pith:KL5325BY
Stochastic Modeling of Power-Grid Frequency Fluctuations in Low-Inertia Systems via a Gaussian-Core Potential and Superstatistics
A Gaussian-core potential plus superstatistics reproduces the bimodal frequency distributions observed in low-inertia power grids.
arxiv:2605.13289 v1 · 2026-05-13 · physics.soc-ph
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Claims
Fitting the model to frequency data resolved at one-second intervals from the Great Britain grid, we find that the central barrier parameter increases substantially from 2020 to 2025 as the grid inertia progressively decreases.
The assumption that the coefficients for the grid dynamics fluctuate slowly, allowing the use of superstatistical modeling with a lognormal distribution for the drift amplitude.
A Gaussian-core potential plus superstatistics reproduces the bimodal frequency distributions, central suppression, and heavy tails observed in Great Britain grid data as inertia declines.
References
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| First computed | 2026-05-18T02:44:49.133054Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
52fbbd7438a7ace8faf53f3659d364ecfa34d842d8bd683ca4dbfa0bb7e2fd14
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KL5325BYU6WOR6XVH43FTU3E5T \
| 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: 52fbbd7438a7ace8faf53f3659d364ecfa34d842d8bd683ca4dbfa0bb7e2fd14
Canonical record JSON
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