Scalable Electric Power System Simulator

Ilić, Marija; Jaddivada, Rupamathi; Miao, Xiangshui

doi:10.1109/isgteurope.2018.8571428

Cited by 7 publications

(4 citation statements)

References 8 publications

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“…In this section, simulation studies on a 5-bus (two-area) test system (Fig.1) are carried out. The nonlinear system (4) including network dynamics is simulated using SEPSS at MIT [11]. The purpose are twofold: to show the importance of network dynamics in frequency regulation and to illustrate the effectiveness of the proposed E-AGC.…”

Section: Illustration Of the E-agc On A 5-bus Systemmentioning

confidence: 99%

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Enhanced Automatic Generation Control (E-AGC) for Electric Power Systems with Large Intermittent Renewable Energy Sources

Miao

Ilić

Liu

2019

2019 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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This paper is motivated by the need to enhance today's Automatic Generation Control (AGC) for ensuring high quality frequency response in the changing electric power systems. Renewable energy sources, if not controlled carefully, create persistent fast and often large oscillations in their electric power outputs. A sufficiently detailed dynamical model of the interconnected system which captures effects of fast nonlinear disturbances created by the renewable energy resources is derived for the first time. Consequently, the real power flow interarea oscillations, and the resulting frequency deviations are modeled. The modeling is multi-layered, and the dynamics of each layer (component level (generator); control area (control balancing authority), and the interconnected system) is expressed in terms of internal states and the interaction variables (IntV) between the layers and within the layers. E-AGC is then derived using this model to show how these interarea oscillations can be canceled. Simulation studies are carried out on a 5-bus system.

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Section: Illustration Of the E-agc On A 5-bus Systemmentioning

confidence: 99%

“…The authors greatly appreciate partial funding by NIST. Also, discussions with Ms. Rupamathi Jaddivada and the use of Scalable Electric Power System Simulator (SEPSS) at MIT[11] are greatly acknowledged.Accepted to the IEEE PES GM 2019. c 2019 IEEE.…”

mentioning

confidence: 99%

Enhanced Automatic Generation Control (E-AGC) for Electric Power Systems with Large Intermittent Renewable Energy Sources

Miao

Ilić

Liu

2019

2019 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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“…With the construction of a power supply company's power dispatching data network, the main station has been consecutively connected to all county dispatching services, resulting in further convergence and an increase in information flow in the main station, which puts considerable pressure on the dispatching data network and the main station dispatching automation system [19,20]. Due to access to county transfer automation business, the operation analysis report of power dispatch automation shows that many hidden defects are generated in the information flow, which is very difficult to trace and analyze due to the large amount of data and fast disappearance of information flow [21,22]. The dispatching automation system sometimes encounters the problem of misreporting or omitting information due to misdirected data from communication channels or plant and station general control equipment [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Identification over Power Big Data: Opportunities, Solutions, and Challenges

Luo¹,

Li²,

Yang³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry. However, with the convergence and increase in power data flow, the data dispatching network and the main station dispatching automation system have encountered substantial pressure. Therefore, the method of online data resolution and rapid problem identification of dispatching automation systems has been widely investigated. In this paper, we perform a comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification, discuss unresolved research issues and outline future directions in this area. In particular, we divide intelligent identification over power big data into data acquisition and storage processes, anomaly detection and fault discrimination processes, and fault tracing for dispatching operations during communication. A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented. Moreover, opportunities and future directions are outlined.

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“…In a more academic setting, a P-HIL test-bed has been developed for grid-connected battery energy storage systems at University of California, Riverside (UCR) [22]. Other platforms [25], [27] focus on testing of advanced DER coordination schemes in a scalable but not real-time environment that incorporates grid communication. Table I compares some key characteristics of these CPS platforms.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Grid and DER Co-Simulation Platform for Testing Large-Scale DER Coordination Schemes

Khurram

Amini

Espinosa

et al. 2022

IEEE Trans. Smart Grid

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Scalable Electric Power System Simulator

Cited by 7 publications

References 8 publications

Enhanced Automatic Generation Control (E-AGC) for Electric Power Systems with Large Intermittent Renewable Energy Sources

Enhanced Automatic Generation Control (E-AGC) for Electric Power Systems with Large Intermittent Renewable Energy Sources

Intelligent Identification over Power Big Data: Opportunities, Solutions, and Challenges

Real-Time Grid and DER Co-Simulation Platform for Testing Large-Scale DER Coordination Schemes

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