A review of<scp>STATCOM</scp>control for stability enhancement of power systems with wind/<scp>PV</scp>penetration: Existing research and future scope
Bibliographic record
Abstract
In recent years, the development of renewable energy sources (RESs) and their integration with the conventional power network have increased significantly. Due to the power grid transformation brought about by the large penetration of power electronics converter-based RESs such as wind and solar photovoltaic (PV), the operation and control of the interconnected power system has become a challenging task with respect to sustaining its stability and reliability. Power systems are confronted by several new stability issues because the dynamic behavior of converter-interfaced renewable sources differs from conventional generation. In this respect, static synchronous compensator (STATCOM), a shunt connected flexible AC transmission system (FACTS), is recognized as a fundamental solution for maintaining power system stability. This paper presents a thorough and state-of-the-art review of STATCOM control in wind- and/or PV-interfaced power systems for enhancing system performance by addressing key stability issues related to rotor angle stability, voltage stability, and resonance stability. A comprehensive analysis of various control techniques of STATCOM based on conventional, adaptive, nonlinear, predictive, robust, and coordinated control and soft computing techniques is provided. Furthermore, the function of the grid-side converter of the wind/PV plant as a STATCOM is also evaluated. Finally, the shortcomings of existing research are highlighted, current control challenges are presented, and several topics for future research are suggested. This paper provides researchers the opportunity to consider the current state of research and develop new control schemes for STATCOM to further improve the stability of modern power grids.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".