Assessment of inertial and primary frequency control from wind power plants in the Mexican electric power grid
Bibliographic record
Abstract
Abstract Large‐scale integration of converter‐based renewable energy sources into power systems, such as wind generation, can lead to frequency stability issues due to the variable nature and lack of inertia of these technologies in combination with the gradual replacement of conventional generating units. However, wind turbine generators (WTGs) can be exploited to provide frequency support and keep system frequency stability requirements. A case study considering the Mexican Electric Power System is presented in this study to highlight both the impact of large‐scale deployment of inverter‐interfaced wind energy generation on system frequency response, and the participation of WTGs in inertial and primary frequency control (IPFC) as a mitigation approach. By incorporating synthetic inertia and droop control functions into the active power control loop of WTG converters, IPFC by wind generation is assessed for several wind shares, different active power modulation strategies based on the rate of change of frequency and frequency deviation, and several IPFC contribution levels under critical contingencies for generation outage. Simulation results show the combination of increasing share of wind energy generation in the study system and retirement of conventional generation has a clearly negative impact on system frequency dynamics. However, the incorporation of IPFC functions into wind power generators of the sample system, with appropriate control gain values, may contribute to effectively achieve an improved system performance in terms of grid frequency response under high wind power penetration scenarios. This article is characterized under: Wind Power > Science and Materials Wind Power > Systems and Infrastructure Energy Research & Innovation > Science and Materials
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".