2020 IEEE Electric Power and Energy Conference (EPEC)最新文献

Event Tree Reliability Analysis of Electrical Power Generation Network using Formal Techniques 基于形式化技术的发电网络事件树可靠性分析

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320092

M. Abdelghany, Waqar Ahmad, S. Tahar

{"title":"Event Tree Reliability Analysis of Electrical Power Generation Network using Formal Techniques","authors":"M. Abdelghany, Waqar Ahmad, S. Tahar","doi":"10.1109/EPEC48502.2020.9320092","DOIUrl":"https://doi.org/10.1109/EPEC48502.2020.9320092","url":null,"abstract":"In recent years, there has been a significant proliferation in the use of Renewable Energy Sources (RES), such as wind/solar systems, for power generation. However, the main obstacle that these resources face is their intermittent nature, which greatly affects their ability to deliver constant power to the power network. This raises several reliability-related concerns and existing sampling-based simulation tools, such as the Monte-Carlo approach, cannot guarantee absolute accuracy of the reliability analysis results due to their inherent incompleteness. In this paper, we propose to use formal techniques based on theorem proving to conduct the reliability analysis of electric grids as an accurate alternate approach. In particular, we use the HOL4 theorem prover, which is a computer-based mathematical reasoning tool. We demonstrate the effectiveness of our proposed approach by analyzing the reliability of the IEEE 39-bus power grid incorporating RES power plants and and also determine its reliability indices, such as System Average Interruption Frequency and Duration ($mathcal{S}mathcal{A}mathcal{I}mathcal{F}mathcal{I}$ and $mathcal{S}mathcal{A}mathcal{I}mathcal{D}mathcal{I}$). To assess the accuracy of our proposed approach, we compare our results with the commercial reliability analysis tool Isograph and the MATLAB toolbox based on Monte-Carlo approach.","PeriodicalId":236395,"journal":{"name":"2020 IEEE Electric Power and Energy Conference (EPEC)","volume":"78 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121014045","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

GridKG: Knowledge Graph Representation of Distribution Grid Data GridKG:配电网格数据的知识图表示

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320066

Yashar Kor, Liang Tan, M. Reformat, P. Musílek

引用次数: 1

Review of Studies and Operational Experiences of PV Hosting Capacity Improvement by Smart Inverters 智能逆变器提高光伏主机容量的研究与运行经验综述

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320116

R. Varma, Vatandeep Singh

引用次数: 5

Self-Secure Inverters Against Malicious Setpoints 针对恶意设定值的自安全逆变器

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320022

Tareq Hossen, F. Sadeque, Mehmetcan Gursoy, B. Mirafzal

{"title":"Self-Secure Inverters Against Malicious Setpoints","authors":"Tareq Hossen, F. Sadeque, Mehmetcan Gursoy, B. Mirafzal","doi":"10.1109/EPEC48502.2020.9320022","DOIUrl":"https://doi.org/10.1109/EPEC48502.2020.9320022","url":null,"abstract":"The next generation of grid-interactive inverters is a cyber-physical device, which can receive setpoints in real-time from a utility operator or a third-party aggregator. This feature enhances the controllability of grid-interactive inverters to provide services beyond just pumping power to the grid. Being a cyber-physical device makes an inverter vulnerable to cyberattacks. In this paper, a model/knowledge-based technique is proposed for developing self-secure smart inverters. The reference model/knowledge is built based on the normal operating region of the inverter and its reduced-order dynamic model. The inverter can autonomously examine the incoming setpoints before engaging them to the local controller. The inverter must learn about the input and output circuits to determine its normal operating region through estimating system parameters. The estimation of the grid parameters is accomplished by injecting current at a different frequency than the power frequency. In this paper, the feasibility of realizing self-secure inverters is examined using a laboratory setup including a Powerflex 755 three-phase inverter and a 12 kW NHR 9410 power grid emulator. The results confirm that inverters can be programmed to autonomously accept or reject the incoming commands and protect themselves from malicious setpoints.","PeriodicalId":236395,"journal":{"name":"2020 IEEE Electric Power and Energy Conference (EPEC)","volume":"177 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544488","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: 11

Review of Protection Strategies for Wind Turbines Against Lightning 风力发电机雷电防护策略综述

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320037

Choudhury Naser Alam, V. Sood

引用次数: 0

Adaptive Capacity Determination for Critical Load in Power Systems 电力系统临界负荷的自适应容量确定

