The increasing penetration of behind-the-meter (BTM) distributed energy resources (DERs) in the electricity grid will reduce the utilities’ net demand and increase customers’ profits through reduced electricity bills and compensation for excess generation via mechanisms such as net-metering credits. To recover lost revenue, distribution utilities, as asset operators—and retailers, as energy procurement entities, are often compelled to raise electricity prices. This, in turn, further incentivizes DERs adoption, potentially leading to a feedback loop of rising rates and declining demand that threatens the long-term financial sustainability of traditional utility models. In this context, there is a gap for innovative retailer business models in the era of increasing DERs. This paper focuses on identifying the dynamics underlying retail market operations and business sustainability in the era of increasing DERs. Accordingly, this paper proposes a dynamic retail market model that captures the interdependencies of market components and processes through non-linear causal relationships and feedback loops. This enables retailers to investigate their long-term business performance in prosumer-penetrated networks. Additionally, this work develops an integrated operation and planning framework for the techno-economic analysis and decision modeling of retailers, utilities, and customers in the retail market paradigm. Using the developed framework, this work further proposes two alternative retailer business models that enhance retailers’ long-term business sustainability and customers’ economic viability. Analytical studies evaluate the business models and present recommendations to ensure the financial sustainablility. The results demonstrate that the proposed subscription-based models can successfully mitigate the adverse financial effects of widespread DERs adoption and ensure long-term system stability.
{"title":"A Dynamic Retail Market Model to Investigate Sustainability of Retail Contracts in DERs-Penetrated Markets","authors":"Sumedha Sharma;Haotian Yao;Mostafa Farrokhabadi;Hamidreza Zareipour;Petr Musilek","doi":"10.1109/OAJPE.2025.3603992","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3603992","url":null,"abstract":"The increasing penetration of behind-the-meter (BTM) distributed energy resources (DERs) in the electricity grid will reduce the utilities’ net demand and increase customers’ profits through reduced electricity bills and compensation for excess generation via mechanisms such as net-metering credits. To recover lost revenue, distribution utilities, as asset operators—and retailers, as energy procurement entities, are often compelled to raise electricity prices. This, in turn, further incentivizes DERs adoption, potentially leading to a feedback loop of rising rates and declining demand that threatens the long-term financial sustainability of traditional utility models. In this context, there is a gap for innovative retailer business models in the era of increasing DERs. This paper focuses on identifying the dynamics underlying retail market operations and business sustainability in the era of increasing DERs. Accordingly, this paper proposes a dynamic retail market model that captures the interdependencies of market components and processes through non-linear causal relationships and feedback loops. This enables retailers to investigate their long-term business performance in prosumer-penetrated networks. Additionally, this work develops an integrated operation and planning framework for the techno-economic analysis and decision modeling of retailers, utilities, and customers in the retail market paradigm. Using the developed framework, this work further proposes two alternative retailer business models that enhance retailers’ long-term business sustainability and customers’ economic viability. Analytical studies evaluate the business models and present recommendations to ensure the financial sustainablility. The results demonstrate that the proposed subscription-based models can successfully mitigate the adverse financial effects of widespread DERs adoption and ensure long-term system stability.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"600-613"},"PeriodicalIF":3.2,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11145173","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036756","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 : 2025-08-28DOI: 10.1109/OAJPE.2025.3603938
Charithri Yapa;Chamitha de Alwis;Uditha Wijewardhana;Madhusanka Liyanage;Janaka Ekanayake
A robust and secure reputation management system is required to ensure reliability, trust, and efficiency in energy transactions. This paper proposes a multi-parameter reputation scoring system, which enables combining factors that reflect direct individual performance, and the contribution towards maintaining a stable grid and delivering a high-quality power supply. Further, this study proposes integrating blockchain for the realization of the reputation management of Smart Grid 2.0. This ensures a secure and transparent mechanism, eliminating data poisoning and repudiation of transactions. Smart contracts facilitate the automatic execution of data aggregation, reputation calculation, and selective decision-making processes. The performance of a multi-factor reputation management scheme on Peer-to-Peer energy trading is evaluated through the conducted tests. The superiority has been showcased through benefits to the consumer and the prosumer. Moreover, a comparison against the state-of-the-art reputation scheme is included to further highlight the significance of this study.
