2022 IEEE Texas Power and Energy Conference (TPEC)最新文献_第2页

Power flow coordination among Smart Migrogrids: A Game Theory Approach 智能微电网的潮流协调:一种博弈论方法

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750814

R. Lahon, C. P. Gupta, E. Fernandez

{"title":"Power flow coordination among Smart Migrogrids: A Game Theory Approach","authors":"R. Lahon, C. P. Gupta, E. Fernandez","doi":"10.1109/TPEC54980.2022.9750814","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750814","url":null,"abstract":"Rapidly increasing levels of variable renewable energy sources in several power systems across the globe has led to a paradigm shift in electric power systems; prompting questions about how energy systems will be operated and managed when variable renewables become the dominant technology. As building blocks of smart grids, microgrids are anticipated to become an indispensable component in this transition. In view of this, this paper proposes a new power flow management strategy for interconnected smart microgrids in a distribution network. The developed approach aims at utilizing the spatiotemporal diversity in resource availability and consumer demands in geo-distributed microgrids through optimal power sharing among them, thus lessening the ‘brown’ energy purchases from the grid. At the lower level, microgrids are modelled as autonomous units with individual objectives while at the upper level, the concept of cooperative game-theory using Nash bargaining solution is applied to coordinate power flows among the participating microgrids. Finally, we highlight the implications of the proposed power flow management strategy through several simulation studies on the modified IEEE 33-bus distribution system with five microgrids.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"103 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":"129997654","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

Hardware-Based Randomized Encoding for Sensor Authentication in Power Grid SCADA Systems 电网SCADA系统中传感器认证的硬件随机编码

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750706

Kevin Hutto, S. Grijalva, V. Mooney

引用次数: 1

Situational Awareness for Reactive Power Management in Large-Scale Electric Grids 大型电网无功管理的态势感知

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750774

Jessica L. Wert, J. Yeo, F. Safdarian, T. Overbye

引用次数: 2

Optimal Protection Coordination of Islanded Microgrids Utilizing an Adaptive Virtual Impedance Fault Current Limiter 基于自适应虚拟阻抗故障限流器的孤岛微电网优化保护协调

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750766

T. Sati, M. Azzouz, M. Shaaban

{"title":"Optimal Protection Coordination of Islanded Microgrids Utilizing an Adaptive Virtual Impedance Fault Current Limiter","authors":"T. Sati, M. Azzouz, M. Shaaban","doi":"10.1109/TPEC54980.2022.9750766","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750766","url":null,"abstract":"Inverter-interfaced distributed generators (IIDGs) have limited fault current contributions compared to those of synchronous-based DGs. These low fault currents impose challenges on microgrid protection. This paper proposes a sensitive protection scheme for islanded microgrids that adopt droop-based IIDGs as the primary power source. Virtual impedance-fault current limiters (VI-FCLs) are employed in the inverter control scheme to limit IIDGs fault currents and protect inverter switches from overcurrent. The VI-FCLs are adapted to provide sensible fault currents. A two-stage optimization method is proposed to achieve optimal protection coordination (OPC) of directional overcurrent relays (DOCRs). Stage I is devoted to short-circuit currents calculation while involving different adaptive VI-FCL characteristics. In Stage II, the OPC problem is formulated as a nonlinear programming problem to obtain the minimum relays' total operating time while satisfying protection coordination constraints and solved to obtain the optimal DOCRs set groups. The performance of the proposed protection scheme is tested on a radial microgrid. The results confirm that the proposed protection scheme successfully maintains protection coordination using a single set group for a range of fault resistances.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"38 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":"129085715","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

Power System Sparse Matrix Statistics 电力系统稀疏矩阵统计

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750777

F. Safdarian, Z. Mao, W. Jang, T. Overbye

引用次数: 1

Wind Turbine Fault Detection Based On Nonlinear Observer 基于非线性观测器的风电机组故障检测

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750800

Ichrak Eben Zaid, Moez Boussada, A. S. Nouri

{"title":"Wind Turbine Fault Detection Based On Nonlinear Observer","authors":"Ichrak Eben Zaid, Moez Boussada, A. S. Nouri","doi":"10.1109/TPEC54980.2022.9750800","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750800","url":null,"abstract":"This paper deals with fault detection strategy used to ensure wind turbine reliability. Based on unknown iput nonlinear observer, the proposed approach have to estimate not only the full system state but also some actuator faults that can be considered as unknown inputs. Compared to some usually used algorithms, this method is caracterized by calculation time earn as well as development effort and accuracy which makes it useful for online implementation even for fast process. Used for linear systems, such approaches demonstrated interesting performances and results. The problem becomes harder for nonlinear systems where models are characterized by complex and coupled behaviors. More over, faults have to be detected as earlier as possible to avoid catastrophic and irreversible damages. In this work, fault detection algorithm based on unknown input high gain observer is proposed for a class of nonlinear systems site of actuator devations. Applied to a simulated wind turbine plant to reconstruct faults altering the electromechanical torque subpart, the results confirmed the accuracy and time convergence performances of the proposed observer which make it an intersting candidate to an online implementation.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"115 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":"132569499","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: 0

A Likelihood-Partitioned Bayesian Framework for Lithium Sulfur Battery State Discharging of Charge Estimation 锂硫电池放电状态估计的似然分割贝叶斯框架

