Pub Date : 2025-12-29DOI: 10.1109/OAJPE.2025.3649154
Mitsuyoshi Enomoto;Keima Wakatsuki;Kenichiro Sano
Multi-terminal high-voltage dc (HVDC) transmission system is a promising approach to connect offshore wind power plants (WPPs) to onshore ac grids. However, there is no standardized protection method against DC faults. As one of its protection methods, mechanical dc circuit breakers (DCCBs) have the potential to improve supply reliability against dc faults while avoiding a cost increase. Nevertheless, due to their relatively slower operation, the blocking of half-bridge-based modular multilevel converter (HBMMC) is often required. In offshore ac collecting system, where the HBMMC maintains the grid voltage, such converter blocking can destabilize the grid voltage and lead to shutdowns of offshore WPPs. Large scale shutdowns of offshore WPPs may have a negative impact on onshore ac grids. Therefore, this article proposes a protection method that enables the continuous operation of offshore WPPs while using mechanical DCCBs. The proposed method focuses on the backbone HVDC configuration connecting multiple onshore and offshore terminals, and applies different fault clearing methods across the terminals. At onshore terminals which form a loop configuration, mechanical DCCBs selectively isolate the faulted section. At offshore terminals which form a radial configuration, reconfiguration is employed to reroute power transmission from the faulted line to the healthy line. These operations are coordinated based on the fault ride-through (FRT) capability of offshore WPPs and realizes their continuous operation. The proposed method is verified by an experiment using the scaled-down three-terminal HVDC system.
{"title":"Protection Method for Continuous Operation of Wind Power Plants in a Mechanical Circuit Breaker-Based Multi-Terminal HVDC System","authors":"Mitsuyoshi Enomoto;Keima Wakatsuki;Kenichiro Sano","doi":"10.1109/OAJPE.2025.3649154","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3649154","url":null,"abstract":"Multi-terminal high-voltage dc (HVDC) transmission system is a promising approach to connect offshore wind power plants (WPPs) to onshore ac grids. However, there is no standardized protection method against DC faults. As one of its protection methods, mechanical dc circuit breakers (DCCBs) have the potential to improve supply reliability against dc faults while avoiding a cost increase. Nevertheless, due to their relatively slower operation, the blocking of half-bridge-based modular multilevel converter (HBMMC) is often required. In offshore ac collecting system, where the HBMMC maintains the grid voltage, such converter blocking can destabilize the grid voltage and lead to shutdowns of offshore WPPs. Large scale shutdowns of offshore WPPs may have a negative impact on onshore ac grids. Therefore, this article proposes a protection method that enables the continuous operation of offshore WPPs while using mechanical DCCBs. The proposed method focuses on the backbone HVDC configuration connecting multiple onshore and offshore terminals, and applies different fault clearing methods across the terminals. At onshore terminals which form a loop configuration, mechanical DCCBs selectively isolate the faulted section. At offshore terminals which form a radial configuration, reconfiguration is employed to reroute power transmission from the faulted line to the healthy line. These operations are coordinated based on the fault ride-through (FRT) capability of offshore WPPs and realizes their continuous operation. The proposed method is verified by an experiment using the scaled-down three-terminal HVDC system.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"15-26"},"PeriodicalIF":3.2,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11316639","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026541","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 : 2025-12-17DOI: 10.1109/OAJPE.2025.3645250
Mohammad GOLGOL;Anamitra Pal;Vijay Vittal;Christine Kessinger;Ernest Palomino;Kyle Girardi
The installation of high-capacity fast electric vehicle (EV) chargers at the residential level is posing a significant risk to the distribution grid. This is because the increased demand from such forms of charging could exceed the ratings of the distribution assets, particularly, transformers. Addressing this issue is critical, given that current infrastructure upgrades to enhance EV hosting capacity are both costly and time-consuming. This study addresses this challenging problem by introducing a novel algorithm to maximize residential EV charging without overloading any transformer within the feeder. The proposed method is applied to a real-world utility feeder in Arizona, which includes 120 transformers of varying capacities. The results demonstrate that this approach effectively manages a substantial number of EVs without overloading the transformers. It also identifies locations that must be prioritized for future upgrades. The proposed framework can serve as a valuable reference tool for utilities when conducting distribution system planning for supporting the growing EV penetration.