{"title":"Empowering P2P Energy Networks: A Blockchain-Based Multi-Parameter Reputation Management System for Grid Enhancement","authors":"Charithri Yapa;Chamitha de Alwis;Uditha Wijewardhana;Madhusanka Liyanage;Janaka Ekanayake","doi":"10.1109/OAJPE.2025.3603938","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3603938","url":null,"abstract":"A robust and secure reputation management system is required to ensure reliability, trust, and efficiency in energy transactions. This paper proposes a multi-parameter reputation scoring system, which enables combining factors that reflect direct individual performance, and the contribution towards maintaining a stable grid and delivering a high-quality power supply. Further, this study proposes integrating blockchain for the realization of the reputation management of Smart Grid 2.0. This ensures a secure and transparent mechanism, eliminating data poisoning and repudiation of transactions. Smart contracts facilitate the automatic execution of data aggregation, reputation calculation, and selective decision-making processes. The performance of a multi-factor reputation management scheme on Peer-to-Peer energy trading is evaluated through the conducted tests. The superiority has been showcased through benefits to the consumer and the prosumer. Moreover, a comparison against the state-of-the-art reputation scheme is included to further highlight the significance of this study.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"614-624"},"PeriodicalIF":3.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11143161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145110245","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 : 2025-08-22DOI: 10.1109/OAJPE.2025.3602014
Abbas Hasani;Xiaodong Liang;Majid Sanaye-Pasand;Moein Abedini
In the earliest generation of loss of excitation (LOE) protection relays, the exciter’s output voltage ($V_{e}$ ) or output current ($I_{e}$ ) were employed for the LOE protection of synchronous generators (SGs) by employing under-voltage or under-current schemes. This paper explores using the excitation system’s output quantities ($V_{e}$ and $I_{e}$ ) to detect the LOE phenomenon in SGs. The phase domain (PD) model of SGs available in the real-time digital simulator (RTDS) is used in this paper rather than the well-known dq representation, because only the PD model can provide realistic modeling of the LOE phenomenon based on the IEEE Standard C37-102, and $V_{e}$ and $I_{e}$ measurements. A new combined scheme using $V_{e}$ and $I_{e}$ is proposed for the LOE protection as an LOE failure causes an interruption on $V_{e}$ or $I_{e}$ . Through simple paralleled under-voltage and under-current logics, such interruptions can be easily detected. The proposed method is compared with conventional impedance-based schemes through case studies, including the complete LOE (CLOE) and partial LOE (PLOE) failures, and the stable power swing (PS) phenomenon, showing superior performance by reliably detecting CLOE events and maintaining secure operations during PS events, although it may perform unreliably during PLOE events.