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750711

Srinivasan Munisamy

{"title":"A Likelihood-Partitioned Bayesian Framework for Lithium Sulfur Battery State Discharging of Charge Estimation","authors":"Srinivasan Munisamy","doi":"10.1109/TPEC54980.2022.9750711","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750711","url":null,"abstract":"Lithium sulfur (Li-S) batteries are promising energy storage devices and alternative to lithium-Ion (Li-Ion) batteries in electric grid and vehicle applications. However, compared to Li-Ion, the discharge voltage of Li-S is much complex and nonlinear. This results a challenging state of charge (SoC) estimation problem while Li-S is discharging. For such a problem, the traditional extended Kalman filter fails to provide accurate SoC. Therefore, this paper proposes a novel likelihood partitioned Bayesian filtering (LPBF) framework and its linearized version for SoC estimation of discharging Li-S battery cell. Though both traditional EKF and linearized LPBF use a prediction error minimization based equivalent circuit network (ECN) parameterization, the LPBF uses a partitioned ECN parameterization. The portioned models result two likelihoods, whereas the EKF uses a single state-space model throughout discharge from 100 percent SoC to zero SoC. With experiment data obtained at two different temperature conditions, numerical simulation results compare both EKF and linearized LPBF based SoC estimators. Simulation results show that the LPBF's accuracy is impressive, about 97 percent, for considered dynamic load current, operating temperature and uncertain initial SoC conditions.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"21 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":"128447715","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: 0

On the Impacts of Different Consistency Constraint Formulations for Distributed Optimal Power Flow 不同一致性约束公式对分布式最优潮流的影响

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750783

Rachel Harris, Mohannad Alkhraijah, David Huggins, D. Molzahn

{"title":"On the Impacts of Different Consistency Constraint Formulations for Distributed Optimal Power Flow","authors":"Rachel Harris, Mohannad Alkhraijah, David Huggins, D. Molzahn","doi":"10.1109/TPEC54980.2022.9750783","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750783","url":null,"abstract":"The optimal power flow (OPF) problem finds the least costly operating point which meets the power grid's operational limits and obeys physical power flow laws. Complementing today's centralized optimization paradigm, future power grids may rely on distributed optimization where multiple agents work together to determine an acceptable operating point. In distributed algorithms, local agents solve subproblems to optimize their region of the system and share data to achieve consistency with their neighboring agents' subproblems. This paper investigates how different methods of enforcing power flow consistency constraints between local areas in distributed optimal power flow impact convergence rate and a classifier's ability to detect malicious cyberattack. The distributed OPF problem is solved with the alternating direction method of multipliers (ADMM) algorithm. First, the ADMM algorithm's convergence rate is compared for three different consistency constraint formulations. Next, the paper considers a cyberattack in which the integrity of information shared between agents is compromised, causing the algorithm to exhibit unacceptable behavior. A support vector machine (SVM) classifier is trained to detect the presence of manipulated data from such cyberattacks. Results demonstrate that consistency constraint formulation impacts the classifier's detection performance; for certain formulations, detection is highly accurate.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"3 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":"126893319","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

Torque Ripple Minimization using an Artificial Neural Network based Speed Sensor less control of SVM-DTC fed PMSM Drive 基于人工神经网络无速度传感器的SVM-DTC永磁同步电机转矩脉动最小化控制

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750850

S. K. Kakodia, D. Giribabu, R. Ravula

{"title":"Torque Ripple Minimization using an Artificial Neural Network based Speed Sensor less control of SVM-DTC fed PMSM Drive","authors":"S. K. Kakodia, D. Giribabu, R. Ravula","doi":"10.1109/TPEC54980.2022.9750850","DOIUrl":"https://doi.org/10.1109/TPEC54980.2022.9750850","url":null,"abstract":"In this paper, an artificial neural network (ANN) controller based position sensorless control of permanent magnet synchronous motor (PMSM) using Space vector modulation-Direct torque control (SVM-DTC) for variable speed drive has been presented. The SVM-DTC require the initial position of the rotor during the starting of the PMSM drive. The installation of the shaft-mounted position sensor requires additional space, assembly, wiring circuit, and is fragile component. The speed sensor-less control of PMSM enhances the performance of drives in harsh environments and reduces the overall cost of the drive and improve mechanical reliability. The speed estimation requires the knowledge of drive parameters, the model-based speed control technique is suitable for low and medium-speed motor drive applications without knowing the exact parameter of the PMSM drive. The Rotor Flux based Model Reference adaptive system (RF-MRAS) is used for a wide speed operation and estimates rotor angle in dynamic conditions. The presence of an integrator in the voltage model of RF-MRAS affects the low speed performance of the drive, therefore to improve the speed response at low speed, the ANN controller is used to replace the Proportional-Integral (PI) controller, which is employed in the adaptive model of the speed observer. The performance of the control scheme is simulated at variable speed and load conditions with the help of the OPAL-RT 4500 simulation platform.","PeriodicalId":185211,"journal":{"name":"2022 IEEE Texas Power and Energy Conference (TPEC)","volume":"17 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":"116853932","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: 4

Optimal Planning of Smart Charging Facilities using Grey Wolf Optimizer 基于灰狼优化器的智能充电设施优化规划

2022 IEEE Texas Power and Energy Conference (TPEC) Pub Date : 2022-02-28 DOI: 10.1109/TPEC54980.2022.9750837

Preetham Goli, Srikanth Yelem, Saad Muaddi, S. Gampa, W. Shireen

引用次数: 2