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Dive into the research topics where Fengkai Hu is active.

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Featured researches published by Fengkai Hu.


IEEE Transactions on Power Systems | 2016

Measurement-Based Real-Time Voltage Stability Monitoring for Load Areas

Fengkai Hu; Kai Sun; Alberto Del Rosso; Evangelos Farantatos; Navin Bhatt

Summary form only given. This paper proposes a measurement-based voltage stability monitoring method for a load area fed by N tie lines. Compared to a traditional Thevenin equivalent based method, the new method adopts an N+1 buses equivalent system so as to model and monitor individual tie lines. For each tie line, the method solves the power transfer limit against voltage instability analytically as a function of all parameters of that equivalent, which are online identified from real-time synchronized measurements on boundary buses of the load area. Thus, this new method can directly calculate the real-time power transfer limit on each tie line. The method is first compared with a Thevenin equivalent based method using a four-bus test system and then demonstrated by case studies on the NPCC (Northeast Power Coordinating Council) 48-machine, 140-bus power system.


power and energy society general meeting | 2014

An adaptive three-bus power system equivalent for estimating voltage stability margin from synchronized phasor measurements

Fengkai Hu; Kai Sun; Alberto Del Rosso; Evangelos Farantatos; Navin Bhatt

This paper utilizes an adaptive three-bus power system equivalent for measurement-based voltage stability analysis. With that equivalent identified online, a measurement-based approach is developed to estimate real-time voltage stability margin for a load-rich area supported by remote generation via multiple tie lines. Compared with traditional Thevenin equivalent based approach, this new approach is able to provide more accurate voltage stability margin for each individual tie line. This approach is validated on a three-bus system and the IEEE 39-bus system.


power and energy society general meeting | 2014

Identification and wide-area visualization of the centers of oscillation for a large-scale power system

Leonardo E. Bernal; Fengkai Hu; Kai Sun; Evangelos Farantatos

A system wide disturbance event usually triggers inter-area oscillations at the system. Understanding the nature of those oscillations is important for taking necessary early mitigation actions. This work presents a novel scheme for analyzing inter-area oscillations by identification of the centers of oscillation (CoO) using two methods based on wide-area measurement data: one method directly calculate CoOs for transmission lines with synchrophasors on both ends and the other estimate CoOs based on contour visualization about frequency deviations extrapolated for the entire map. CoOs serve as pivots between oscillating parts under disturbances and hence indicate the grid interfaces involved in oscillation, so this scheme can provide the operator recommendations on where mitigation actions may be taken to prevent instability. The proposed scheme is tested using simulated synchrophasor data on a WECC 179-bus test system.


IEEE Transactions on Power Systems | 2018

Online Voltage Stability Assessment for Load Areas Based on the Holomorphic Embedding Method

Chengxi Liu; Bin Wang; Fengkai Hu; Kai Sun; Claus Leth Bak

This paper proposes an online steady-state voltage stability assessment scheme to evaluate the proximity to voltage collapse at each bus of a load area. Using a non-iterative holomorphic embedding method (HEM) with a proposed physical germ solution, an accurate loading limit at each load bus can be calculated based on online state estimation on the entire load area and a measurement-based equivalent for the external system. The HEM employs a power series to calculate an accurate Power-Voltage (P-V) curve at each load bus and accordingly evaluates the voltage stability margin considering load variations in the next period. An adaptive two-stage Pade approximants (PA) method is proposed to improve the convergence of the power series for accurate determination of the nose point on the P-V curve with moderate computational burden. The proposed method is illustrated in detail on a 4-bus test system and then demonstrated on a load area of the Northeast Power Coordinating Council (NPCC) 48-generator, 140-bus power system.


power and energy society general meeting | 2016

Measurement-based real-time voltage stability monitoring for load areas

Fengkai Hu; Kai Sun; Alberto Del Rosso; Evangelos Farantatos; Navin Bhatt

This paper proposes a measurement-based voltage stability monitoring method for a load area fed by N tie lines. Compared to a traditional Thevenin equivalent based method, the new method adopts an N +1 buses equivalent system so as to model and monitor individual tie lines. For each tie line, the method solves the power transfer limit against voltage instability analytically as a function of all parameters of that equivalent, which are online identified from real-time synchronized measurements on boundary buses of the load area. Thus, this new method can directly calculate the real-time power transfer limit on each tie line. The method is first compared with a Thevenin equivalent based method using a 4-bus test system and then demonstrated by case studies on the Northeast Power Coordinating Council (NPCC) 48-machine, 140-bus power system.


power and energy society general meeting | 2016

Voltage stability margin estimation for a load area using a three-bus equivalent

Denis Osipov; Fengkai Hu; Kai Sun

This paper describes a new method for estimating the power transfer limits on tie lines of a load area represented using a three-bus equivalent recently proposed. This new method uses companion matrix eigenvalues to solve a sextic equation about the maximum active power transfer against voltage instability and is able to handle more general load increase scenarios. The proposed method is compared with a previously proposed partial derivative calculation based method using an artificial three-bus system to demonstrate its better accuracy and is also tested on the Northeast Power Coordinating Council 140-bus power system for calculating the power transfer limits of three tie lines of the Connecticut Load Center.


power and energy society general meeting | 2016

Measurement-based voltage stability assessment and control on CURENT hardware test bed system

Fengkai Hu; Liu Yang; Jingxin Wang; Yiwei Ma; Kai Sun; Leon M. Tolbert; Fred Wang

A measurement-based voltage stability assessment and closed-loop control strategy is proposed and demonstrated on the Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT) Hardware Test Bed (HTB) system, a power electronic converter-based research and experiment platform. This new strategy is based on an N+1 buses equivalent proposed recently by Ref. [1] for calculating real-time voltage stability margins on individual tie lines of a load area. Two voltage stability scenarios are designed and implemented on the HTB system that emulates a three-area power system integrating conventional generation, wind generation, and multi-terminal HVDC transmission. The tests validate the effectiveness of real-time monitoring and closed-loop control against voltage instability initiated from one tie line of the load area.


ieee pes innovative smart grid technologies conference | 2014

A new approach for real-time voltage stability monitoring using PMUs

Kai Sun; Fengkai Hu; Navin Bhatt


arXiv: Computational Engineering, Finance, and Science | 2017

Real-Time Voltage Stability Assessment for Load Areas Based on the Holomorphic Embedding Method.

Chengxi Liu; Bin Wang; Fengkai Hu; Kai Sun; Claus Leth Bak


Iet Generation Transmission & Distribution | 2017

Measurement-based voltage stability assessment for load areas addressing n−1 contingencies

Fengkai Hu; Kai Sun; Di Shi; Zhiwei Wang

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Kai Sun

University of Tennessee

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Evangelos Farantatos

Electric Power Research Institute

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Navin Bhatt

Electric Power Research Institute

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Alberto Del Rosso

Electric Power Research Institute

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Bin Wang

University of Tennessee

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Chengxi Liu

University of Tennessee

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Denis Osipov

University of Tennessee

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Di Shi

Princeton University

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Fred Wang

University of Tennessee

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