{"title":"Excitation System Output Quantities-Based Loss of Excitation Detection in Synchronous Generators","authors":"Abbas Hasani;Xiaodong Liang;Majid Sanaye-Pasand;Moein Abedini","doi":"10.1109/OAJPE.2025.3602014","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3602014","url":null,"abstract":"In the earliest generation of loss of excitation (LOE) protection relays, the exciter’s output voltage (<inline-formula> <tex-math>$V_{e}$ </tex-math></inline-formula>) or output current (<inline-formula> <tex-math>$I_{e}$ </tex-math></inline-formula>) were employed for the LOE protection of synchronous generators (SGs) by employing under-voltage or under-current schemes. This paper explores using the excitation system’s output quantities (<inline-formula> <tex-math>$V_{e}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$I_{e}$ </tex-math></inline-formula>) to detect the LOE phenomenon in SGs. The phase domain (PD) model of SGs available in the real-time digital simulator (RTDS) is used in this paper rather than the well-known dq representation, because only the PD model can provide realistic modeling of the LOE phenomenon based on the IEEE Standard C37-102, and <inline-formula> <tex-math>$V_{e}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$I_{e}$ </tex-math></inline-formula> measurements. A new combined scheme using <inline-formula> <tex-math>$V_{e}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$I_{e}$ </tex-math></inline-formula> is proposed for the LOE protection as an LOE failure causes an interruption on <inline-formula> <tex-math>$V_{e}$ </tex-math></inline-formula> or <inline-formula> <tex-math>$I_{e}$ </tex-math></inline-formula>. Through simple paralleled under-voltage and under-current logics, such interruptions can be easily detected. The proposed method is compared with conventional impedance-based schemes through case studies, including the complete LOE (CLOE) and partial LOE (PLOE) failures, and the stable power swing (PS) phenomenon, showing superior performance by reliably detecting CLOE events and maintaining secure operations during PS events, although it may perform unreliably during PLOE events.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"578-589"},"PeriodicalIF":3.2,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11134407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914163","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 : 2025-08-11DOI: 10.1109/OAJPE.2025.3597538
Thongchart Kerdphol
To address the challenge of inertia deficiency in multi-area power systems, this paper proposes a novel approach to inertia sharing by leveraging supplementary control integrated with thyristor-controlled series capacitors (TCSC). The proposed supplementary power modulation controller (SPMC) dynamically adjusts TCSC reactance based on frequency and tie-line power deviations to facilitate coordinated inertia transfer from well-equipped areas to inertia-deficient regions. Unlike conventional strategies that rely on deploying additional energy storage systems or distributed virtual inertia units, the proposed method utilizes existing transmission infrastructure, thereby reducing implementation complexity and cost. The efficacy of the proposed control strategy is assessed using a benchmark interconnected model configured to reflect practical multi-area dynamics and intertie constraints. Simulation results confirm that the SPMC-based TCSC control improves transient frequency stability, enhances damping, and increases the efficiency of inertia sharing, even under network congestion and delay conditions. These findings highlight the potential of the proposed strategy as a scalable and practical solution for enhancing dynamic performance in renewable-rich, interconnected power grids.
{"title":"Designing Supplementary Controller With Thyristor-Controlled Series Capacitor for Enhancing Inertia-Sharing Capability","authors":"Thongchart Kerdphol","doi":"10.1109/OAJPE.2025.3597538","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3597538","url":null,"abstract":"To address the challenge of inertia deficiency in multi-area power systems, this paper proposes a novel approach to inertia sharing by leveraging supplementary control integrated with thyristor-controlled series capacitors (TCSC). The proposed supplementary power modulation controller (SPMC) dynamically adjusts TCSC reactance based on frequency and tie-line power deviations to facilitate coordinated inertia transfer from well-equipped areas to inertia-deficient regions. Unlike conventional strategies that rely on deploying additional energy storage systems or distributed virtual inertia units, the proposed method utilizes existing transmission infrastructure, thereby reducing implementation complexity and cost. The efficacy of the proposed control strategy is assessed using a benchmark interconnected model configured to reflect practical multi-area dynamics and intertie constraints. Simulation results confirm that the SPMC-based TCSC control improves transient frequency stability, enhances damping, and increases the efficiency of inertia sharing, even under network congestion and delay conditions. These findings highlight the potential of the proposed strategy as a scalable and practical solution for enhancing dynamic performance in renewable-rich, interconnected power grids.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"564-577"},"PeriodicalIF":3.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11121887","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144853515","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 : 2025-08-11DOI: 10.1109/OAJPE.2025.3597533
James Rojas Waterhouse;Cristhian R. Morante Villarreal;Guilherme Beppu de Souza;Fernando Vilas Boas Ribeiro;Carlos Henrique Gasparetti;Kauan Pires Quevedo;Josiel Gonçalves Dos Santos;George Camargo Dos Santos;Marlos José Ribeiro Guimarães
This article presents a comprehensive design study of a low-speed wind turbine optimized for regions with weak wind resources, with a particular focus on Brazil’s extensive territories. The research challenges conventional turbine designs by incorporating innovative strategies to enhance aerodynamic performance, structural integrity, and cost efficiency. Consolidated computational tools were integrated with optimization algorithms, creating an innovative multidisciplinary optimization framework. Multiple configurations were assessed based on energy output, load mitigation, and economic viability, leading to the identification of promising designs that effectively balance performance targets with practical constraints. The study highlights how a structured multidisciplinary design optimization (MDO) approach, applied during the preliminary and conceptual design phases, enables the development of configurations well-adapted to low-wind-speed environments. These findings result into the output configuration achieving a rated wind speed of 6.45 m/s, and moreover they offer a scalable framework for future research and field validation in low-wind-speed applications. Therefore, the objective of developing a viable wind turbine prototype using custom multidisciplinary optimization models was successfully achieved.