{"title":"Maximizing Grid Support of Electric Vehicles by Coordinating Residential Charging: Insights From an Arizona Feeder Case Study","authors":"Mohammad GOLGOL;Anamitra Pal;Vijay Vittal;Christine Kessinger;Ernest Palomino;Kyle Girardi","doi":"10.1109/OAJPE.2025.3645250","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3645250","url":null,"abstract":"The installation of high-capacity fast electric vehicle (EV) chargers at the residential level is posing a significant risk to the distribution grid. This is because the increased demand from such forms of charging could exceed the ratings of the distribution assets, particularly, transformers. Addressing this issue is critical, given that current infrastructure upgrades to enhance EV hosting capacity are both costly and time-consuming. This study addresses this challenging problem by introducing a novel algorithm to maximize residential EV charging without overloading any transformer within the feeder. The proposed method is applied to a real-world utility feeder in Arizona, which includes 120 transformers of varying capacities. The results demonstrate that this approach effectively manages a substantial number of EVs without overloading the transformers. It also identifies locations that must be prioritized for future upgrades. The proposed framework can serve as a valuable reference tool for utilities when conducting distribution system planning for supporting the growing EV penetration.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"27-38"},"PeriodicalIF":3.2,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11303219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026621","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 : 2025-12-17DOI: 10.1109/OAJPE.2025.3645591
Magnus Tarle;Mats Larsson;Gunnar Ingeström;Mårten Björkman
Coordinated control of Flexible AC Transmission Systems (FACTS) setpoints can significantly enhance power flow and voltage control. However, optimizing the setpoints of multiple FACTS devices in real-world systems remains uncommon, partly due to challenges in model-based control. Data-driven approaches, such as reinforcement learning (RL), offer a promising alternative for coordinated control. In this work, we address a setting where a useful real-time network model is unavailable. Recognizing the increasing deployment of Phasor Measurement Units (PMUs) for advanced monitoring and control, we consider having access to a few but reliable measurements and a constraint violation signal. Under these assumptions, we demonstrate on several scenarios on the IEEE 14-bus and IEEE 57-bus systems that an RL-based optimization of FACTS setpoints can substantially reduce voltage deviations compared to a fixed-setpoint baseline. To improve robustness and prevent unobserved constraint violations, we show that a complete, albeit simple, constraint violation signal is necessary. As an alternative to relying on such a signal, Dynamic Mode Decomposition is proposed to determine new PMU placements, thereby reducing the risk of unobserved constraint violations. Finally, to assess the gap to an optimal policy, we benchmark the RL-based agent against a model-based optimal controller with perfect information.
{"title":"Reinforcement Learning for Optimizing FACTS Setpoints With Limited Set of Measurements","authors":"Magnus Tarle;Mats Larsson;Gunnar Ingeström;Mårten Björkman","doi":"10.1109/OAJPE.2025.3645591","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3645591","url":null,"abstract":"Coordinated control of Flexible AC Transmission Systems (FACTS) setpoints can significantly enhance power flow and voltage control. However, optimizing the setpoints of multiple FACTS devices in real-world systems remains uncommon, partly due to challenges in model-based control. Data-driven approaches, such as reinforcement learning (RL), offer a promising alternative for coordinated control. In this work, we address a setting where a useful real-time network model is unavailable. Recognizing the increasing deployment of Phasor Measurement Units (PMUs) for advanced monitoring and control, we consider having access to a few but reliable measurements and a constraint violation signal. Under these assumptions, we demonstrate on several scenarios on the IEEE 14-bus and IEEE 57-bus systems that an RL-based optimization of FACTS setpoints can substantially reduce voltage deviations compared to a fixed-setpoint baseline. To improve robustness and prevent unobserved constraint violations, we show that a complete, albeit simple, constraint violation signal is necessary. As an alternative to relying on such a signal, Dynamic Mode Decomposition is proposed to determine new PMU placements, thereby reducing the risk of unobserved constraint violations. Finally, to assess the gap to an optimal policy, we benchmark the RL-based agent against a model-based optimal controller with perfect information.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"51-63"},"PeriodicalIF":3.2,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11303221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026449","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 : 2025-12-12DOI: 10.1109/OAJPE.2025.3643748
Taulant Kërçi;Federico Milano
This industry-oriented paper introduces the concept of ‘frequency control strength’ as a novel approach to understand how different real-world power systems compare to each other in terms of effectiveness and performance of system-wide frequency control. It presents a comprehensive comparison, based on measurement data, of the frequency control strength of four real-world, renewable-based, synchronous island power systems, namely Great Britain (GB), the All-Island power system (AIPS) of Ireland, and Australia (AUS) mainland and Tasmania (TAS). The strength is evaluated by means of different frequency quality metrics. The common understanding is that the bigger the capacity of a power system, the bigger its robustness with respect to events and contingencies. Here we show that this is not always the case in the context of frequency control. In fact, our study shows that mainland AUS shows the highest frequency control strength during normal operating conditions, whereas the AIPS shows the highest relative frequency control strength for abnormal system conditions. The strength is, in particular, greatly influenced by different regulatory requirements and different system/ancillary services arrangements in each jurisdiction. The paper also provides possible mitigations to improve frequency control strength through grid codes and market rules.
