Design of wind generation auxiliary controls for stability improvement of bulk transmission systems
Bibliographic record
Abstract
Rapid development of renewable generation technology driven by economic, social and environmental incentives puts additional burden on power system operation and planning routines.Numerous challenges associated with the integration of renewable generation and gradual displacement of conventional energy sources determine current research activities and prospects.The focus of this thesis lies in the analysis and improvement of power system stability with the presence of renewable generation.Recognizing the potential of modern power electronics interfaced generation technologies to improve oscillatory angle and frequency stability, this thesis proposes an auxiliary control strategy based on multiple band-pass filters with well separated central frequencies.Given the operational complexity and growing rate of penetration of wind generation technology in bulk transmission grids, established multi-band control is specifically tailored towards applications for modern variable speed wind turbine technologies.Designated action of the auxiliary multi-band control is to temporarily change active and reactive power outputs of a wind farm during a contingency event in order to provide frequency support and damping capabilities for both electromechanical and frequency oscillations.The main advantage of such control over other commonly used topologies is its enhanced capability to improve long-term frequency stability associated with frequency control in power grids.In order to perform efficient analysis of frequency stability, a quasi-steady state approximation model for power system frequency dynamics based on time-scale decomposition is proposed.It recognizes important interactions between voltage and frequency dynamics in power systems and further justifies the potential of the proposed auxiliary control to improve frequency dynamics.Moreover, it serves as the basis for an auxiliary multi-band control design approach developed in this thesis.Case studies involving multiple contingency scenarios, including hardware-in-the-loop simulations with detailed wind turbine models confirm feasibility and effectiveness of the established auxiliary control loops and associated design procedures.Significant improvement of various aspects of power system stability is achieved without undue impact on wind turbines operation.First and foremost, I would like to thank Professor Gza Jos for his support and guidance throughout my work.His expertise, along with his constant feedback filled with insightful suggestions and comments helped me stay on course and ultimately see my thesis through.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".