2022 IEEE Texas Power and Energy Conference (TPEC)最新文献_第5页

Scalable Protection and Self-Healing of Microgrids: Hardware In The Loop Co-Simulation 微电网的可扩展保护和自修复:硬件在环联合仿真

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750681

P. Gadde, S. Brahma, Trupal Patel

{"title":"Scalable Protection and Self-Healing of Microgrids: Hardware In The Loop Co-Simulation","authors":"P. Gadde, S. Brahma, Trupal Patel","doi":"10.1109/TPEC54980.2022.9750681","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750681","url":null,"abstract":"The design of a reliable protection scheme for micro-grids often requires communication between protective devices and microgrid controllers. These communication assisted schemes must be validated in real time with cyber physical co-simulation for successful demonstration. The paper presents such a co-simulation platform between a simulated power system model using RTDS and physical protective devices. The authors have developed a scalable protection scheme with a self healing feature to protect a microgrid with 100% Inverter Based Resources (IBRs). The primary protection of the scheme is programmed in SEL 421–7 relay and backup protection is programmed in MATLAB on a generic computer acting as a microgrid controller. IEC 61850 models are used to communicate between SEL-421 relay and RTDS, TCP/IP communication connects the microgrid controller to RTDS. The paper's focus is to demonstrate the co-simulation platform with real communication links established using both communication protocols. The paper shows the configuration of the IEC 61850 and TCP/IP communications as the interface requires proper hardware and software setup. The real time performance on IEEE 123 node distribution feeder indicates the Hardware In the Loop (HIL) framework as a competent testing environment for the developed protection scheme for microgrids.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132609513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Superimposed Sequence Components for Microgrid Protection: A Review 微电网保护的叠加序列分量研究进展

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750756

Kwasi Opoku, Subash Pokharel, A. Dimitrovski

{"title":"Superimposed Sequence Components for Microgrid Protection: A Review","authors":"Kwasi Opoku, Subash Pokharel, A. Dimitrovski","doi":"10.1109/TPEC54980.2022.9750756","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750756","url":null,"abstract":"The new challenge to protective relaying in distribution networks (DNs), due to the integration of distributed generation (DG), has become a significant area of focus and research for power engineers. To achieve high penetration of DGs in the DNs, new methods of achieving desired sensitivity, selectivity, and security of fault detection and coordination must be adopted. Recent literature shows that superimposed sequence components offer great potential in fault detection and coordination in such DNs. This paper reviews different proposed solutions to fault detection and coordination in microgrids using superimposed sequence quantities. It also includes a discussion on their application methods, unique advantages, and limitations. This way, it contributes to existing reviews on microgrid protection by presenting the unique considerations necessary for the superimposed method, as well the way conventional protection schemes can be improved for microgrid protection using this method. Results from applying a new approach for detecting faults based on superimposed negative sequence admittance is presented to demonstrate the application of superimposed quantities in fault detection.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123337991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Soft-Switching Single-Stage AC-DC Converter 一种软开关单级交流-直流变换器

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-18 DOI: 10.1109/TPEC54980.2022.9750818

Farid Naghavi, H. Toliyat

引用次数: 3

Exploring the use of Shapelets in Traveling Wave based Fault Detection in Distribution Systems 探索Shapelets在配电系统行波故障检测中的应用

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-01 DOI: 10.1109/TPEC54980.2022.9750728

M. Biswal, Shubhasmita Pati, S. Ranade, O. Lavrova, M. Reno

引用次数: 0

Data-Driven Detection of Phase Changes in Evolving Distribution Systems 数据驱动的配电系统相变检测

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-01 DOI: 10.1109/TPEC54980.2022.9750748