{"title":"Development of a Low-Speed Wind Turbine for Brazilian Onshore Areas: A Preliminary and Conceptual Design","authors":"James Rojas Waterhouse;Cristhian R. Morante Villarreal;Guilherme Beppu de Souza;Fernando Vilas Boas Ribeiro;Carlos Henrique Gasparetti;Kauan Pires Quevedo;Josiel Gonçalves Dos Santos;George Camargo Dos Santos;Marlos José Ribeiro Guimarães","doi":"10.1109/OAJPE.2025.3597533","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3597533","url":null,"abstract":"This article presents a comprehensive design study of a low-speed wind turbine optimized for regions with weak wind resources, with a particular focus on Brazil’s extensive territories. The research challenges conventional turbine designs by incorporating innovative strategies to enhance aerodynamic performance, structural integrity, and cost efficiency. Consolidated computational tools were integrated with optimization algorithms, creating an innovative multidisciplinary optimization framework. Multiple configurations were assessed based on energy output, load mitigation, and economic viability, leading to the identification of promising designs that effectively balance performance targets with practical constraints. The study highlights how a structured multidisciplinary design optimization (MDO) approach, applied during the preliminary and conceptual design phases, enables the development of configurations well-adapted to low-wind-speed environments. These findings result into the output configuration achieving a rated wind speed of 6.45 m/s, and moreover they offer a scalable framework for future research and field validation in low-wind-speed applications. Therefore, the objective of developing a viable wind turbine prototype using custom multidisciplinary optimization models was successfully achieved.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"590-599"},"PeriodicalIF":3.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11122021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036816","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}
The increasing penetration of Distributed Energy Resources (DER) expands the cyberattack surface of power systems. This paper analyses, using PowerFactory, the impact and success of MaDIoT 3.0 attacks in the PST-16 model, a simplified model of the European system. MaDIoT 3.0 attacks are a novel type of attack that manage to compromise both high-wattage IoT demand devices and DER devices at the same time. The results indicate that the inclusion of distributed solar PV generation in the PST-16 system reduces the success ratio and impact of load-altering MaDIoT attacks when compared to the same system without DER, mainly due to an increment of the initial voltages. For MaDIoT 3.0 attacks, the demand had a more significant influence on the attack’s success than DER in the PST-16 system. Distributing the attacked demand across more buses or targeting the demand from other areas would decrease the success ratio of the attack. Therefore, the local scalability and replicability of vulnerable high-wattage demand devices in the analysed system become more critical than their distributed deployment in larger areas.
