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Implementing Online Oscillation Monitoring and Forced Oscillation Source Locating at Peak Reliability 实现在线振荡监测和峰值可靠性强制振荡源定位
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000376
Hongming Zhang, Jiawei Ning, Haoyu Yuan, V. Venkatasubramanian
{"title":"Implementing Online Oscillation Monitoring and Forced Oscillation Source Locating at Peak Reliability","authors":"Hongming Zhang, Jiawei Ning, Haoyu Yuan, V. Venkatasubramanian","doi":"10.1109/NAPS46351.2019.9000376","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000376","url":null,"abstract":"This paper introduces a framework of online oscillation monitoring systems and forced oscillation detection & source location tools that Peak Reliability (“PEAK”) has implemented for the Reliability Coordinator (RC) function of the Western Interconnection. The framework consists of four main components: (1) Montana Tech's Modal Analysis Software (MAS) engine; (2) Washington State University's Oscillation Monitor System (OMS) software; (3) Forced Oscillation Detection and Source Location Algorithms (FODSL); and (4) PEAK in-house visualization tool and alarming logic built in PI Processbook. The framework has been validated and applied for real system oscillation studies successfully. Implementation experience and lessons learned will be discussed in the paper.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128879040","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: 6
Resilient and Extreme-Event-Aware Microgrid Using Energy Storage and Load Curtailment 基于储能和负荷缩减的弹性和极端事件感知微电网
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000242
Farshina Nazrul Shimim, M. Bahramipanah, H. Nehrir
{"title":"Resilient and Extreme-Event-Aware Microgrid Using Energy Storage and Load Curtailment","authors":"Farshina Nazrul Shimim, M. Bahramipanah, H. Nehrir","doi":"10.1109/NAPS46351.2019.9000242","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000242","url":null,"abstract":"Extreme events such as hurricane, earthquake, flooding, and cyber-attacks can result in power system blackout. Due to the high cost of power outage, appropriate planning, scheduling and preventive strategies should be considered to improve the resiliency of the power system. The optimal resource allocation in an area with high risk of extreme events occurrence is quite challenging. In this paper, a novel method is presented to improve the grid resiliency, from electrical point of view, in case of an extreme event with an emphasis on grid preparation. A multi-objective planning & control strategy is proposed at the pre-event stage. The proposed approach includes microgrid islanding, generation regulation, and load curtailment. Energy Storage Systems are considered as alternative resources in case of occurrence of extreme events. The effectiveness of the proposed method is assessed and compared to the equivalent conventional control scheme using a test case composed by the IEEE 13-bus distribution test feeders suitably adapted to include stochastic generation and energy storage systems. It is shown that our proposed strategy is able to cover the critical loads in all the 24-hour simulation study.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124418633","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
Feeder Level Linear Voltage Drop Model for Active Radial Distribution System Operation in the Presence of Distributed Generation 有分布式发电时主动径向配电系统的馈线级线性电压降模型
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000390
Aasheesh Deshmukh, Md Rakib Ur Rahman, V. Aravinthan
{"title":"Feeder Level Linear Voltage Drop Model for Active Radial Distribution System Operation in the Presence of Distributed Generation","authors":"Aasheesh Deshmukh, Md Rakib Ur Rahman, V. Aravinthan","doi":"10.1109/NAPS46351.2019.9000390","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000390","url":null,"abstract":"In active distribution system, distributed generators require voltage drop management and power loss minimization. This paper proposes a voltage drop model and optimal management model for voltage drop and power loss including distributed generation (DG). The main focus of this work is to create a linear relationship between voltage drop and apparent power in the presence of DG. This is used to minimize voltage drop and power loss for a radial distribution feeder using minimization technique which comprises of DG real and reactive power control. Numerical analysis was done using IEEE 13 node test feeder system. Successful working of proposed model and minimization of line voltage drop, real and reactive power losses is demonstrated in this paper.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115225236","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
Event Classification in Distribution Networks Using a Quotient Gradient System 基于商梯度系统的配电网事件分类
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.8999976
H. Khodabandehlou, I. Niazazari, H. Livani, M. S. Fadali
