Virtual Inertia Planning for Enhancing Grid Stability in Low‐Inertia Systems

ABSTRACT The global power grid is undergoing a significant transition with the increasing integration of renewable energy sources (RESs). This shift, characterised by a decline in conventional synchronous generators and a rise in inverter‐based RESs, has resulted in reduced grid inertia, posing substantial challenges to frequency stability. To address these challenges, this paper proposes a reliability‐aware optimisation framework for virtual inertia planning in grids with high RES penetration. The framework accounts for stochastic variations in load demand and renewable generation and optimises the required virtual inertia to ensure frequency stability during a contingency involving the largest generating unit. A reliability‐driven methodology is integrated to determine the necessary virtual inertia constants and energy reserves in battery energy storage systems (BESSs) on an hourly basis, ensuring that the frequency nadir and RoCoF constraints are met under varying system conditions. The case study illustrated how the proposed approach determines BESS virtual inertia support requirements on an hourly basis, adapting to fluctuations in available system inertia and RES output. For instance, at 12:00 corresponding to peak solar generation, the required BESS inertia constant and energy reserve were determined to be 1.65 s and 2.56 MWh for 50% reliability increasing to 3.57 s and 5.27 MWh for 90% reliability. The total BESS capacity required was 76.3 MWh for 90% reliability compared to 46.25 MWh and 57.78 MWh for 50% and 70% reliability, respectively. These results underscore the significance of reliability aware inertia planning as higher reliability levels necessitate greater inertial support to mitigate the impact of contingencies involving the largest generating unit. Notably, during peak solar hours (e.g., 11:00, 13:00 and 15:00), the percentage of frequency constraint violations is reduced from nearly 100% to 4.38%, 9.86% and 7.12%, respectively, when virtual inertia support from BESS is applied at 90% reliability. An economic evaluation was carried out to assess BESS performance under different reliability targets. The results show that although annual benefits remain positive, the benefit–cost ratio declines from 1.12 at 50% to 1.06 at 90% and the NPV decreases from 2.06 M AUD to 1.50 M AUD. This indicates that higher reliability improves frequency stability but requires greater BESS investment, leading to diminishing economic returns. In this context, the proposed framework offers grid operators a decision‐making tool to set reliability targets consistent with grid codes, contingency standards and investment capacity.

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Publication Details

Journal
IET Energy Systems Integration
Published
2025-01-01
DOI
https://doi.org/10.1049/esi2.70019
Citations
1
Primary Topic
Vibration and Dynamic Analysis
Type
article
Field-Weighted Citation Impact
1.21
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article

Virtual Inertia Planning for Enhancing Grid Stability in Low‐Inertia Systems

Amanullah Maung Than Oo, M.I. Saleem, Tushar Kanti Roy, Sajeeb Saha
1 citations
IET Energy Systems Integration
Vibration and Dynamic Analysis
1.21
article

Virtual Inertia Planning for Enhancing Grid Stability in Low‐Inertia Systems

Amanullah Maung Than Oo, M.I. Saleem, Tushar Kanti Roy, Sajeeb Saha
article en
1 citations

Abstract

ABSTRACT The global power grid is undergoing a significant transition with the increasing integration of renewable energy sources (RESs). This shift, characterised by a decline in conventional synchronous generators and a rise in inverter‐based RESs, has resulted in reduced grid inertia, posing substantial challenges to frequency stability. To address these challenges, this paper proposes a reliability‐aware optimisation framework for virtual inertia planning in grids with high RES penetration. The framework accounts for stochastic variations in load demand and renewable generation and optimises the required virtual inertia to ensure frequency stability during a contingency involving the largest generating unit. A reliability‐driven methodology is integrated to determine the necessary virtual inertia constants and energy reserves in battery energy storage systems (BESSs) on an hourly basis, ensuring that the frequency nadir and RoCoF constraints are met under varying system conditions. The case study illustrated how the proposed approach determines BESS virtual inertia support requirements on an hourly basis, adapting to fluctuations in available system inertia and RES output. For instance, at 12:00 corresponding to peak solar generation, the required BESS inertia constant and energy reserve were determined to be 1.65 s and 2.56 MWh for 50% reliability increasing to 3.57 s and 5.27 MWh for 90% reliability. The total BESS capacity required was 76.3 MWh for 90% reliability compared to 46.25 MWh and 57.78 MWh for 50% and 70% reliability, respectively. These results underscore the significance of reliability aware inertia planning as higher reliability levels necessitate greater inertial support to mitigate the impact of contingencies involving the largest generating unit. Notably, during peak solar hours (e.g., 11:00, 13:00 and 15:00), the percentage of frequency constraint violations is reduced from nearly 100% to 4.38%, 9.86% and 7.12%, respectively, when virtual inertia support from BESS is applied at 90% reliability. An economic evaluation was carried out to assess BESS performance under different reliability targets. The results show that although annual benefits remain positive, the benefit–cost ratio declines from 1.12 at 50% to 1.06 at 90% and the NPV decreases from 2.06 M AUD to 1.50 M AUD. This indicates that higher reliability improves frequency stability but requires greater BESS investment, leading to diminishing economic returns. In this context, the proposed framework offers grid operators a decision‐making tool to set reliability targets consistent with grid codes, contingency standards and investment capacity.

IET Energy Systems IntegrationVol. 7(1)
University of the Sunshine Coast (AU), Macquarie University (AU)
Openalex Percentile: Top 16%
Vibration and Dynamic Analysis
1.21
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