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320115

Hanyue Li, Jessica L. Wert, P. Cicilio

引用次数: 1

Robust Integral Sliding Mode Control of Non-minimum Phase DC-DC Converters 非最小相位DC-DC变换器的鲁棒积分滑模控制

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320126

Youssef El Haj, A. Sheir, R. Milman, V. Sood

{"title":"Robust Integral Sliding Mode Control of Non-minimum Phase DC-DC Converters","authors":"Youssef El Haj, A. Sheir, R. Milman, V. Sood","doi":"10.1109/EPEC48502.2020.9320126","DOIUrl":"https://doi.org/10.1109/EPEC48502.2020.9320126","url":null,"abstract":"In this paper, a modified integral sliding mode controller (ISMC) is proposed for non-minimum phase dc-dc converters. A boost dc-dc converter operating in continuous conduction mode (CCM) is chosen as a representative case study. The converter’s bilinear model and its effect on the controller design necessitate the need for a nonlinear controller. Unlike a recently introduced ISMC, the proposed controller does not need a priori knowledge of initial conditions such as inductor current or capacitor voltage, nor does it implement a sign function to ensure a fast response or reachability. A novel modified sliding surface which ensures reachability, stability and reduces chattering at the steady-state operation point is proposed. Moreover, the proposed controller in conjunction with a disturbance observer (DO) enables the converter to maintain stable operation under disturbances and uncertainties. The system’s robustness against drastic, discontinuous, autonomous, or non-zero derivative disturbances are enhanced by including an invariant saturation function. The performance of the proposed ISMC is tested and compared with a well-established linear controller to prove its validity under different types and levels of disturbances and uncertainties.","PeriodicalId":236395,"journal":{"name":"2020 IEEE Electric Power and Energy Conference (EPEC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114834950","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

A CPFL Energia Fraud Detection Model Based on Geographic Census Sectors Analysis 基于地理普查部门分析的CPFL能源欺诈检测模型

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320023

Flávio Alceu, Lídia Gusmão, Douglas Akassaka, Hugo Helito

{"title":"A CPFL Energia Fraud Detection Model Based on Geographic Census Sectors Analysis","authors":"Flávio Alceu, Lídia Gusmão, Douglas Akassaka, Hugo Helito","doi":"10.1109/EPEC48502.2020.9320023","DOIUrl":"https://doi.org/10.1109/EPEC48502.2020.9320023","url":null,"abstract":"Non-technical losses and irregular energy consumption severely jeopardize distribution utilities, and customers in general. Therefore, reducing them and pursuing revenue recovery stand for a crucial mechanism to secure companies financial health and quality in provided services. In such context, this work incorporates socioeconomic variables from demographic census into fraud detection models to improve the existing algorithms and enhance their performance. The inclusion of geographically sectioned explanatory characteristics reduces the existing models bias, preventing that only vulnerable areas are addressed in inspections, whereas others are unwisely left out. In order to achieve so, demographic census data are combined with historical inspection results and myriad predictive modeling tools to evaluate sectors fraud scores–i.e., the likeliness that an inspection will lead to the identification of a fraud within a given sector–and point out areas to which more inspections should be directed. The final proposed methodology applies Linear Regression, Spatial Auto-regressive Models, Geographically Weighted Regression and Logistic Regression techniques and the inclusion of sectors fraud scores has increased model accuracy to 72% (a 3 percentage points growth), improving success rates for fraud detection.","PeriodicalId":236395,"journal":{"name":"2020 IEEE Electric Power and Energy Conference (EPEC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813769","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

Real-Time Monitoring Applications for the Power Grid under Geomagnetic Disturbances 地磁扰动下电网的实时监测应用

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9320114

C. Klauber, K. Shetye, Zeyu Mao, T. Overbye, J. Gannon, M. Henderson

引用次数: 1

Peak-Load Forecasting of Nova Scotia During Winter Using Support Vector Machine with Optimally Configured Hyperparameters 基于超参数优化配置支持向量机的新斯科舍省冬季峰值负荷预测

2020 IEEE Electric Power and Energy Conference (EPEC) Pub Date : 2020-11-09 DOI: 10.1109/EPEC48502.2020.9319923

Ali R. Al-Roomi, M. El-Hawary

引用次数: 0