{"title":"Event Classification in Distribution Networks Using a Quotient Gradient System","authors":"H. Khodabandehlou, I. Niazazari, H. Livani, M. S. Fadali","doi":"10.1109/NAPS46351.2019.8999976","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.8999976","url":null,"abstract":"The classification of events or sudden changes in power networks versus normal abrupt changes or switching actions is essential to take appropriate maintenance actions that guarantee the quality of power delivery. This issue has increased in importance and complexity with the proliferation of volatile resources that introduce variability, uncertainty, and intermittency in network behavior, observed as variations in voltage and current phasors. This paper proposes using a quotient gradient system (QGS) to train a two-stage partially recurrent neural network to improve event classification rate in power distribution networks using high-fidelity data from micro-phasor measurement units (µPMUs). QGS is a systematic approach to finding solutions of constraint satisfaction problems. We transform the µPMUs data from the power network into a constraint satisfaction problem and use QGS to train a neural network by solving the resulting optimization problem. Simulation results show that the proposed supervised classification method can reliably distinguish between different events in power distribution networks. Comparison with other neural network classifiers shows that QGS trained networks provide significantly better classification. Sensitivity analysis is performed concerning the number of µPMUs, reporting rates, noise level and early versus late data stream fusion frameworks.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766206","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
Small-scale Microgrid Energy Market Based on PILT-DAO 基于PILT-DAO的小型微电网能源市场
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000399
Tianlu Gao, Wei Gao, J. Zhang, Wenzhong Gao
{"title":"Small-scale Microgrid Energy Market Based on PILT-DAO","authors":"Tianlu Gao, Wei Gao, J. Zhang, Wenzhong Gao","doi":"10.1109/NAPS46351.2019.9000399","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000399","url":null,"abstract":"The energy market of DERs in Microgrids (MGs) is still under devolvement due to low security and transparency at present. Therefore, a small-scale microgrid energy market is proposed in this study based on Decentralized Autonomous Organization of Parallel, Integrity, Longevity, and Transparency (PILT-DAO) based on the features of the blockchain. A buyer or seller at the microgrid level can complete the transaction matching in the PILT-DAO market. In order to implement this energy trading platform, the first step is to simulate a modified distributed IEEE 13 node test feeders system. The next step is to develop a price mechanism based on a consensus + innovation distributed algorithm to calculate the Distribution Locational Marginal Price (DLMP). In the meantime, smart meters record the Power Flow (PF) data of each DG as one node of the whole simulated distribution power system and send them to blockchain including distributed price and power generation data. The third step is to constitute a decentralized autonomous market by programming smart contracts in Ethereum DAO, running in an artificial system parallelly. A case study of a small-scale microgrid energy market based on PILT-DAO is illustrated followed by the conclusion.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115843776","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: 5
A Diversity-Based Clustering Technique For Implementing Decentralized Node Level Charge Scheduling Of Electric Vehicles 基于多样性的聚类技术实现分散节点级电动汽车充电调度
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000199
Chak Lam Shek, Arun-Kaarthick Manoharan, Srikanth Gampa, T. Chandrappa, V. Aravinthan
{"title":"A Diversity-Based Clustering Technique For Implementing Decentralized Node Level Charge Scheduling Of Electric Vehicles","authors":"Chak Lam Shek, Arun-Kaarthick Manoharan, Srikanth Gampa, T. Chandrappa, V. Aravinthan","doi":"10.1109/NAPS46351.2019.9000199","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000199","url":null,"abstract":"The number of Electric Vehicles in usage has been increasing and this trend creates a lot of challenges to the existing power grid. The advancements in the communication and control infrastructure have made applications such as real time charge scheduling of the Electric Vehicles possible. The main issue in case of Electric Vehicle charge scheduling is the scalability and the uncertainty concerning the customer charging patterns. In this work, a decentralized node level clustering technique based on customers charging pattern has been developed. An Integer Linear programming scheme is used to schedule the Electric Vehicles in each group separately. The detailed study of the effectiveness of the method developed is also presented in the paper.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126890145","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
Physics-Guided Deep Learning for Time-Series State Estimation Against False Data Injection Attacks 针对假数据注入攻击的时间序列状态估计的物理引导深度学习
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000305
Lei Wang, Qun Zhou