{"title":"A Comprehensive Approach to Evaluate Frequency Control Strength of Power Systems","authors":"Taulant Kërçi;Federico Milano","doi":"10.1109/OAJPE.2025.3643748","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3643748","url":null,"abstract":"This industry-oriented paper introduces the concept of ‘frequency control strength’ as a novel approach to understand how different real-world power systems compare to each other in terms of effectiveness and performance of system-wide frequency control. It presents a comprehensive comparison, based on measurement data, of the frequency control strength of four real-world, renewable-based, synchronous island power systems, namely Great Britain (GB), the All-Island power system (AIPS) of Ireland, and Australia (AUS) mainland and Tasmania (TAS). The strength is evaluated by means of different frequency quality metrics. The common understanding is that the bigger the capacity of a power system, the bigger its robustness with respect to events and contingencies. Here we show that this is not always the case in the context of frequency control. In fact, our study shows that mainland AUS shows the highest frequency control strength during normal operating conditions, whereas the AIPS shows the highest relative frequency control strength for abnormal system conditions. The strength is, in particular, greatly influenced by different regulatory requirements and different system/ancillary services arrangements in each jurisdiction. The paper also provides possible mitigations to improve frequency control strength through grid codes and market rules.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"39-50"},"PeriodicalIF":3.2,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11299077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026594","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 : 2025-12-10DOI: 10.1109/OAJPE.2025.3642553
Cheng Qian;Zaijun Wu;Dongliang Xu;Xiaobo Dou;Qinran Hu
Residential loads, with their substantial scale, rapid response speed, and flexible controllability, have become a crucial resource for demand side management. However, privacy concerns arising from data communication and the complexity of response strategies due to variations in customer flexibility present significant challenges to the effectiveness of demand response (DR) programs. To address these issues, this paper proposes a load management framework based on a multi-cluster mean-field (MCMF) game. Firstly, customer flexibility is quantified based on historical power consumption data, and an improved k-means algorithm is employed to cluster customers within the community. Then, considering each customer’s optimization objective to minimize the cost function including the electricity cost and the discomfort level, the problem is formulated as an MCMF game. Customers adjust their power consumption strategies according to the group-specific estimated electricity price, while the load aggregator (LA) collects total power consumption values and updates the price information iteratively until the optimal strategies of all customers converge to an $varepsilon $ -Nash equilibrium ($varepsilon $ -NE). Case studies involving 2000 customers with heterogeneous flexibility are conducted, and the results demonstrate the effectiveness and advantages of the proposed framework compared with existing methods in peak shaving, electricity cost reduction, and computational efficiency.