{"title":"MaDIoT 3.0: Assessment of Attacks to Distributed Energy Resources and Demand in a Power System","authors":"Néstor Rodríguez-Pérez;Javier Matanza;Lukas Sigrist;José Rueda Torres;Gregorio López","doi":"10.1109/OAJPE.2025.3595631","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3595631","url":null,"abstract":"The increasing penetration of Distributed Energy Resources (DER) expands the cyberattack surface of power systems. This paper analyses, using PowerFactory, the impact and success of MaDIoT 3.0 attacks in the PST-16 model, a simplified model of the European system. MaDIoT 3.0 attacks are a novel type of attack that manage to compromise both high-wattage IoT demand devices and DER devices at the same time. The results indicate that the inclusion of distributed solar PV generation in the PST-16 system reduces the success ratio and impact of load-altering MaDIoT attacks when compared to the same system without DER, mainly due to an increment of the initial voltages. For MaDIoT 3.0 attacks, the demand had a more significant influence on the attack’s success than DER in the PST-16 system. Distributing the attacked demand across more buses or targeting the demand from other areas would decrease the success ratio of the attack. Therefore, the local scalability and replicability of vulnerable high-wattage demand devices in the analysed system become more critical than their distributed deployment in larger areas.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"552-563"},"PeriodicalIF":3.2,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11112612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831775","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 : 2025-07-25DOI: 10.1109/OAJPE.2025.3592698
Shafi Muhammad Jiskani;Tanweer Hussain;Anwar Ali Sahito;Faheemullah Shaikh;Laveet Kumar
High voltage electrical infrastructure inspection requires condition monitoring of transmission line assets to avoid any possible failures or emergency. Detection of insulators in strings is linked with electrical infrastructure monitoring pertaining to the insulator fault classification. The dataset widely available for insulator monitoring are either synthetic, lab created or publicly not available. In this paper, an indigenous dataset is created using Autonomous Aerial Vehicles (AAV) technology, capturing images in diverse topographical ambience across different transmission lines/circuits managed by National transmission and dispatch company ltd. in Pakistan. For detection of insulators in string, object detector model You Only Look Once-version 8 (YOLOv8n) is trained on created dataset of 3618 images, 603 being original and other augmented, after preprocessing and augmentation techniques were applied. The model’s performance is up to the mark with accuracy of 92%. The precision and recall being 0.95 and 0.90 respectively, whereas F1 score of the model peaked at 0.95 at confidence level of 0.652.
高压电力基础设施检查需要对输电线路资产进行状态监测，以避免任何可能的故障或紧急情况。串接绝缘子的检测与绝缘子故障分类相关的电气基础设施监测息息相关。广泛用于绝缘体监测的数据集要么是合成的，要么是实验室创建的，要么是公开不可用的。在本文中，使用自主飞行器（AAV）技术创建了一个本地数据集，在巴基斯坦国家输电和调度公司有限公司管理的不同输电线路/电路中捕获不同地形环境下的图像。针对字符串中绝缘子的检测，在创建的3618张图像数据集上，使用预处理和增强技术，训练You Only Look Once-version 8 （YOLOv8n）目标检测器模型，其中603张为原始图像，其余为增强图像。该模型的性能达到了要求，准确率达到92%。精密度和召回率分别为0.95和0.90，而在置信水平为0.652时，模型的F1得分达到了0.95的峰值。
{"title":"Electrical Infrastructure Monitoring: Case of NTDCL’s 500kV Network Insulator Detection With YoloV8","authors":"Shafi Muhammad Jiskani;Tanweer Hussain;Anwar Ali Sahito;Faheemullah Shaikh;Laveet Kumar","doi":"10.1109/OAJPE.2025.3592698","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3592698","url":null,"abstract":"High voltage electrical infrastructure inspection requires condition monitoring of transmission line assets to avoid any possible failures or emergency. Detection of insulators in strings is linked with electrical infrastructure monitoring pertaining to the insulator fault classification. The dataset widely available for insulator monitoring are either synthetic, lab created or publicly not available. In this paper, an indigenous dataset is created using Autonomous Aerial Vehicles (AAV) technology, capturing images in diverse topographical ambience across different transmission lines/circuits managed by National transmission and dispatch company ltd. in Pakistan. For detection of insulators in string, object detector model You Only Look Once-version 8 (YOLOv8n) is trained on created dataset of 3618 images, 603 being original and other augmented, after preprocessing and augmentation techniques were applied. The model’s performance is up to the mark with accuracy of 92%. The precision and recall being 0.95 and 0.90 respectively, whereas F1 score of the model peaked at 0.95 at confidence level of 0.652.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"505-514"},"PeriodicalIF":3.2,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11096616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773271","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 : 2025-07-17DOI: 10.1109/OAJPE.2025.3590048
