Pub Date : 2026-01-22DOI: 10.1109/OAJPE.2026.3656044
{"title":"2025 Index IEEE Open Access Journal of Power and Energy Vol. 12","authors":"","doi":"10.1109/OAJPE.2026.3656044","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3656044","url":null,"abstract":"","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"895-915"},"PeriodicalIF":3.2,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11361308","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026396","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 : 2026-01-16DOI: 10.1109/OAJPE.2026.3651206
Fangxing Fran Li
{"title":"2025 Best Papers, Outstanding Associate Editors, and Outstanding Reviewers","authors":"Fangxing Fran Li","doi":"10.1109/OAJPE.2026.3651206","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3651206","url":null,"abstract":"","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"1-1"},"PeriodicalIF":3.2,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11355900","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982288","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 : 2026-01-12DOI: 10.1109/OAJPE.2026.3652419
Kaiyang Huang;Min Xiong;Yang Liu;Kai Sun;Feng Qiu
Electromagnetic transient simulation plays a crucial role in power system transient stability analysis, but traditional numerical integration methods such as the trapezoidal rule method and the Euler method are time-consuming due to the small and fixed time steps. To improve efficiency, this paper proposes a novel generalized high-order nodal formulation for electromagnetic transient simulations. The method generalizes and extends the traditional companion circuit method to achieve any high-order accuracy. By utilizing a multi-stage diagonally implicit Runge-Kutta method, the corresponding companion circuits of network components are derived. Then, a recursive computation process is proposed to solve the network equation without rebuilding the conductance matrix with multi-stages in a time step. The high-order nodal method allows for larger time steps without sacrificing accuracy. Case studies on a four-bus and an 1170-node system compare the computational efficiency of the proposed method with different orders.
{"title":"A Generalized High-Order Nodal Formulation for Accelerated Electromagnetic Transient Simulation","authors":"Kaiyang Huang;Min Xiong;Yang Liu;Kai Sun;Feng Qiu","doi":"10.1109/OAJPE.2026.3652419","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3652419","url":null,"abstract":"Electromagnetic transient simulation plays a crucial role in power system transient stability analysis, but traditional numerical integration methods such as the trapezoidal rule method and the Euler method are time-consuming due to the small and fixed time steps. To improve efficiency, this paper proposes a novel generalized high-order nodal formulation for electromagnetic transient simulations. The method generalizes and extends the traditional companion circuit method to achieve any high-order accuracy. By utilizing a multi-stage diagonally implicit Runge-Kutta method, the corresponding companion circuits of network components are derived. Then, a recursive computation process is proposed to solve the network equation without rebuilding the conductance matrix with multi-stages in a time step. The high-order nodal method allows for larger time steps without sacrificing accuracy. Case studies on a four-bus and an 1170-node system compare the computational efficiency of the proposed method with different orders.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"64-75"},"PeriodicalIF":3.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11343769","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026577","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 growing use of nonlinear household appliances, such as LED lighting and inverter-based devices, has led to significant power quality problems. This is mainly due to harmonic currents altering the shape of voltage waveforms. Such distortions can lead to increased system losses, transformer overheating, and reduced equipment lifespan. Therefore, this paper proposes an optimized model of a new damped double-tuned filter (DDTF) designed to accommodate dynamic variations in household loads. The particle swarm optimization (PSO) algorithm is used to enhance the design by determining the optimal values for the filter’s constituent parts. Additionally, an artificial neural network (ANN) model is developed to validate and predict filter performance based on experimental data. The DDTF is specifically designed to mitigate dominant harmonics at the 3rd, 5th, and 7th orders. Both simulation and experimental validation were conducted using MATLAB Simulink under realistic household load scenarios. At peak load (2100 W), the unfiltered system exhibited a total harmonic distortion of voltage (THDv) of 155.1%, a total harmonic distortion of current (THDi) of 204.41%, and a power factor of 0.55. After using the new six-stage DDTF at various load levels (from 350 W to 2100 W), the THDv dropped to 7.98%, the THDi fell to 3.57%, and the power factor increased to 0.8089. The ANN-based performance evaluation achieved 94% prediction accuracy, with an error margin of 2% to 6%. These results demonstrate that the designed DDTF is a viable, efficient, and cost-effective approach to mitigating harmonics and enhancing power quality in residential electrical systems.
{"title":"A New Damped Double-Tuned Filter to Improve Power Quality and System Performance for Nonlinear Household Loads","authors":"Faisal Irsan Pasaribu;Ira Devi Sara;Tarmizi Tarmizi;Nasaruddin Nasaruddin","doi":"10.1109/OAJPE.2026.3652375","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3652375","url":null,"abstract":"The growing use of nonlinear household appliances, such as LED lighting and inverter-based devices, has led to significant power quality problems. This is mainly due to harmonic currents altering the shape of voltage waveforms. Such distortions can lead to increased system losses, transformer overheating, and reduced equipment lifespan. Therefore, this paper proposes an optimized model of a new damped double-tuned filter (DDTF) designed to accommodate dynamic variations in household loads. The particle swarm optimization (PSO) algorithm is used to enhance the design by determining the optimal values for the filter’s constituent parts. Additionally, an artificial neural network (ANN) model is developed to validate and predict filter performance based on experimental data. The DDTF is specifically designed to mitigate dominant harmonics at the 3rd, 5th, and 7th orders. Both simulation and experimental validation were conducted using MATLAB Simulink under realistic household load scenarios. At peak load (2100 W), the unfiltered system exhibited a total harmonic distortion of voltage (THDv) of 155.1%, a total harmonic distortion of current (THDi) of 204.41%, and a power factor of 0.55. After using the new six-stage DDTF at various load levels (from 350 W to 2100 W), the THDv dropped to 7.98%, the THDi fell to 3.57%, and the power factor increased to 0.8089. The ANN-based performance evaluation achieved 94% prediction accuracy, with an error margin of 2% to 6%. These results demonstrate that the designed DDTF is a viable, efficient, and cost-effective approach to mitigating harmonics and enhancing power quality in residential electrical systems.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"76-87"},"PeriodicalIF":3.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11343798","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026578","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 : 2025-12-29DOI: 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}
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