PHASE 4 — REAL LOAD + BLACKOUT REPLAY

inZORi PF-Δ Phase 4: Real Load Profiles + Historical Blackout Scenarios

OPSD Real Data (UA/DE/FR) · N-4 Contingencies · Balkans 2006 · Ukraine 2015 · Moldova 2026
Dumitru Novic · February 2026 · IEEE 118-bus · OPSD real profiles · 3 countries · 5 seeds · CI95

Abstract

Phase 4 extends the inZORi Frozen Elite validation from synthetic load profiles to real historical load data from the Open Power System Data (OPSD) platform, covering Ukraine (UA), Germany (DE), and France (FR) — three structurally distinct European grids. Additionally, three documented historical blackout events are replayed as stress scenarios: the Balkans Cascading Blackout (Nov 2006), the Ukraine Cyberattack (Dec 2015), and the Moldova Blackout of 31 January 2026. Across all three real-profile countries, inZORi FrozenElite consistently outperforms NR standard by +3.31% to +3.69% in S3 convergence rate with statistically non-overlapping CI95 intervals across 5 seeds.

+3.64%
FrozenElite vs NR
Ukraine (UA) — 5 seeds
+3.69%
FrozenElite vs NR
Germany (DE) — 5 seeds
+3.31%
FrozenElite vs NR
France (FR) — 5 seeds
3
Historical blackout events
replayed & analyzed
60
Total simulation runs
3 countries × 4 variants × 5 seeds
CI95
Non-overlapping intervals
on all 3 countries

1. Methodology

1.1 Real Load Profile Integration

Load profiles from Open Power System Data (OPSD) replace the synthetic ShockGenerator seasonal variation. For each simulation step, the real hourly load value (normalized to [0,1]) is mapped to a scaling factor:

factor = 0.92 + normalized_profile[step] × 0.16 # → [0.92, 1.08] on base 1.75×

The ShockGenerator local zone perturbations (±3–12%) are retained on top, adding realistic local variability.

1.2 Data Sources

CountryGrid TypeData SourcePeriod
Ukraine (UA)Post-Soviet thermal/hydro mixOPSD 20202018–2019 hourly
Germany (DE)Renewables-heavy (wind/solar)OPSD 20202018–2019 hourly
France (FR)Nuclear-dominant (~70%)OPSD 20202018–2019 hourly

1.3 Variants Compared

LabelAlgorithmLoad ProfileRole
A: FrozenElite+RealAdaptive pool (12 genomes)OPSD (UA/DE/FR)Main result
B: G01 Static+RealFixed best genomeOPSD (UA/DE/FR)Single-genome baseline
C: NR Standard+RealNeutral genome (flat start)OPSD (UA/DE/FR)NR reference
D: FrozenElite+SyntheticAdaptive pool (12 genomes)ShockGeneratorSynthetic control

60 total runs: 3 countries × 4 variants × 5 seeds. Each run: 50,000 steps, N-1@300, N-2@600, N-4@1800. Runtime: 65.2 min on 12 cores.

2. Results — S3 Convergence per Country

S3 Convergence per country
Fig. 1 — S3 convergence rate (mean ± CI95) for UA, DE, FR across four variants. Error bars show 95% confidence intervals (5 seeds). All FrozenElite vs NR advantages are statistically significant with non-overlapping CI95.
CountryA: FE+RealB: G01+RealC: NR+RealD: FE+SyntAdvantage (A−C)
UA (Ukraine)74.17% ±0.4873.66% ±0.3570.54% ±0.5471.14% ±0.49+3.64%
DE (Germany)71.01% ±0.4670.33% ±0.5267.32% ±0.4871.13% ±0.57+3.69%
FR (France)76.30% ±0.4475.87% ±0.5372.99% ±0.5871.20% ±0.53+3.31%
FrozenElite advantage over NR
Fig. 2 — FrozenElite advantage over NR Standard per country (CI95 error bars). All three advantages are statistically significant with non-overlapping confidence intervals.
Phase 1 to 4 progression
Fig. 3 — inZORi research progression Phase 1→4. S3 convergence and FE advantage maintained across all phases. Phase 4 lower absolute values reflect harder real-world conditions.

3. Historical Blackout Replay

Three real documented blackout events are replayed in the IEEE 118-bus simulator. Each scenario uses the documented severity (N-k lines out) and estimated load level at the time of the event.

Balkans Cascading Blackout
4 November 2006, 22:10 CET — E.ON Netz line switching → European grid splits into 3 islands. ~15 million people affected in Western Europe.
Severity:N-2
Load level:1.0× nominal
Duration:200 simulation steps
Source:ENTSO-E Final Report 2007
FrozenElite: 90.7% · NR: 88.8% · Advantage: +1.9%
Ukraine Cyberattack Blackout
23 December 2015, 15:30 local — BlackEnergy malware on 3 TSOs. ~30 substations disconnected simultaneously. 225,000 customers without power for 1–6 hours.
Severity:N-4 equivalent
Load level:1.15× nominal
Duration:500 simulation steps
Source:E-ISAC/SANS ICS Report 2016
FrozenElite: 11.7% · NR: 11.5% · Advantage: +0.2% (both struggle at N-4 extreme)
Moldova Blackout
31 January 2026 — Technical failure on Isaccea–Vulcănești–MGRES 400kV line. Moldova islanded from Romania and Ukraine. Chișinău affected. Restored same day.
Severity:N-1 critical
Load level:1.10× nominal
Duration:150 simulation steps
Source:Moldelectrica / Ukrenergo, Jan 2026
FrozenElite: 22.5% · NR: 21.4% · Advantage: +1.1%
Blackout scenario replay results
Fig. 4 — Convergence rate during critical event windows for three historical blackout scenarios. inZORi FrozenElite consistently maintains higher convergence. At N-4 extreme (Ukraine 2015), both methods struggle — the network approaches voltage collapse boundary.
  • Simulation note: Blackout scenarios use IEEE 118-bus topology, not the actual Isaccea–Vulcănești or Ukrainian TSO networks. N-k parameters and load levels are calibrated from public reports but the simulation is a proxy, not an exact replay. Exact reproduction requires CGMES network models from ENTSO-E (addressed in Phase 5 with ENTSO-E API data).

4. Claims & Limitations

  • CLAIMS: inZORi FrozenElite maintains higher S3 convergence than NR standard on real OPSD load profiles from UA, DE, FR with statistically significant margins (CI95 non-overlapping) across 5 seeds
  • CLAIMS: The advantage is consistent (+3.3–3.7%) regardless of grid structure (post-Soviet thermal, renewables-heavy, or nuclear-dominant)
  • CLAIMS: Under extreme N-4 conditions (Ukraine 2015 scenario), all methods degrade equally — the advantage shrinks to ~0.2%, confirming inZORi cannot solve physically infeasible systems
  • DOES NOT CLAIM: Results on real TSO network topologies (CGMES) — only IEEE 118-bus
  • DOES NOT CLAIM: Exact replay of historical blackouts — only calibrated proxies using public report parameters
  • DOES NOT CLAIM: Comparison with commercial solvers (PSS/E, PowerFactory) or deep learning approaches

5. Reproducibility

ComponentDetails
Load profilesOPSD 2020-10-06, hourly, UA/DE/FR columns
Networkpandapower case118 (IEEE 118-bus)
Seeds0–4 (5 independent runs per variant)
Steps50,000 per run, seasons S0–S3 (25% each)
ContingenciesN-1@300, N-2@600, N-4@1800 steps (S3 only)
Runtime65.2 min, 12 cores, ProcessPoolExecutor