faults. However, it is based on only one representative manufacturer, and the model’s versatility and practicality need improvement. This study experimentally investigated the responses of EV chargers manufactured by several manufacturers. Each EV charger’s response was characterized. The developed model was improved to represent the response of each EV charger. The model parameters for each charger type were identified by comparing and validating the measured and simulated responses following balanced faults. An excellent match between the measured and simulated responses demonstrated that the developed model and the identified parameters accurately simulated the response following balanced faults. This model and the identified parameters can enable a more accurate assessment of EV charger impact on power system stability.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"284-296"},"PeriodicalIF":3.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11002605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-08DOI: 10.1109/OAJPE.2025.3566957
Fahad S. Alshammari;Ayman El-Refaie;Saleh Alyahya;Sheroz Khan
Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization function is designed with local frequency and voltage constraints to maintain the frequency at its nominal value and ensure the voltage remains within a 5% tolerance range.. The proposed controller maintains power sharing among all units at the global consensus average value with constraints to within the limits. When the voltage limit is reached, the reactive power automatically deviates from the agreed global average in an optimal manner. The performance of the controller is shown using MATLAB/SIMULINK for different control parameters. The performance is compared to centralized-based topology. Finally, the controller is tested for grids with different line-parameters mismatches. The results show the reactive power sharing in an optimized manner.
{"title":"Optimization-Based Distributed Controller for Multi-Agents System in Microgrid Secondary Control","authors":"Fahad S. Alshammari;Ayman El-Refaie;Saleh Alyahya;Sheroz Khan","doi":"10.1109/OAJPE.2025.3566957","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3566957","url":null,"abstract":"Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization function is designed with local frequency and voltage constraints to maintain the frequency at its nominal value and ensure the voltage remains within a 5% tolerance range.. The proposed controller maintains power sharing among all units at the global consensus average value with constraints to within the limits. When the voltage limit is reached, the reactive power automatically deviates from the agreed global average in an optimal manner. The performance of the controller is shown using MATLAB/SIMULINK for different control parameters. The performance is compared to centralized-based topology. Finally, the controller is tested for grids with different line-parameters mismatches. The results show the reactive power sharing in an optimized manner.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"417-428"},"PeriodicalIF":3.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10993382","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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