Satyaprajna Sahoo;Anamitra Pal
The focus of this paper is on operating the electric power grid in a secure manner during scenarios of active wildfire risk. This is a challenging problem because of the uncertain ways in which the fires can impact the operation of the power system. To address this challenge, we propose a novel preventive-corrective coordinated decision-making scheme that quickly mitigates both static and dynamic insecurities given the risk of active wildfires in a region. The scheme utilizes a comprehensive contingency analysis tool for multi-asset outages that leverages: (i) a “Feasibility Test” algorithm which exhaustively desaturates overloaded cut-sets to prevent cascading line outages, and (ii) a data-driven transient stability analyzer which alleviates dynamic instabilities. This tool is then used to operate a coordinated unit commitment/optimal power flow model that is designed to adapt to varying risk levels associated with wildfires. Depending on the allowed risk, the model balances economical operation and grid robustness. The results obtained using the IEEE 118-bus system indicate that the proposed approach alleviates system vulnerabilities to wildfires while also minimizing operational cost.
{"title":"A Preventive-Corrective Scheme for Ensuring Power System Security During Active Wildfire Risks","authors":"Satyaprajna Sahoo;Anamitra Pal","doi":"10.1109/OAJPE.2025.3590048","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3590048","url":null,"abstract":"The focus of this paper is on operating the electric power grid in a secure manner during scenarios of active wildfire risk. This is a challenging problem because of the uncertain ways in which the fires can impact the operation of the power system. To address this challenge, we propose a novel preventive-corrective coordinated decision-making scheme that quickly mitigates both static and dynamic insecurities given the risk of active wildfires in a region. The scheme utilizes a comprehensive contingency analysis tool for multi-asset outages that leverages: (i) a “Feasibility Test” algorithm which exhaustively desaturates overloaded cut-sets to prevent cascading line outages, and (ii) a data-driven transient stability analyzer which alleviates dynamic instabilities. This tool is then used to operate a coordinated unit commitment/optimal power flow model that is designed to adapt to varying risk levels associated with wildfires. Depending on the allowed risk, the model balances economical operation and grid robustness. The results obtained using the IEEE 118-bus system indicate that the proposed approach alleviates system vulnerabilities to wildfires while also minimizing operational cost.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"492-504"},"PeriodicalIF":3.2,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11083470","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144725166","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 : 2025-07-15DOI: 10.1109/OAJPE.2025.3589243
Mohammadhossein Nazemi;Xiaodong Liang
This paper presents a non-invasive threshold-based method for early detection of stator inter-turn faults (SITFs) and single phasing (SP) faults in induction motors by measuring the three-phase voltages at the motor terminal. These voltage signals are processed to extract the sequence components. The Negative Voltage Factor (NVF) is defined as the ratio of the magnitudes of negative sequence voltage $vert $ V${}_{mathbf {2}} vert $ to positive sequence voltage $vert $ V${}_{mathbf {1}} vert $ , and is used as a fault indicator. The proposed method uses a dual-threshold strategy: a lower threshold for SITFs detection and a higher threshold for SP faults detection by comparing with the VNF values. Unlike traditional current-based approaches, this voltage-based technique proves to be more sensitive and load-independent. Simulation results using ANSYS Maxwell and experiments in the lab for a 2.2 kW induction motor demonstrate the method’s effectiveness to detect incipient SITFs and SP faults accurately under various motor loadings and fault severities.
