IEEE Open Access Journal of Power and Energy最新文献_第4页

Numerical Algorithm for Solving Market Clearing Problem in Power Electronics-Based Power Distribution Systems 电力电子配电系统市场出清问题的数值求解

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-11-18 DOI: 10.1109/OAJPE.2024.3501575

Musharrat Sabah;Aaron M. Cramer;Yuan Liao

引用次数: 0

A Robust Multi-Modal Deep Learning-Based Fault Diagnosis Method for PV Systems 基于鲁棒多模态深度学习的光伏系统故障诊断方法

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-11-13 DOI: 10.1109/OAJPE.2024.3497880

Shahabodin Afrasiabi;Sarah Allahmoradi;Mousa Afrasiabi;Xiaodong Liang;C. Y. Chung;Jamshid Aghaei

引用次数: 0

Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model 利用单粒子模型在线和离线识别电池传感器中的虚假数据注入攻击

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-11-07 DOI: 10.1109/OAJPE.2024.3493757

Victoria A. O’Brien;Vittal S. Rao;Rodrigo D. Trevizan

{"title":"Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model","authors":"Victoria A. O’Brien;Vittal S. Rao;Rodrigo D. Trevizan","doi":"10.1109/OAJPE.2024.3493757","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3493757","url":null,"abstract":"The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"571-582"},"PeriodicalIF":3.3,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10746526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672078","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

Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems 基于模型的配电系统协同攻击（DCA）检测

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-10-31 DOI: 10.1109/OAJPE.2024.3489477

Nitasha Sahani;Chen-Ching Liu

{"title":"Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems","authors":"Nitasha Sahani;Chen-Ching Liu","doi":"10.1109/OAJPE.2024.3489477","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3489477","url":null,"abstract":"The fast-paced growth in digitization of smart grid components enhances system observability and remote-control capabilities through efficient communication. However, enhanced connectivity results in heightened system vulnerability towards cybersecurity risks in the cyber-physical power system. Coordinated cyber-attacks (CCA), when undetected, lead to system-wide impact in terms of large disturbances or widespread outages. Detecting CCA in the cyber layer is critical to thwart cyber-attacks in real-time before the attack impacts the physical system. The challenge of locating CCA stems from the complex grid dynamics, making it difficult to distinguish between normal operational variations and cyber-attack impact. CCA often employs multiple attack vectors targeting geographically distributed components, further complicating CCA identification. Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. In this paper, a novel proactive DCA strategy is proposed for early detection of CCA by establishing correlations among distinct attack events through model-based reinforcement learning that utilizes abductive reasoning to conclude the attacker goal. The solution includes understanding the system model, learning the system dynamics, and correlating individual cyber-attacks to extract the attacker’s objective. The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. A DNP3-based cyber-physical co-simulation testbed is developed to test the proposed algorithm using the IEEE 13-node test feeder.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"558-570"},"PeriodicalIF":3.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10740327","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636308","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 Dual-Rotor Homopolar AC Machine 新型双转子同极性交流电机

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-10-10 DOI: 10.1109/OAJPE.2024.3475928

T. Ruekamnuaychok;J. Zhong;S. Sudhoff;R. Swanson;A. Sah;H. Singh;N. Aronhime;E. Schultz

引用次数: 0

Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning 通过少量元学习学习电力系统波形初始模式

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-10-10 DOI: 10.1109/OAJPE.2024.3477630