Bethany D. Peña, Logan Blakely, M. Reno

{"title":"Data-Driven Detection of Phase Changes in Evolving Distribution Systems","authors":"Bethany D. Peña, Logan Blakely, M. Reno","doi":"10.1109/TPEC54980.2022.9750748","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750748","url":null,"abstract":"The installation of digital sensors, such as advanced meter infrastructure (AMI) meters, has provided the means to implement a wide variety of techniques to increase visibility into the distribution system, including the ability to calibrate the utility models using data-driven algorithms. One challenge in maintaining accurate and up-to-date distribution system models is identifying changes and event occurrences that happen during the year, such as customers who have changed phases due to maintenance or other events. This work proposes a method for the detection of phase change events that utilizes techniques from an existing phase identification algorithm. This work utilizes an ensemble step to obtain predicted phases for windows of data, therefore allowing the predicted phase of customers to be observed over time. The proposed algorithm was tested on four utility datasets as well as a synthetic dataset. The synthetic tests showed the algorithm was capable of accurately detecting true phase change events while limiting the number of false-positive events flagged. In addition, the algorithm was able to identify possible phase change events on two real datasets.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126888912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Generating Connected, Simple, and Realistic Cyber Graphs for Smart Grids 生成连接的，简单的，和现实的网络图形智能电网

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-01-12 DOI: 10.1109/TPEC54980.2022.9750688

Osman Boyaci, M. Narimani, K. Davis, E. Serpedin

{"title":"Generating Connected, Simple, and Realistic Cyber Graphs for Smart Grids","authors":"Osman Boyaci, M. Narimani, K. Davis, E. Serpedin","doi":"10.1109/TPEC54980.2022.9750688","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750688","url":null,"abstract":"Smart grids integrate communication systems with power networks to enable power grids operation and command through real-time data collection and control signals. Designing, analyzing, and simulating smart grid infrastructures as well as predicting the impact of power network failures strongly depend on the topologies of the underlying power network and communication system. Despite the substantial impact that the communication systems bring to smart grid operation, the topology of communication systems employed in smart grids was less studied. The power community lacks realistic generative communication system models that can be calibrated to match real-world data. To address this issue, this paper proposes a framework to generate the underlying topological graphs for the communication systems deployed in smart grids by mimicking the topology of real-world smart grids. In this regard, we have updated the Chung-Lu algorithm to guarantee the communication network connectivity and to match the degree distribution of a real-world smart grid rather than the following an expected degree distribution. In addition, key characteristics of communication systems such as diameter, average shortest paths, clustering coefficients, assortativity, and spectral gap were taken into consideration to generate the most similar real-world communication network for smart grid studies. We believe that the proposed algorithm to generate realistic cyber graphs for smart grid studies will benefit the power community.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Flood-aware Optimal Power Flow for Proactive Day-ahead Transmission Substation Hardening 主动日前变电所加固的洪水感知最优潮流

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-01-10 DOI: 10.1109/TPEC54980.2022.9750830

Mohadese Movahednia, Amin Kargarian Marvasti

引用次数: 3

Hybrid Quantum-Classical Unit Commitment 混合量子-经典单位承诺

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-01-07 DOI: 10.1109/TPEC54980.2022.9750763

Reza Mahroo, A. Kargarian

引用次数: 9

Explainable Signature-based Machine Learning Approach for Identification of Faults in Grid-Connected Photovoltaic Systems 基于可解释签名的并网光伏系统故障识别机器学习方法

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2021-12-25 DOI: 10.1109/TPEC54980.2022.9750761

S. Wali, I. Khan

{"title":"Explainable Signature-based Machine Learning Approach for Identification of Faults in Grid-Connected Photovoltaic Systems","authors":"S. Wali, I. Khan","doi":"10.1109/TPEC54980.2022.9750761","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750761","url":null,"abstract":"Transformation of conventional power networks into smart grids with the heavy penetration level of renewable energy resources, particularly grid-connected Photovoltaic (PV) systems, has increased the need for efficient fault identification systems. Malfunctioning any single component in grid-connected PV systems may lead to grid instability and other serious consequences, showing that a reliable fault identification system is the utmost requirement for ensuring operational integrity. Therefore, this paper presents a novel fault identification approach based on statistical signatures of PV operational states. These signatures are unique because each fault has a different nature and distinctive impact on the electrical system. Thus, the Random Forest Classifier trained on these extracted signatures showed 100% accuracy in identifying all types of faults. Furthermore, the performance comparison of the proposed framework with other Machine Learning classifiers depicts its credibility. Moreover, to elevate user trust in the predicted outcomes, SHAP (Shapley Additive Explanation) was utilized during the training phase to extract a complete model response (global explanation). This extracted global explanation can help in the assessment of predicted outcomes' credibility by decoding each prediction in terms of features contribution. Hence, the proposed explainable signature-based fault identification technique is highly credible and fulfills all the requirements of smart grids.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124543786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3