2020 IEEE Kansas Power and Energy Conference (KPEC)最新文献_第2页

A Hybrid Electric Circuit Battery Model Capturing Dynamic Battery Characteristics 捕获动态电池特性的混合电路电池模型

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167659

Alamgir Ahmad Khattak, A. Khan, Muhammad Safdar, A. Basit, N. Zaffar

引用次数: 1

Adaptive Virtual Impedance Consensus Control for Reactive Power Sharing 无功共享的自适应虚拟阻抗一致性控制

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167609

Ahmed S. Alsafran, M. Daniels

引用次数: 2

A Non-Isolated High-Voltage-Gain DC-DC Converter with Modified Greinacher Voltage Multiplier in DCM 一种基于改进Greinacher电压乘法器的非隔离高压增益DC-DC变换器

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167595

Mohammad R. Altimania, Mohamad Saleh Sanjari Nia, M. Ferdowsi, P. Shamsi

引用次数: 5

Network Harmonic Impedance Derivation for Harmonic Filter Designing using Power Flow Program 基于潮流程序设计谐波滤波器的网络谐波阻抗推导

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167519

Nitish Sharma

引用次数: 0

A Hybrid Bayesian Ridge Regression-CWT-Catboost Model For PV Power Forecasting 用于光伏发电功率预测的混合贝叶斯岭回归- cwt - catboost模型

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167596

M. Massaoudi, S. Refaat, H. Abu-Rub, I. Chihi, Fakhreddine S. Wesleti

{"title":"A Hybrid Bayesian Ridge Regression-CWT-Catboost Model For PV Power Forecasting","authors":"M. Massaoudi, S. Refaat, H. Abu-Rub, I. Chihi, Fakhreddine S. Wesleti","doi":"10.1109/KPEC47870.2020.9167596","DOIUrl":"https://doi.org/10.1109/KPEC47870.2020.9167596","url":null,"abstract":"The forecasting of the high intermittency of Photovoltaic (PV) energy in smart grid is a persisting challenge. The proposed paper takes this challenge by presenting accurate forecasting techniques. PV power forecasting contributes to energy sector stability, controllability, and utilization through systematic monitoring for proper energy operation and optimization of grid-load balance. This paper addresses a novel paradigm that effectively copes with unpredictable extreme meteorological conditions. The proposed technique combines the Bayesian Ridge Regression (BRR) model, Continuous Wavelet Transform (CWT), and Gradient boosting with categorical features (Catboost). The architecture of the proposed model is based on the acquisition of features inputs, which sorts those features according to their importance. This ranking deploys a Bayesian Ridge Regression model to select the most relevant features. Then, the CWT decomposition technique converts the features chosen into a time-frequency domain. Catboost model generates the forecast output for one day ahead. The final results are deduced using inverse CWT. The Australian weather data have been used to evaluate the performance of the proposed technique on short short-term power forecasting for large-scale PV plants. The evaluation has been conducted using score metrics, visualization curves, and to-fold cross-validation. Simulation results are conducted to confirm the performance of the proposed technique.","PeriodicalId":308212,"journal":{"name":"2020 IEEE Kansas Power and Energy Conference (KPEC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115249533","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: 19

Aging Detection of Multiple Power Switches in a Live 3-Phase Inverter using Reflectometry 用反射法检测三相逆变器中多个电源开关的老化

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167565

Sourov Roy, A. Hanif, Faisal Khan

{"title":"Aging Detection of Multiple Power Switches in a Live 3-Phase Inverter using Reflectometry","authors":"Sourov Roy, A. Hanif, Faisal Khan","doi":"10.1109/KPEC47870.2020.9167565","DOIUrl":"https://doi.org/10.1109/KPEC47870.2020.9167565","url":null,"abstract":"Reflectometry-based degradation detection technique designed around spread spectrum time domain reflectometry (SSTDR) for multiple power semiconductor devices in a live 3-phase inverter has been proposed in this paper. Using SSTDR, aging-related impedance variation within the power semiconductor device can be identified without interrupting the circuit's normal operation. The rapid change in the SSTDR propagation path due to the high switching frequency of power switches makes real-time health monitoring challenging. Existing SSTDR based techniques proposed for degradation detection of the DC-DC converter and single-phase grid-tied H-bridge PV inverter require a large number of SSTDR test data acquisition to minimize the error caused by rapid change in the SSTDR propagation path. Moreover, a three-phase inverter may utilize a very complicated switching scheme and multiple impedance paths compared to the other converter topologies used in the previous SSTDR-based degradation detection technique. The proposed method requires significantly less amount of SSTDR data to successfully characterize the device aging by adopting a little modification in the inverter switching scheme. Included experimental results demonstrate that the proposed method can reduce the number of accessible nodes for performing the state of health (SOH) monitoring of all individual devices used in a three-phase inverter, which will eliminate the need for a separate SOH monitoring module for each device. In addition, due to SSTDR's ability to be embedded in the gate signal, the proposed technique can be integrated with the gate driver module, thus making it intelligent.","PeriodicalId":308212,"journal":{"name":"2020 IEEE Kansas Power and Energy Conference (KPEC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121704537","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

