Performance Analysis of a 10 MW Wind Farm in Providing Secondary Frequency Regulation: Experimental Aspects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Experimental results and performance analyses of wind farms providing secondary frequency regulation is lacking. This is despite the increasing share of variable generators in electrical energy production. As variable generators displace traditional generators that provide ancillary services, there is a growing need for alternate providers of these ancillary services. Wind generators are technologically capable of providing ancillary services, such as frequency regulation. This paper presents experimental results of a secondary frequency regulation test carried out on a 10 MW wind farm with Type-V wind turbines. This is a 5 h test of the wind farm's ability to follow an external, historical automatic generation control signal. 1 MW of power is offered on the regulation market with up-regulation provided via a fixed curtailment value. The performance of the farm is evaluated using the performance score method developed by the Pennsylvania-New Jersey-Maryland (PJM) system operator. Performance scores are used to perform an economic analysis using 2017 hourly PJM price data. This results in an estimated additional income of $7200 from participating in the regulation market versus providing energy alone. A sensitivity analysis reveals that profitability is more influenced by the turbine's performance scores than regulation and energy prices. This paper also examines some practical aspects of providing secondary regulation, such as pitch activity, power error, and operating power ranges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 it