{"title":"A Multi-Cluster Mean-Field Game-Based Demand Response Management for Large-Scale Residential Customers With Heterogeneous Flexibility","authors":"Cheng Qian;Zaijun Wu;Dongliang Xu;Xiaobo Dou;Qinran Hu","doi":"10.1109/OAJPE.2025.3642553","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3642553","url":null,"abstract":"Residential loads, with their substantial scale, rapid response speed, and flexible controllability, have become a crucial resource for demand side management. However, privacy concerns arising from data communication and the complexity of response strategies due to variations in customer flexibility present significant challenges to the effectiveness of demand response (DR) programs. To address these issues, this paper proposes a load management framework based on a multi-cluster mean-field (MCMF) game. Firstly, customer flexibility is quantified based on historical power consumption data, and an improved k-means algorithm is employed to cluster customers within the community. Then, considering each customer’s optimization objective to minimize the cost function including the electricity cost and the discomfort level, the problem is formulated as an MCMF game. Customers adjust their power consumption strategies according to the group-specific estimated electricity price, while the load aggregator (LA) collects total power consumption values and updates the price information iteratively until the optimal strategies of all customers converge to an <inline-formula> <tex-math>$varepsilon $ </tex-math></inline-formula>-Nash equilibrium (<inline-formula> <tex-math>$varepsilon $ </tex-math></inline-formula>-NE). Case studies involving 2000 customers with heterogeneous flexibility are conducted, and the results demonstrate the effectiveness and advantages of the proposed framework compared with existing methods in peak shaving, electricity cost reduction, and computational efficiency.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"2-14"},"PeriodicalIF":3.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11296832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026539","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 : 2025-12-05DOI: 10.1109/OAJPE.2025.3640636
Xiaofei Wang;Jiazi Zhang;Leonardo Rese;Mingjian Tuo;Hongfei Sun
With the worldwide growth in deploying high-voltage direct current (HVDC) transmission systems, their ability to facilitate black-start (BS) restoration has been a research topic of interest. In this context, voltage source converter (VSC)-HVDC is regarded as a BS resource, and this paper proposes a VSC-HVDC-assisted parallel BS restoration strategy in bulk power systems. The proposed strategy consists of two stages: 1) determination of the VSC and generator startup sequence and 2) load restoration simulation. In the first stage, the entire blackout system is sectionalized into multiple subsystems. Each subsystem includes a VSC-HVDC station or traditional BS unit, it independently determines its generator startup timeline and the energization timelines for buses and lines. The second stage involves load restoration, conceptualized as a modified unit commitment problem, with the timelines established in the first stage work as critical inputs. The proposed BS restoration strategy is tested on the San Diego power system to simulate the 2011 Southwest blackout. The simulation results validate the effectiveness of using VSC-HVDC links as a BS resource which not only speeds up the restoration process but also reduces both energy and economic losses.
{"title":"A VSC-HVDC-Assisted Black-Start Strategy in Bulk Power Systems a Case Study in San Diego","authors":"Xiaofei Wang;Jiazi Zhang;Leonardo Rese;Mingjian Tuo;Hongfei Sun","doi":"10.1109/OAJPE.2025.3640636","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3640636","url":null,"abstract":"With the worldwide growth in deploying high-voltage direct current (HVDC) transmission systems, their ability to facilitate black-start (BS) restoration has been a research topic of interest. In this context, voltage source converter (VSC)-HVDC is regarded as a BS resource, and this paper proposes a VSC-HVDC-assisted parallel BS restoration strategy in bulk power systems. The proposed strategy consists of two stages: 1) determination of the VSC and generator startup sequence and 2) load restoration simulation. In the first stage, the entire blackout system is sectionalized into multiple subsystems. Each subsystem includes a VSC-HVDC station or traditional BS unit, it independently determines its generator startup timeline and the energization timelines for buses and lines. The second stage involves load restoration, conceptualized as a modified unit commitment problem, with the timelines established in the first stage work as critical inputs. The proposed BS restoration strategy is tested on the San Diego power system to simulate the 2011 Southwest blackout. The simulation results validate the effectiveness of using VSC-HVDC links as a BS resource which not only speeds up the restoration process but also reduces both energy and economic losses.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"870-881"},"PeriodicalIF":3.2,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278889","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778151","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 : 2025-12-05DOI: 10.1109/OAJPE.2025.3640666
Reynaldo S. Gonzalez;Ahmed Almoola;Krishna S. Ayyagari;Venkatanaga A. Aryasomyajula;Nikolaos Gatsis;Miltiadis Alamaniotis;Sara Ahmed
Optimal protection coordination (OPC) is a well-established problem with numerous solution methods, including mathematical optimization and genetic algorithms. Traditional OPC formulations for overcurrent relays typically optimize two parameters: the time dial setting (TDS) and the pickup current. However, modern relays offer additional curve characteristics, yet standard formulations do not fully utilize these additional settings. This paper introduces a novel OPC formulation for dual-setting relays that integrates inverse-time and definite-time curve characteristics. The optimization variables include TDS, pickup current, short-time delay (STD), and short-time pickup (STP) To ensure proper coordination, new constraints are developed for the interplay of these four settings per relay. The problem is formulated as a Mixed-Integer Nonlinear Programming (MINLP) task, solved using both a general-purpose MINLP solver and a Genetic Algorithm (GA). The approach is validated on the IEEE 123-bus network integrating inverter-based resources with limited fault current contributions under two switch configurations, which are selected to alter current flows and reassign backup roles among relays. Results demonstrate that incorporating dual-curve settings significantly reduces total relay operation time and improves discrimination times between primary and backup relays, compared to the standard OPC formulation.