Lixian Shi;Qiushi Cui;Yang Weng;Yigong Zhang;Shilong Chen;Jian Li;Wenyuan Li

{"title":"Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning","authors":"Lixian Shi;Qiushi Cui;Yang Weng;Yigong Zhang;Shilong Chen;Jian Li;Wenyuan Li","doi":"10.1109/OAJPE.2024.3477630","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3477630","url":null,"abstract":"Incipient faults (IFs) are abnormal states before the permanent failure of power equipment. IFs are typically transient and generally do not trigger the operation of relay protection devices. This leads the difficulty in capturing IF data from waveform monitoring or recording devices. However, traditional detection methods cannot achieve satisfactory performance when faced with limited data. Besides, some signal analysis methods based on waveform conversion to images cannot obtain understandable image data and cannot analyze both current and voltage signals simultaneously. To resolve these problems, a few-shot meta-learning framework for incipient fault detection (FSMLF-IFD) is proposed in this paper. For better data processing, a waveform image conversion strategy is proposed to convert waveforms into understandable images from the time domain perspective. Then, an adaptive image fusion strategy is developed to concurrently analyze voltage and current images. Next, at the meta-training stage, an adaptability-enhancing weighting initialization strategy is constructed to address the data differences between the meta-training stage and IF detection stage. Finally, an IF detection model based on convolutional neural networks (CNNs) is obtained through the fine-tuning process. In the numerical results, the IF detection and classification accuracy of FSMLF-IFD reached 0.9720 and 0.9840 based on simulation and field IF data, which validates the effectiveness of the proposed method.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"532-545"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10713429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142452743","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

Data Driven Real-Time Dynamic Voltage Control Using Decentralized Execution Multi-Agent Deep Reinforcement Learning 利用分散执行多代理深度强化学习实现数据驱动的实时动态电压控制

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-09-12 DOI: 10.1109/OAJPE.2024.3459002

Yuling Wang;Vijay Vittal

{"title":"Data Driven Real-Time Dynamic Voltage Control Using Decentralized Execution Multi-Agent Deep Reinforcement Learning","authors":"Yuling Wang;Vijay Vittal","doi":"10.1109/OAJPE.2024.3459002","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3459002","url":null,"abstract":"In recent years, there has been an increasing need for effective voltage control methods in power systems due to the growing complexity and dynamic nature of practical power grid operations. To enhance the controller’s resilience in addressing communication failures, a dynamic voltage control method employing distributed execution multi-agent deep reinforcement learning(DRL) is proposed. The proposed method follows a centralized training and decentralized execution based approach. Each agent has independent actor neural networks to output generator control commands and critic neural networks that evaluate command performance. Detailed dynamic models are integrated for agent training to effectively capture the system’s dynamic behavior following disturbances. Subsequent to training, each agent possesses the capability to autonomously generate control commands utilizing only local information. Simulation outcomes underscore the efficacy of the distributed execution multi-agent DRL controller, showcasing its capability in not only providing voltage support but also effectively handling communication failures among agents.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"508-519"},"PeriodicalIF":3.3,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10679222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368490","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

Global Research Priorities for Holistic Integration of Water and Power Systems 水电系统整体整合的全球研究重点

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-09-10 DOI: 10.1109/OAJPE.2024.3457448

Rebecca O’Neil;Konstantinos Oikonomou;Vince Tidwell;Nathalie Voisin;Jessica Kerby;Z. Jason Hou;Masood Parvania;Ali T. Al-Awami;Mathaios Panteli;Steven A. Conrad;Ted K. A. Brekken

{"title":"Global Research Priorities for Holistic Integration of Water and Power Systems","authors":"Rebecca O’Neil;Konstantinos Oikonomou;Vince Tidwell;Nathalie Voisin;Jessica Kerby;Z. Jason Hou;Masood Parvania;Ali T. Al-Awami;Mathaios Panteli;Steven A. Conrad;Ted K. A. Brekken","doi":"10.1109/OAJPE.2024.3457448","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3457448","url":null,"abstract":"Energy and water systems are deeply interdependent yet organized and managed into separate sectors. Although technological innovations emerge at the intersection of energy and water, these sectors largely operate independently, despite their mutual importance. This persistent challenge is structural, as the sectors are organized and managed as separate systems. More can be done to integrate these sectors for mutual benefit and resilience. This paper provides an overview and a useful categorization of six research areas that bridge the water and energy sectors: integrated planning, integrated operations, data and analytics, policy and economics, hydropower and marine energy, and resilience. The authors lead the IEEE Power & Energy Society Task Force on Water-Power Systems (WPS), which represents an international and rapidly growing collaboration across both energy and water sectors to find common areas of cooperation and innovation. Through the collective efforts of this Task Force, a comprehensive roadmap on water power systems integration was issued in 2023. The paper presents evidence that coordinated efforts in data analytics, policy, and economic interventions can significantly advance hydropower, marine energy, and energy storage technologies, ultimately enhancing the resilience and efficiency of both water and power infrastructures.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"457-468"},"PeriodicalIF":3.3,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10674014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274943","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

