IEEE Open Access Journal of Power and Energy最新文献

Survey of Load-Altering Attacks Against Power Grids: Attack Impact, Detection, and Mitigation 针对电网的负载改变攻击调查：攻击影响、检测和缓解

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-04-17 DOI: 10.1109/OAJPE.2025.3562052

Sajjad Maleki;Shijie Pan;Subhash Lakshminarayana;Charalambos Konstantinou

引用次数: 0

Soft Actor-Critic-Based MPPT Control of Solar PV Systems Under Partial Shading Conditions 部分遮阳条件下基于软因子临界的太阳能光伏系统MPPT控制

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-04-15 DOI: 10.1109/OAJPE.2025.3560626

Sampson E. Nwachukwu;Komla A. Folly;Kehinde O. Awodele

{"title":"Soft Actor-Critic-Based MPPT Control of Solar PV Systems Under Partial Shading Conditions","authors":"Sampson E. Nwachukwu;Komla A. Folly;Kehinde O. Awodele","doi":"10.1109/OAJPE.2025.3560626","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3560626","url":null,"abstract":"This paper presents a soft actor-critic (SAC)-based method for solving the solar photovoltaic (PV) Maximum Power Point Tracking (MPPT) control problem under partial shading conditions (PSCs). The MPPT method optimizes the solar PV power and ensures that it constantly operates at its “maximum power point (MPP),” regardless of the dynamics of weather conditions. Traditional MPPT methods, such as the perturb and observe (P&O) method, are commonly employed to solve the MPPT control problem. However, they often suffer from a slower convergence rate, significant oscillation near the MPP, drift problems. Additionally, in the presence of partial shading, they frequently fail to track the solar PV global maximum power point (GMPP). These problems were addressed using the deep Q-network (DQN) method. However, DQN cannot be applied to continuous action spaces. It also uses inefficient experience replay and suffers from Q-value overestimation. Thus, under PSCs and certain environmental conditions, DQN produces fluctuations of power close to the MPP or GMPP, resulting in power loss. To solve the MPPT control task, mathematical models of the Markov Decision Process, solar PV system, and boost converter were developed. Key hyperparameters affecting the SAC algorithm’s performance were also investigated. Furthermore, the P&O method was developed for comparison. Simulation results show that the SAC-based MPPT method achieved better tracking accuracy than the DQN method under standard testing conditions, varying irradiance levels, and PSCs. Also, it is shown that both the DQN and SAC methods have superior tracking performance compared to the P&O method under similar environmental conditions tested.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"194-208"},"PeriodicalIF":3.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10965705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892359","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}

引用次数: 0

A Novel Multi-Task Learning-Based Approach to Multi-Energy System Load Forecasting 基于多任务学习的多能源系统负荷预测新方法

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-04-14 DOI: 10.1109/OAJPE.2025.3559336

Zain Ahmed;Mohsin Jamil;Ashraf Ali Khan

引用次数: 0

Graph Learning-Based Power System Health Assessment Model 基于图学习的电力系统健康评估模型

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-31 DOI: 10.1109/OAJPE.2025.3556004

Koji Yamashita;Nanpeng Yu;Evangelos Farantatos;Lin Zhu

{"title":"Graph Learning-Based Power System Health Assessment Model","authors":"Koji Yamashita;Nanpeng Yu;Evangelos Farantatos;Lin Zhu","doi":"10.1109/OAJPE.2025.3556004","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3556004","url":null,"abstract":"As the power transmission system’s energy sources become increasingly diversified, the grid stability is experiencing increased fluctuations, thereby necessitating more frequent and near real-time monitoring by grid operators. The power system security has been monitored through real-time contingency analysis and dynamic security assessment framework, both of which are typically based on time-domain simulations or power flow calculations. Achieving higher accuracy in grid health level prediction often requires time-consuming simulation and analysis. To improve computational efficiency, this paper develops machine learning models with phasor measurement unit (PMU) data to monitor the power system health index, focusing on rotor angle stability and frequency stability. The proposed machine learning models accurately predict frequency and angle stability indicators, essential for evaluating grid health considering various contingencies, even when dealing with limited PMU deployment in transmission grids. The proposed framework leverages a physics-informed graph convolution network and graph attention network with ordinal encoders, which are benchmarked with multi-layer perceptron models. These models are trained on dataset derived from an augmented IEEE 118-bus system with different demand levels and fuel mix, including tailored dynamic generator models, generator controller models, and grid protection models. The numerical studies explored the performance of the proposed and baseline machine learning models under both full PMU coverage and various partial PMU coverage conditions, where different data imputation methods are used for substations without PMUs. The findings from this study offer valuable insights, such as machine learning model selection and critical PMU locations regarding power equipment, into the design of data-driven grid health index prediction models for power systems.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"181-193"},"PeriodicalIF":3.3,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10945887","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800742","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}