{"title":"Optimal Protection Coordination of Dual-Setting Relays With Inverse-Time and Definite-Time Characteristics","authors":"Reynaldo S. Gonzalez;Ahmed Almoola;Krishna S. Ayyagari;Venkatanaga A. Aryasomyajula;Nikolaos Gatsis;Miltiadis Alamaniotis;Sara Ahmed","doi":"10.1109/OAJPE.2025.3640666","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3640666","url":null,"abstract":"Optimal protection coordination (OPC) is a well-established problem with numerous solution methods, including mathematical optimization and genetic algorithms. Traditional OPC formulations for overcurrent relays typically optimize two parameters: the time dial setting (TDS) and the pickup current. However, modern relays offer additional curve characteristics, yet standard formulations do not fully utilize these additional settings. This paper introduces a novel OPC formulation for dual-setting relays that integrates inverse-time and definite-time curve characteristics. The optimization variables include TDS, pickup current, short-time delay (STD), and short-time pickup (STP) To ensure proper coordination, new constraints are developed for the interplay of these four settings per relay. The problem is formulated as a Mixed-Integer Nonlinear Programming (MINLP) task, solved using both a general-purpose MINLP solver and a Genetic Algorithm (GA). The approach is validated on the IEEE 123-bus network integrating inverter-based resources with limited fault current contributions under two switch configurations, which are selected to alter current flows and reassign backup roles among relays. Results demonstrate that incorporating dual-curve settings significantly reduces total relay operation time and improves discrimination times between primary and backup relays, compared to the standard OPC formulation.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"882-894"},"PeriodicalIF":3.2,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830944","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}
False Data Injection Attacks (FDIAs) pose a substantial risk to the reliability and stability of Cyber-Physical Power Systems (CPPS). While federated learning (FL) has emerged as a promising approach to detect such attacks without exposing sensitive data, security concerns remain in FL, including untrusted central aggregators and potential malicious client updates. This research integrate a private Ethereum blockchain layer and homomorphic encryption into a secure FL framework for FDIA detection to verify model updates and authenticate participating nodes. We design smart contracts to immutably log model update hashes and enforce client authentication, enhancing traceability and tamper-resistance. A prototype implementation uses Ethereum smart contracts for model update verification and client identity management. We simulate the blockchain-integrated FL on a cyber-physical power system dataset using three detection models – XGBoost, LSTM, and a Transformer – and analyze the blockchain-induced latency and communication overhead under a specific network configuration. Results show that the blockchain layer has negligible impact on detection accuracy (global AUC $sim 0.94 text {-}0.96$ across models) while introducing a moderate training time overhead ($sim 13- -40%$ increase in training duration due to block confirmation delays). The proposed research demonstrates a viable approach to blockchain-aided federated learning for critical infrastructure security, combining data privacy, model integrity, and participant trust in a unified framework.
