pith:SWFIIC23
Frequency Quality Metrics based on Second-Order Derivative and Autocorrelation
Power systems can show good frequency quality by standard metrics yet poor quality by metrics based on second-order derivatives and autocorrelation.
arxiv:2604.09136 v2 · 2026-04-10 · eess.SY · cs.SY
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\usepackage{pith}
\pithnumber{SWFIIC23PBTM3HOJMATBEW3ZWH}
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Record completeness
Claims
a power system may show good frequency quality using standard metrics and poor frequency quality using the proposed metrics
That second-order derivative and autocorrelation metrics provide a more accurate or useful assessment of true dynamic frequency behavior than existing TSO metrics, without the paper demonstrating superior predictive power for stability events.
New second-order derivative and autocorrelation metrics for grid frequency quality can indicate poor performance in systems rated good by traditional measures.
Receipt and verification
| First computed | 2026-05-29T01:05:09.134427Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
958a840b5b7866cd9dc96026125b79b1c763d6c75ebe1d85f32ad43d4bb07910
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SWFIIC23PBTM3HOJMATBEW3ZWH \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 958a840b5b7866cd9dc96026125b79b1c763d6c75ebe1d85f32ad43d4bb07910
Canonical record JSON
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