Multi-Agent based Control of a Microgrid Power System in Case of Cyber Intrusions 网络入侵下基于多智能体的微电网控制

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167631

H. Keshtkar, F. Mohammadi, J. Solanki, S. K. Solanki

引用次数: 2

Multi-Level Constant Current Based Fast Li-Ion Battery Charging Scheme With LMS Based Online State of Charge Estimation 基于LMS在线充电状态估计的多级恒流快速锂离子电池充电方案

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167541

R. Rai, Mihir Gaglani, Soumitra Das, T. Panigrahi

{"title":"Multi-Level Constant Current Based Fast Li-Ion Battery Charging Scheme With LMS Based Online State of Charge Estimation","authors":"R. Rai, Mihir Gaglani, Soumitra Das, T. Panigrahi","doi":"10.1109/KPEC47870.2020.9167541","DOIUrl":"https://doi.org/10.1109/KPEC47870.2020.9167541","url":null,"abstract":"Li-ion battery supports fast charging. However in conventional battery charging schemes, this fast charging capability is restricted by its terminal voltage during constant current charging profile. Furthermore conventional charging schemes neglect battery dynamics for an optimized charging protocol. This paper characterises Li-ion battery into its electrical equivalent circuit model. Additionally, based on the dynamics characterized through battery modelling a multi-level constant current charging protocol is adopted. This paper demonstrates a multi-level constant current charging scheme for faster battery charging with state of charge (SoC) estimation using least mean square (LMS) based algorithm. The implemented modified LMS algorithm with variable learning rate estimates the SoC of the battery accurately. The charging scheme approaches 100% SoC at a relatively higher charging current in comparison to the conventional battery charging schemes making the SoC estimation an important aspect for charge termination. The multi-level constant current charging scheme, inspired by the Taguchi optimization technique is implemented using a DC-DC buck converter as a variable current source. Experimental comparison between multi-level constant current and conventional charging scheme is performed. The hardware results showcase a reduction in charging time over conventional charging schema by 39.28%.","PeriodicalId":308212,"journal":{"name":"2020 IEEE Kansas Power and Energy Conference (KPEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134266843","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

Block-Phasor: A Decentralized Blockchain Framework to Enhance Security of Synchrophasor 块相量:一种增强同步相量安全性的去中心化区块链框架

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167676

Arpan Bhattacharjee, S. Badsha, A. Shahid, H. Livani, S. Sengupta

{"title":"Block-Phasor: A Decentralized Blockchain Framework to Enhance Security of Synchrophasor","authors":"Arpan Bhattacharjee, S. Badsha, A. Shahid, H. Livani, S. Sengupta","doi":"10.1109/KPEC47870.2020.9167676","DOIUrl":"https://doi.org/10.1109/KPEC47870.2020.9167676","url":null,"abstract":"The synchrophasor technology has been changing the wide-area monitoring system (WAMS) of power grids; as it facilitates real-time grid situational awareness, observability and state estimation, and online stability assessment. However, the measurement samples inside the substations, or in phasor data concentrators (PDCs) can become a target for cyber-attacks, such as false data injection and data tampering attacks. Moreover, the synchrophasors are vulnerable to a single point of failure. Blockchain, the main technology behind the bitcoin, can simultaneously ensure reliability, security, and integrity with decentralization properties in a peer-to-peer system. Therefore, to mitigate the issues in the synchrophasor network, in this paper, we propose a blockchain-based synchrophasor network protection framework to enhance the self-defensive capability of its monitoring system. Our proposed model can mitigate data manipulation attacks from malicious entities by introducing bloom filter based fast phasor data identity validation, and Merkle tree-based fast data verification. Finally, the blockchain consensus can help to keep the consistency in the system and eliminate malicious entities from manipulating the overall security of the protection framework. Our experimental results show that the proposed system is scalable and fast in terms of synchrophasor data verification.","PeriodicalId":308212,"journal":{"name":"2020 IEEE Kansas Power and Energy Conference (KPEC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132341507","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: 13

An Approach for Resilience Assessment of SIRES SIRES恢复力评估方法研究

2020 IEEE Kansas Power and Energy Conference (KPEC) Pub Date : 2020-07-01 DOI: 10.1109/KPEC47870.2020.9167559

Zeel Maheshwari, R. Ramakumar

引用次数: 2