Short-Term Voltage Stability Improvement in Power System Through Grid-Forming Hybrid PV Plants

Short-term voltage stability problems are a major concern in power systems with high penetration of inverter-based resources (IBRs). Fault-induced delayed voltage recovery (FIDVR) is one such problem that can lead to short-term voltage instability. This paper investigates FIDVR mitigation using dynamic voltage support from hybrid PV plants and load control. We propose a deep reinforcement learning (DRL) based optimization framework for optimal dynamic reactive power injection from hybrid PV plants and optimal load control. The Q-injection and amount of load tripping depend on system operating conditions, so the data-driven framework gives optimal setpoints that are adaptable to the varying operating conditions. The numerical simulations show that the optimal dynamic reactive power injection and load control improve the voltage recovery and decrease the load trip amount to comply with the voltage recovery criterion.

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Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2025-03-11
DOI
https://doi.org/10.1109/tia.2025.3550153
Citations
4
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
2.13
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article

Short-Term Voltage Stability Improvement in Power System Through Grid-Forming Hybrid PV Plants

Hugo N. Villegas Pico, Venkataramana Ajjarapu, Amarsagar Reddy Ramapuram Matavalam, Soummya Roy et al.
4 citations
IEEE Transactions on Industry Applications
Power Systems and Renewable Energy
2.13
article

Short-Term Voltage Stability Improvement in Power System Through Grid-Forming Hybrid PV Plants

Hugo N. Villegas Pico, Venkataramana Ajjarapu, Amarsagar Reddy Ramapuram Matavalam, Soummya Roy, Muhammad Sarwar
article en
4 citations

Abstract

Short-term voltage stability problems are a major concern in power systems with high penetration of inverter-based resources (IBRs). Fault-induced delayed voltage recovery (FIDVR) is one such problem that can lead to short-term voltage instability. This paper investigates FIDVR mitigation using dynamic voltage support from hybrid PV plants and load control. We propose a deep reinforcement learning (DRL) based optimization framework for optimal dynamic reactive power injection from hybrid PV plants and optimal load control. The Q-injection and amount of load tripping depend on system operating conditions, so the data-driven framework gives optimal setpoints that are adaptable to the varying operating conditions. The numerical simulations show that the optimal dynamic reactive power injection and load control improve the voltage recovery and decrease the load trip amount to comply with the voltage recovery criterion.

IEEE Transactions on Industry ApplicationsVol. 61(5)
Iowa State University (US), Arizona State University (US)
Affordable and clean energy
Openalex Percentile: Top 13%
Power Systems and Renewable Energy
2.13
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