引用次数: 0

Energy-Efficient Direct Instantaneous Torque Control of Switched Reluctance Generator at Low Speeds 低速开关磁阻发电机的节能直接瞬时转矩控制

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-20 DOI: 10.1109/OAJPE.2025.3553408

Elmer O. Hancco Catata;Marcelo Vinícius De Paula;Ernesto Ruppert Filho;Tárcio André Dos Santos Barros

{"title":"Energy-Efficient Direct Instantaneous Torque Control of Switched Reluctance Generator at Low Speeds","authors":"Elmer O. Hancco Catata;Marcelo Vinícius De Paula;Ernesto Ruppert Filho;Tárcio André Dos Santos Barros","doi":"10.1109/OAJPE.2025.3553408","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3553408","url":null,"abstract":"An efficient switching method is proposed for Direct Instantaneous Torque Control (DITC) in Switched Reluctance Generators (SRG) operating at low speeds, aiming to enhance system efficiency and reduce torque ripple. In the traditional DITC strategy, the magnetization state in the outgoing phase is enabled at low operating speeds, leading to decreased efficiency and unnecessary torque ripple. The proposed DITC strategy improves efficiency at low speeds while maintaining low torque ripple levels. It prioritizes the freewheeling and demagnetization states during the outgoing period. When the back electromotive force (back EMF) is small, the magnetization state is disabled, using the freewheeling state to smoothly increase torque and the demagnetization state to decrease torque. The magnetization state is reintroduced as the back EMF increases. To implement the modified DITC, an artificial neural network is used to estimate electromagnetic torque. Experimental tests were conducted for both fixed and variable SRG speeds. The proposed method is compared with other methods in the literature. Experimental tests carried out at fixed and variable SRG speeds show that the proposed method significantly enhances efficiency by up to 20% and reduces torque ripple by up to 21% compared to existing methods.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"171-180"},"PeriodicalIF":3.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10935298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Optimal Operation Strategy of an Energy Community Aggregator for Heterogeneous Distributed Flexible Resources 异构分布式柔性资源下能源社区聚合器的最优运行策略

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-07 DOI: 10.1109/OAJPE.2025.3549113

Xinyi Yang;Tao Chen;Yuanshi Zhang;Ciwei Gao;Xingyu Yan;Hongxun Hui;Xiaomeng Ai

{"title":"The Optimal Operation Strategy of an Energy Community Aggregator for Heterogeneous Distributed Flexible Resources","authors":"Xinyi Yang;Tao Chen;Yuanshi Zhang;Ciwei Gao;Xingyu Yan;Hongxun Hui;Xiaomeng Ai","doi":"10.1109/OAJPE.2025.3549113","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3549113","url":null,"abstract":"The widespread integration of renewable energy into the grid emphasizes the issues of power system uncertainty and insufficient flexibility. Heterogeneous flexible distributed resources can address the above challenges by interacting with distribution networks. This paper proposes a multi-timescale optimal operation strategy for an energy community that aggregates multiple distributed resources. Based on flexibility indicators including the degree of load variation and task laxity, a tri-level structure involving distribution system operators (DSOs), aggregators, and the home energy management system (HEMS) is developed. The aggregator serves as mediator between customers and DSOs, gathering the end user’s flexibility through the rescheduling of household appliances to leverage both upward and downward energy adjustments. According to different scenarios and application requirements, a multi-time-scale rolling optimal dispatch model is proposed. The day-ahead dispatch is combined with the Model Predictive Control (MPC) method to achieve fine-grained rolling adjustment of the power dispatch instructions of distributed resources with different time scales. Finally, a simulation experiment example is constructed to verify the effectiveness of the proposed method. The simulation results demonstrate that the economic benefits of end users and aggregators are improved with more grid-friendly load curves.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"157-170"},"PeriodicalIF":3.3,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10916768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706646","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}

引用次数: 0

An Average Power-Based Planning Framework of Transmission Expansion: A New Role for Energy Storage 基于平均功率的输电扩展规划框架：储能的新角色

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-06 DOI: 10.1109/OAJPE.2025.3548911