{"title":"Physics-Guided Deep Learning for Time-Series State Estimation Against False Data Injection Attacks","authors":"Lei Wang, Qun Zhou","doi":"10.1109/NAPS46351.2019.9000305","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000305","url":null,"abstract":"The modern power grid is a cyber-physical system. While the grid is becoming more intelligent with emerging sensing and communication techniques, new vulnerabilities are introduced and cyber security becomes a major concern. One type of cyber-attacks - False Data Injection Attacks (FDIAs) - exploits the limitations in traditional power system state estimation, and modifies system states without being detected. In this paper, we propose a physics-guided deep learning (PGDL) approach to defend against FDIAs. The PGDL takes real-time measurements as inputs to neural networks, outputs the estimated states, and reconstructs measurements considering power system physics. A deep recurrent neural network - Long Short-Term Memory (LSTM) - is employed to learn the temporal correlations among states. This hybrid learning model leads to a time-series state estimation method to defend against FDIAs. The simulation results using IEEE 14-bus test system demonstrate the accuracy and robustness of the proposed time-series state estimation under FDIAs.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127014393","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: 5
Realization of Enhanced Phase Locked Loop using Raspberry Pi and LabVIEW 用树莓派和LabVIEW实现增强型锁相环
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000278
R. Kolla, Zhengyu Wang, Zhixin Miao, Lingling Fan
{"title":"Realization of Enhanced Phase Locked Loop using Raspberry Pi and LabVIEW","authors":"R. Kolla, Zhengyu Wang, Zhixin Miao, Lingling Fan","doi":"10.1109/NAPS46351.2019.9000278","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000278","url":null,"abstract":"Real-time data is gaining more importance in engineering. With archived data and the real-time data, utilities are making systems more robust by developing new methods for controlling and monitoring. Frequency information of the system is one of the key factors for better controlling and monitoring purpose. Acquiring real-time frequency information at a low cost is of timely important. This paper presents Raspberry Pi based data acquisition for frequency measurement through enhanced Phase-Locked-Loop (PLL). This paper discusses elements: (i) The complete procedure for acquiring the real-time data using Raspberry Pi, Multi-chip package (MCP) 3008 and LabVIEW. (ii) Modeling of Enhanced PLL with the data acquisition system for processing the real-time data to extract the frequency and amplitude information.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123276151","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
Quasi-Dynamic Domain Modeling of Line-Commutated Converters with the Analytical Approach 用解析法进行线换相变换器的准动态域建模
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.8999985
Kaiyu Liu, A. Meliopoulos, Boqi Xie, Chiyang Zhong, Jiahao Xie
{"title":"Quasi-Dynamic Domain Modeling of Line-Commutated Converters with the Analytical Approach","authors":"Kaiyu Liu, A. Meliopoulos, Boqi Xie, Chiyang Zhong, Jiahao Xie","doi":"10.1109/NAPS46351.2019.8999985","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.8999985","url":null,"abstract":"Line-commutated converters (LCCs) are significant components of conventional high-voltage direct current (HVDC) transmission systems and distributed energy resources. Various simulation methods have been developed to model LCCs under different operational conditions. To alleviate the computational burden and realize real-time simulation, the dynamic phasor model based on generalized averaging method was established for LCCs. However, the complexity of the analytical switching function limits the flexibility of utilizing the model in different situation and there is room for improvement on accuracy. This paper derives a more accurate expression for current switching function and a more extensive expression for voltage switching function for LCC modeling. The model is developed in quasi-dynamic domain and is transformed into an algebraic quadratic companion form. A simple example system is utilized to show the accuracy of the model and a large example system is utilized to demonstrate the performance of the model under transient conditions.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126577182","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
Short-term Load Forecasting on Smart Meter via Deep Learning 基于深度学习的智能电表短期负荷预测
2019 North American Power Symposium (NAPS) Pub Date : 2019-10-01 DOI: 10.1109/NAPS46351.2019.9000185
Ishan Khatri, Xishuang Dong, J. Attia, Lijun Qian
{"title":"Short-term Load Forecasting on Smart Meter via Deep Learning","authors":"Ishan Khatri, Xishuang Dong, J. Attia, Lijun Qian","doi":"10.1109/NAPS46351.2019.9000185","DOIUrl":"https://doi.org/10.1109/NAPS46351.2019.9000185","url":null,"abstract":"Smart metering has grabbed significant attention in recent years, particularly for the utility providers who plan the energy resources and take control actions to balance the electricity demand and supply by load forecasting. Currently, load forecasting is performed at the aggregated level, not at an individual level because it is highly uncertain and complex. Specifically, the performance of short-term forecasting is affected significantly by the variance of load uncertainty. Moreover, limited work has been done to help users choose the optimal usage plan. In this paper, we evaluate several deep learning models for load forecasting. In addition, we employ deep learning techniques to provide the optimal power plan for users based on their power usage. Experimental results using the data from the Irish Social Science Data Archive demonstrate the effectiveness of the proposed schemes.","PeriodicalId":175719,"journal":{"name":"2019 North American Power Symposium (NAPS)","volume":"1172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126725088","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
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