Floating Neutral Detection Using Actual Generation of Form 2S Meters 使用实际生成的 2S 表进行浮动中性点检测

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-09-06 DOI: 10.1109/OAJPE.2024.3455756

I. Vicente;A. Arrinda;J. E. Rodríguez-Seco;L. Piyasinghe

{"title":"Floating Neutral Detection Using Actual Generation of Form 2S Meters","authors":"I. Vicente;A. Arrinda;J. E. Rodríguez-Seco;L. Piyasinghe","doi":"10.1109/OAJPE.2024.3455756","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3455756","url":null,"abstract":"In the low-voltage distribution system of the USA, Canada and some countries of Central and South America, the most used configuration is the single-phase three-wire system (120 V/240 V) also known as the split-phase distribution system. When the neutral wire of the distribution system gets damaged or broken the current returns through the ground and a floating neutral condition arises. Service to the house continues without interruptions because no high over-currents come up. If the return path impedance is high enough, the equally balanced voltage system gets shifted, going out of boundaries and causing malfunctions in the appliances or even fire. A new classification-based detector is proposed to detect this condition, which only needs current measurements that the actual generation of form 2S meter gathers. Moreover, due to the simplicity of the algorithm, it can be embedded in the current generation of meters, which represents great potential of the detector. To that end, the low-voltage distribution system is modelled using a real database and some assumptions are made. The proposed novel detector approach shows zero false alarms in the houses tested and a detection time that allows the fault to be detected before significant damage occurs to the house.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"481-492"},"PeriodicalIF":3.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275001","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 Model Predictive Control Framework for Combining Energy Arbitrage and Power Quality Applications From Energy Storage Systems 结合储能系统能源套利和电能质量应用的模型预测控制框架

IF 3.3

IEEE Open Access Journal of Power and Energy Pub Date : 2024-08-29 DOI: 10.1109/OAJPE.2024.3451501

Ujjwol Tamrakar;Niranjan Bhujel;Tu A. Nguyen;Raymond H. Byrne;Babu Chalamala

{"title":"A Model Predictive Control Framework for Combining Energy Arbitrage and Power Quality Applications From Energy Storage Systems","authors":"Ujjwol Tamrakar;Niranjan Bhujel;Tu A. Nguyen;Raymond H. Byrne;Babu Chalamala","doi":"10.1109/OAJPE.2024.3451501","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3451501","url":null,"abstract":"Energy storage systems (ESSs) are a flexible resource that will be vital to meet the aggressive clean energy targets of the future. However, the economic gains from ESSs can be limited due to large capital investments and monetization challenges. It is thus desirable to utilize ESSs for multiple techno-economic benefits to justify deployment costs. In this work, a framework to simultaneously dispatch ESSs for energy arbitrage and power quality applications is presented. More specifically, a model predictive control (MPC)-based framework that can dispatch energy storage to accomplish multiple techno-economic objectives is proposed. This is achieved without impacting market revenues while satisfying all power system and ESS constraints. Simulation results indicate that power quality applications such as voltage regulation and power factor correction can be stacked with arbitrage without significantly impacting arbitrage revenues and in some cases even improving the revenues. A controller-hardware-in-the-loop (CHIL) study of the proposed framework is also performed to demonstrate the practical feasibility of the framework.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"469-480"},"PeriodicalIF":3.3,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10659047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274962","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