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Power systems with utility-scale solar photovoltaic (PV) can significantly influence the operating points (OPs) of synchronous generators, particularly during periods of high solar PV generation. A sudden drop in solar PV output due to cloud cover or other transient conditions will alter the generation of synchronous generators shifting their OPs. These shifted OPs can become a challenge for stability as the system may operate closer to its stability limits. If a disturbance occurs while the system is operating at the shifted OP, with reduced stability margins, it will be more vulnerable to increased oscillations, loss of synchronism of its generator(s) and system instability. This study introduces a scalable delta-automatic generation control (delta-AGC) logic method designed to address stability challenges arising from shifts in the OPs of synchronous generators during abrupt drops in PV generation. By temporarily adjusting the OPs of synchronous generators through modification of their participation factors (PFs) in the AGC logic dispatch, the proposed method enhances power system stability. The proposed delta-AGC logic method focuses on the optimal determination of delta-PFs in power systems with large number of generators, using the concept of coherency and employing a hierarchical optimization strategy that includes both inter-coherent and intra-coherent group optimization. Additionally, a new electromechanical oscillation index (EMOI), integrating both time response analysis (TRA) and frequency response analysis (FRA), is utilized as an online situational awareness tool (SAT) for optimizing the system’s stability under various conditions. This online SAT has been implemented in a decentralized manner at the area level, limiting wide-area communication overheads and any cybersecurity concerns. The delta-AGC logic method is illustrated on a modified IEEE 68 bus system, incorporating large utility-scale solar PV plants, and is validated through real-time simulation. Various cases, including high-loading conditions with and without power system stabilizers, conventional AGC logic, and delta-AGC logic, are carried out to evaluate the effectiveness of the proposed delta-AGC logic method. The results illustrate the performance and benefits of the delta-AGC logic method, highlighting its potential to significantly enhance power system stability.
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This content will become publicly available on February 1, 2026
Impedance Profile Prediction for Grid-Connected VSCs With Data-Driven Feature Extraction
Data-driven approach is promising for predicting impedance profile of grid-connected voltage source converters (VSCs) under a wide range of operating points (OPs). However, the conventional approaches rely on a one-to-one mapping between operating points and impedance profiles, which, as pointed out in this article, can be invalid for multiconverter systems. To tackle this challenge, this article proposes a stacked-autoencoder-based machine learning framework for the impedance profile predication of grid-connected VSCs, together with its detailed design guidelines. The proposed method uses features, instead of OPs, to characterize impedance profiles, and hence, it is scalable for multiconverter systems. Another benefit of the proposed method is the capability of predicting VSC impedance profiles at unstable OPs of the grid-VSC system. Such prediction can be realized solely based on data collected during stable operation, showcasing its potential for rapid online state estimation. Experiments on both single-VSC and multi-VSC systems validate the effectiveness of the proposed method.
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- Award ID(s):
- 1847365
- PAR ID:
- 10563421
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE Transactions on Power Electronics
- Volume:
- 40
- Issue:
- 2
- ISSN:
- 0885-8993
- Page Range / eLocation ID:
- 3043 to 3061
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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