A method for monitoring the load margin of power systems under load growth variations

被引：19

作者：

Bento, Murilo E. C. ^{[1
]}

机构：

[1] Univ Fed Rio de Janeiro, Dept Elect Engn, BR-21941909 Rio De Janeiro, RJ, Brazil

来源：

SUSTAINABLE ENERGY GRIDS & NETWORKS | 2022年 / 30卷

基金：

巴西圣保罗研究基金会;

关键词：

Voltage stability; Small-signal stability; Dynamic security assessment; Load growth direction uncertainty; Load margin; PMU placement; REDUCED NETWORK; STABILITY;

D O I：

10.1016/j.segan.2022.100677

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The load margin is an important safety measure used in operation centers to assess the voltage stability of power systems. Usually this measure is calculated considering a single load growth direction and voltage stability requirements. However, oscillation modes with low damping rates can compromise the small-signal stability of power systems and different load growth directions can also affect load margin estimates. Thus, these two factors must be considered to provide adequate load margin power system operation. This paper proposes a load margin monitoring scheme based on Artificial Neural Networks (ANN) considering voltage stability requirements and small-signal stability and load growth variations. Thus, the power system operator will have real-time load margin information considering voltage stability requirements and small-signal stability requirements. ANN uses as input data the voltage magnitude and voltage angle measurements provided by Phasor Measurement Units (PMUs) installed in system buses. A method to select a reduced set of buses for the monitoring system is proposed and evaluated. Case studies are presented and the results achieved provide indications the applicability of the proposed scheme in the real-time operation of power systems. (c) 2022 Elsevier Ltd. All rights reserved.

引用

页数：10

共 36 条

[1]

Ajjarapu V, 2007, POWER ELECTRON POWER, P1, DOI 10.1007/978-0-387-32935-2

[2] Voltage stability assessment algorithm to predict power system loadability margin [J].

Akbarzadeh Aghdam, Pouria ;

Khoshkhoo, Hamid .

IET GENERATION TRANSMISSION & DISTRIBUTION, 2020, 14 (10) :1816-1828

[3] Synchrophasor Measurement Technology in Power Systems: Panorama and State-of-the-Art [J].

Aminifar, Farrokh ;

Fotuhi-Firuzabad, Mahmud ;

Safdarian, Amir ;

Davoudi, Ali ;

Shahidehpour, Mohammad .

IEEE ACCESS, 2014, 2 :1607-1628

[4]

[Anonymous], 2007, PROPOSITION TEST SYS

[5] Voltage stability monitoring of power systems using reduced network and artificial neural network [J].

Ashraf, Syed Mohammad ;

Gupta, Ankur ;

Choudhary, Dinesh Kumar ;

Chakrabarti, Saikat .

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2017, 87 :43-51

[6] Power system voltage stability monitoring using artificial neural networks with a reduced set of inputs [J].

Bahmanyar, A. R. ;

Karami, A. .

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 58 :246-256

[7] An approach for monitoring and updating the load margin of power systems in dynamic security assessment [J].

Bento, Murilo E. C. ;

Ramos, Rodrigo A. .

ELECTRIC POWER SYSTEMS RESEARCH, 2021, 198

[8] Monitoring of the power system load margin based on a machine learning technique [J].

Bento, Murilo E. C. .

ELECTRICAL ENGINEERING, 2022, 104 (01) :249-258

[9] Fixed Low-Order Wide-Area Damping Controller Considering Time Delays and Power System Operation Uncertainties [J].

Bento, Murilo E. C. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (05) :3918-3926

[10]

Bento MEC, 2018, 2018 WORKSHOP ON COMMUNICATION NETWORKS AND POWER SYSTEMS (WCNPS), P1

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