Insights on Blackstart Provisioning Using a Synchronous Generator and Grid-Forming Inverter Using EMT Simulations

Grid-forming inverters (GFMIs) have been identified as critical assets in ensuring modern power system reliability. Their ability to synthesize an internal voltage reference while emulating synthetic inertia has sparked extensive research. These characteristics have recently piqued interest in their capacity to provide blackstart ancillary services. The blackstart of a bulk power system poses significant challenges, namely the large transients from the energization of unloaded transformers, rotational motor loads, and long transmission cables, which have been effectively studied using conventional synchronous generators (SGs). The concept of an inverter-based resource (IBR)-based blackstart continues to be an open research area necessitating further investigations due to the known limitations of IBRs such as low short-circuit current capabilities. This paper presents a blackstart case study of a bulk power system investigating the performances of a conventional SG to a GFMI when utilizing hard switching methods. The paper qualitatively investigates the transient inrush currents from the transformer and rotational load energization sequences. Additional examinations into the significance of the GFMI’s current-limiting schemes and voltage control loop compensator gains are presented. Furthermore, the harmonic distortions from the transformer energization sequence are also evaluated. Finally, a full network energization case is presented to demonstrate how both sources can provide blackstart provisioning services. The models are developed in EMTDC/PSCAD using real-world transmission planning data.

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Publication Details

Journal
Energies
Published
2024-08-16
DOI
https://doi.org/10.3390/en17164067
Citations
1
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
0.21

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article

Insights on Blackstart Provisioning Using a Synchronous Generator and Grid-Forming Inverter Using EMT Simulations

Olga Lavrova, Satish J. Ranade, José Ribeiro, Deepak Ramasubramanian et al.
1 citations
Energies
Islanding Detection in Power Systems
0.21
article

Insights on Blackstart Provisioning Using a Synchronous Generator and Grid-Forming Inverter Using EMT Simulations

Olga Lavrova, Satish J. Ranade, José Ribeiro, Deepak Ramasubramanian, Huzaifa Karimjee
article en
1 citations

Abstract

Grid-forming inverters (GFMIs) have been identified as critical assets in ensuring modern power system reliability. Their ability to synthesize an internal voltage reference while emulating synthetic inertia has sparked extensive research. These characteristics have recently piqued interest in their capacity to provide blackstart ancillary services. The blackstart of a bulk power system poses significant challenges, namely the large transients from the energization of unloaded transformers, rotational motor loads, and long transmission cables, which have been effectively studied using conventional synchronous generators (SGs). The concept of an inverter-based resource (IBR)-based blackstart continues to be an open research area necessitating further investigations due to the known limitations of IBRs such as low short-circuit current capabilities. This paper presents a blackstart case study of a bulk power system investigating the performances of a conventional SG to a GFMI when utilizing hard switching methods. The paper qualitatively investigates the transient inrush currents from the transformer and rotational load energization sequences. Additional examinations into the significance of the GFMI’s current-limiting schemes and voltage control loop compensator gains are presented. Furthermore, the harmonic distortions from the transformer energization sequence are also evaluated. Finally, a full network energization case is presented to demonstrate how both sources can provide blackstart provisioning services. The models are developed in EMTDC/PSCAD using real-world transmission planning data.

EnergiesVol. 17(16)
New Mexico State University (US), Electric Power Research Institute (US)
New Mexico State University
Industry, innovation and infrastructure
Openalex Percentile: Top 49%
Islanding Detection in Power Systems
0.21
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