Data-driven unified scheme to enhance the stability of solar energy integrated power system in real-time.
Solar energy penetration in power grids helps to maintain power balance between generation and demand, thus enhances power grid performance. However, these integrations reduce grids' time margin to respond against sudden frequency changes and re-establishing generation-demand equivalency. There...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/104911/1/HasmatMalik2023_DataDrivenUnifiedSchemetoEnhancetheStability.pdf http://eprints.utm.my/104911/ http://dx.doi.org/10.1109/ACCESS.2023.3325195 |
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| Summary: | Solar energy penetration in power grids helps to maintain power balance between generation and demand, thus enhances power grid performance. However, these integrations reduce grids' time margin to respond against sudden frequency changes and re-establishing generation-demand equivalency. Thereby, it poses challenges to the performance and stability of the power system. It therefore becomes increasingly important to comprehend the real-time system data, identify and initiate necessary remedies to sustain the healthy system's operation. This article presents a data-driven unified methodology for enhancing grid stability in solar energy-penetrated power network. The proposed method is a two-stage unified framework that incorporates Prompt Instability Evaluation (PIE) to evaluate impending system transient instability in first stage. In the second stage for a system unstable operation a Decision Assisted Adaptive Control (DAAC) is developed and implemented for corrective emergency control. A novel PIE is presented to perform a post-disturbance transient stability assessment using short-synchronized moving data. The PIE assesses the upcoming transient instability within the first few cycles following fault inception. Next, a novel DAAC is proposed to design an emergency remedial scheme for identifying location (where), magnitude, and type in real-time for unstable operations. The DAAC utilizes a novel Decision Rule Based Inference (DRBI) to evaluate suitable action sets that may be deployed by the DAAC to sustain system stability. The simulation results demonstrate the suitability of the proposed study on the system's performance in the absence/presence of solar energy with topological variations. |
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