本文提出了一种基于阈值法的异步电动机定子匝间故障和单相故障的非侵入性早期检测方法，该方法通过测量电动机端电压来实现。对这些电压信号进行处理，提取序列分量。负电压因子（NVF）定义为负序电压$vert $ V ${}_{mathbf {2}} vert $与正序电压$vert $ V ${}_{mathbf {1}} vert $的大小之比，用作故障指示器。该方法采用双阈值策略：通过与VNF值的比较，使用较低的sitf检测阈值和较高的SP故障检测阈值。与传统的基于电流的方法不同，这种基于电压的技术被证明更敏感和负载无关。基于ANSYS Maxwell的仿真和实验室实验结果表明，该方法可以在不同电机负载和故障严重程度下准确检测出早期的sitf和SP故障。
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Pub Date : 2025-07-04DOI: 10.1109/OAJPE.2025.3585994
Haoxiang Gao;Weixin Kang;Miao Fan
Electricity load forecasting constitutes a pivotal task in achieving an equilibrium between supply and demand within the power system, facilitating effective power grid dispatching, and ensuring the safe and stable operation of the grid. The ELM model, characterized by its high efficiency and expeditious training, has become a prevalent approach in the domain of electricity load forecasting. The model’s architecture comprises a front end, a core, and a back end. However, the optimization scheme of the model is optimized for a specific aspect, namely single-objective optimization. This approach disregards the pathological characteristics and overfitting that arise from the simultaneous optimization of the three, the challenges of calculation, and the deviation of the prediction results. This paper proposes a seamless enhanced incremental ELM triple optimization model (SBOA-SEI-MRU-ELM) based on the Secretary bird optimization algorithm and the MINres regularization under the U-curve method to solve the above problem. The optimal input weight matrix and threshold vector can be selected through the front-end module, incremental iteration can be performed through the core, and pathological problems and overfitting can be eliminated through the back-end module. A comparison of the proposed method with traditional single-weight optimization reveals a twofold reduction in MSE and a more than 20% decrease in MAPE. When evaluated against LSTM, SVM, and RBF methods, the proposed method exhibits a one-to-two-order magnitude reduction in MSE and a 1% to 16% decrease in MAPE. The findings demonstrate a competitive edge over research conducted within a specialized branch that utilizes metaheuristic algorithms.
{"title":"A Triple-Optimized Extreme Learning Machine Model for Power Load Forecasting","authors":"Haoxiang Gao;Weixin Kang;Miao Fan","doi":"10.1109/OAJPE.2025.3585994","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3585994","url":null,"abstract":"Electricity load forecasting constitutes a pivotal task in achieving an equilibrium between supply and demand within the power system, facilitating effective power grid dispatching, and ensuring the safe and stable operation of the grid. The ELM model, characterized by its high efficiency and expeditious training, has become a prevalent approach in the domain of electricity load forecasting. The model’s architecture comprises a front end, a core, and a back end. However, the optimization scheme of the model is optimized for a specific aspect, namely single-objective optimization. This approach disregards the pathological characteristics and overfitting that arise from the simultaneous optimization of the three, the challenges of calculation, and the deviation of the prediction results. This paper proposes a seamless enhanced incremental ELM triple optimization model (SBOA-SEI-MRU-ELM) based on the Secretary bird optimization algorithm and the MINres regularization under the U-curve method to solve the above problem. The optimal input weight matrix and threshold vector can be selected through the front-end module, incremental iteration can be performed through the core, and pathological problems and overfitting can be eliminated through the back-end module. A comparison of the proposed method with traditional single-weight optimization reveals a twofold reduction in MSE and a more than 20% decrease in MAPE. When evaluated against LSTM, SVM, and RBF methods, the proposed method exhibits a one-to-two-order magnitude reduction in MSE and a 1% to 16% decrease in MAPE. The findings demonstrate a competitive edge over research conducted within a specialized branch that utilizes metaheuristic algorithms.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"480-491"},"PeriodicalIF":3.3,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11071898","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695472","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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