Qian Zhang;P. R. Kumar;Le Xie

{"title":"An Average Power-Based Planning Framework of Transmission Expansion: A New Role for Energy Storage","authors":"Qian Zhang;P. R. Kumar;Le Xie","doi":"10.1109/OAJPE.2025.3548911","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3548911","url":null,"abstract":"This paper introduces a framework and computational algorithm that utilizes energy storage systems in pairs to improve transmission capacity in electric power systems. Recognizing prolonged development timelines and urgent needs for inter-regional transmission corridors, this paper proposes a near-term supplementary solution that schedules pairs of energy storage systems to increase the throughput of congested transmission lines effectively. We establish a theoretical lower bound on the minimum capacity required for electric power delivery, defined as a function of cumulative power over time. In sharp contrast with conventional transmission planning based on peak power delivery, this new framework allows transmission capacity to be designed around average power delivery needs. This shift would significantly enhance asset utilization in a future grid with large renewable power fluctuations. Numerical experiments demonstrate the proposed method across various grids. In the RTS-GMLC system, the minimum line capacity required was reduced by 36.8% compared to peak-based planning and further decreased by 43.5% when contingency scenarios were considered. In the Texas synthetic grid, the approach achieved a 46.2% reduction in line capacity while maintaining system reliability. These results highlight storage’s potential as a transmission asset, providing practical guidance for planning and policy while enabling insights into future market designs.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"122-134"},"PeriodicalIF":3.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10915681","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667725","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}

引用次数: 0

A Novel Fault Diagnosis of Induction Motor by Using Various Soft Computation Techniques: BESO-RDFA 基于多种软计算技术的异步电动机故障诊断方法：BESO-RDFA

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-04 DOI: 10.1109/OAJPE.2025.3547731

Kapu V. Sri Ram Prasad;K. Dhananjay Rao;Guruvulu Naidu Ponnada;Umit Cali;Taha Selim Ustun

引用次数: 0

Data-Driven Chance-Constrained Capacity Offering for Wind-Electrolysis Joint Systems 数据驱动的机会约束的风力-电解联合系统容量提供

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-03-03 DOI: 10.1109/OAJPE.2025.3545858

Xuemei Dai;Chunyu Chen;Bixing Ren;Shengfei Yin

{"title":"Data-Driven Chance-Constrained Capacity Offering for Wind-Electrolysis Joint Systems","authors":"Xuemei Dai;Chunyu Chen;Bixing Ren;Shengfei Yin","doi":"10.1109/OAJPE.2025.3545858","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3545858","url":null,"abstract":"An alkaline water electrolyzer (AWE) that converts surplus electricity from fluctuating power of a wind farm (WF) is a promising technology for large-scale and cost-effective hydrogen production. By considering the complementarity of the AWEs and the WF in offering market services, this paper treats the AWE and the WF as a coalition and proposes a joint bidding strategy in the energy and regulation markets to maximize the coalition’s revenue. To overcome the influence of wind and hydrogen uncertainties, we first establish a data-driven distributionally robust chance-constrained bidding model, which reduces market risks by observing uncertainty-related chance constraints for any distribution in the ambiguity set. Then, we use the Shapley value method to evaluate the marginal contribution of the AWE and the WF. Further we propose a game-theory-based bidding revenue allocation scheme. Eventually, case studies based on real-world market data demonstrate that the total profit of the proposed joint bidding strategy increases 27.4% if compared with individual bidding strategy. The average marginal cost of hydrogen production can be reduced by <inline-formula> <tex-math>$5.1~ {$}/$ </tex-math></inline-formula>kg if compared with only participating in the energy market.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"111-121"},"PeriodicalIF":3.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908898","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654938","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}

引用次数: 0

Coherency-Constrained Spectral Clustering for Power Network Reduction 基于相干约束的频谱聚类算法

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2025-02-04 DOI: 10.1109/OAJPE.2025.3538619

Mario D. Baquedano-Aguilar;Sean Meyn;Arturo Bretas

{"title":"Coherency-Constrained Spectral Clustering for Power Network Reduction","authors":"Mario D. Baquedano-Aguilar;Sean Meyn;Arturo Bretas","doi":"10.1109/OAJPE.2025.3538619","DOIUrl":"https://doi.org/10.1109/OAJPE.2025.3538619","url":null,"abstract":"This paper presents a methodology for reducing the complexity of large-scale power network models using spectral clustering, aggregation of electrical components, and cost function approximation. Two approaches are explored using unconstrained and constrained spectral clustering to determine areas for effective system reduction. Once the system areas are determined, both loads and generators by type are aggregated, and their new cost function is approximated through polynomial curve-fitting or statistical methods. The performance of reduced networks is evaluated in terms of their ability to follow the true daily cost of the original system over a 24-hour period considering a set of several days. Two test systems are taken as test beds. Application of the methodology to a modified version of the IEEE 39-bus system reduces it from 17 generators to a 4-bus system and 9 generators with about 93% of accuracy. Similarly, the IEEE 118-bus system is reduced from 19 generators to a 3-bus system with three aggregated units achieving over 99% of accuracy. These findings address scalability challenges and enhance accuracy for high and mid-loading level conditions, and by aggregating thermal units with similar cost functions.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"12 ","pages":"88-99"},"PeriodicalIF":3.3,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10870381","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422842","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}

引用次数: 0