Probabilistic assessment of short‐term voltage stability under load and wind uncertainty
Abstract Contemporary electricity networks are exposed to operational uncertainties, which may jeopardise the stability of the power grid. More specifically, the increasing penetration level of variable renewable energy generation and uncertainty in load demand are key catalysts for these emerging s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
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| Series: | IET Smart Grid |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/stg2.12180 |
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| Summary: | Abstract Contemporary electricity networks are exposed to operational uncertainties, which may jeopardise the stability of the power grid. More specifically, the increasing penetration level of variable renewable energy generation and uncertainty in load demand are key catalysts for these emerging stability issues. A mathematical relationship is established to track the system voltage trajectory with respect to variations in uncertain inputs (associated with wind speed, system load, and wind power penetration levels). Additionally, it demonstrates the consequences of varying uncertain inputs on the short‐term voltage response across different potential operating conditions. The theoretical proposition has further been verified by the simulation studies with two test power networks in DIgSILENT PowerFactory software. The simulation results revealed that uncertain injection sources significantly impacted the system voltage at the receiving end. High uncertainty in wind speed and system loads increased voltage recovery variation, causing delays in voltage response during low wind speeds and high system loads. Additionally, increased wind power penetration levels expanded voltage recovery uncertainties, resulting in decreased system voltage and potentially leading to voltage violations and instability at 30% wind power levels. Moreover, the results showed that the system's response time increased, and in some cases, it collapsed due to increased system capacity (>80%) and dynamic load (>75%), as well as encountering a large disturbance under uncertain circumstances. |
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| ISSN: | 2515-2947 |