{"title":"Blockchain-Integrated Federated Learning Framework for Detecting False Data Injection Attacks in Power Systems With Homomorphic Encryption","authors":"Firdous Kausar;Sajid Hussain;Karl Walker;Ayesha Imam","doi":"10.1109/OAJPE.2025.3631069","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3631069","url":null,"abstract":"False Data Injection Attacks (FDIAs) pose a substantial risk to the reliability and stability of Cyber-Physical Power Systems (CPPS). While federated learning (FL) has emerged as a promising approach to detect such attacks without exposing sensitive data, security concerns remain in FL, including untrusted central aggregators and potential malicious client updates. This research integrate a private Ethereum blockchain layer and homomorphic encryption into a secure FL framework for FDIA detection to verify model updates and authenticate participating nodes. We design smart contracts to immutably log model update hashes and enforce client authentication, enhancing traceability and tamper-resistance. A prototype implementation uses Ethereum smart contracts for model update verification and client identity management. We simulate the blockchain-integrated FL on a cyber-physical power system dataset using three detection models – XGBoost, LSTM, and a Transformer – and analyze the blockchain-induced latency and communication overhead under a specific network configuration. Results show that the blockchain layer has negligible impact on detection accuracy (global AUC <inline-formula> <tex-math>$sim 0.94 text {-}0.96$ </tex-math></inline-formula> across models) while introducing a moderate training time overhead (<inline-formula> <tex-math>$sim 13- -40%$ </tex-math></inline-formula> increase in training duration due to block confirmation delays). The proposed research demonstrates a viable approach to blockchain-aided federated learning for critical infrastructure security, combining data privacy, model integrity, and participant trust in a unified framework.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"819-832"},"PeriodicalIF":3.2,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11237138","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612096","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 : 2025-11-07DOI: 10.1109/OAJPE.2025.3630180
Nupur;Yaosuo Xue;Fred Wang
The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. This paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.
{"title":"Spectral Clustering-Based Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis","authors":"Nupur;Yaosuo Xue;Fred Wang","doi":"10.1109/OAJPE.2025.3630180","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3630180","url":null,"abstract":"The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. This paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"806-818"},"PeriodicalIF":3.2,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11234885","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560780","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}
Reconfiguration in low-inertia microgrids (MGs) can often result in a critical small-signal stability margin. In this condition, the ability of inverter-based resources (IBRs) to provide voltage and frequency support may be insufficient. To maintain stable operation without interruptions, this paper presents a control strategy that first evaluates the effect of MG reconfiguration on system stability and then employs controllable loads as an enhancement mechanism to improve small-signal stability in scenarios involving reconfigurable MGs, particularly during islanded operation or high-demand situations such as sudden load changes or fault recovery. Mathematical models of system reconfiguration are presented. Then, we demonstrate how reconfiguration in MGs can result in marginal small-signal stability. The proposed framework operates in two stages: (i) assessing optimal breaker/switch configurations to ensure a baseline stability margin, and (ii) using controllable loads to fine-tune and improve damping performance. It is shown that the proposed framework can shift stability from critical or unstable levels to an acceptable range, making the initial conditions of reconfigured MGs feasible. Simulation results in a reconfigurable MG with different portions of IBRs and controllable loads demonstrate the effectiveness of the proposed framework in using controllable loads to successfully enhance small-signal stability. The proposed strategy ensures that the reconfigured MGs remain stable after reconfigurations.
{"title":"Two-Stage Small-Signal Stability-Assisted Framework Using Controllable Loads in Reconfigurable Microgrids","authors":"Tossaporn Surinkaew;Watcharakorn Pinthurat;Boonruang Marungsri;Branislav Hredzak","doi":"10.1109/OAJPE.2025.3628911","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3628911","url":null,"abstract":"Reconfiguration in low-inertia microgrids (MGs) can often result in a critical small-signal stability margin. In this condition, the ability of inverter-based resources (IBRs) to provide voltage and frequency support may be insufficient. To maintain stable operation without interruptions, this paper presents a control strategy that first evaluates the effect of MG reconfiguration on system stability and then employs controllable loads as an enhancement mechanism to improve small-signal stability in scenarios involving reconfigurable MGs, particularly during islanded operation or high-demand situations such as sudden load changes or fault recovery. Mathematical models of system reconfiguration are presented. Then, we demonstrate how reconfiguration in MGs can result in marginal small-signal stability. The proposed framework operates in two stages: (i) assessing optimal breaker/switch configurations to ensure a baseline stability margin, and (ii) using controllable loads to fine-tune and improve damping performance. It is shown that the proposed framework can shift stability from critical or unstable levels to an acceptable range, making the initial conditions of reconfigured MGs feasible. Simulation results in a reconfigurable MG with different portions of IBRs and controllable loads demonstrate the effectiveness of the proposed framework in using controllable loads to successfully enhance small-signal stability. The proposed strategy ensures that the reconfigured MGs remain stable after reconfigurations.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"772-783"},"PeriodicalIF":3.2,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11224833","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510197","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：