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Gas — Metro

Harbor City Gas (synthetic)
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UnitTrack · Disclosure-controlled report

Gas — Metro

Harbor City Gas (synthetic)
Generated 2026-07-27 19:37 · Grouped by customer class · k = 15
Residual re-identification risk
worst case 0% · Low · smallest published group 995
1/3
Customer class groups published
—
of meter reads in published output
2
groups withheld by disclosure control
15/15 rule
≥15 contributors; no single customer over 15%
Contents
  1. Disclosure control & data provenance
  2. Consumption profile
  3. Geography & spatial clustering
  4. Weather & seasonality
  5. Benchmarking (EUI)
  6. Energy burden & equity
  7. Measurement & verification (M&V)
  8. Differential privacy (alternative release)
  9. Appendix — policy & citations

Disclosure control & data provenance

Grouping the dataset into 3 customer class groups, 1 were safe to publish and 2 were withheld under the rules below. The exact share published and the grand total are withheld here so the small suppressed group can't be recovered by subtraction; the published output carries a worst-case re-identification risk of 0% (Low).

Data quality & reliability
14400
Loaded reads
0 rejected & quarantined
13.8%
Estimated reads
utility estimate flag
1.8%
Negative usage
rollovers / net metering
1810
High outliers
Tukey 1.5·IQR (1977)

Anomalies are flagged, not dropped; rows failing validation are quarantined as rejected. 1356 reads (9.4%) lack coordinates and are excluded from spatial views.

Methods & authorities
  • (n,k)-dominance — 2 groups withheld (triggered by your top-1 dominance limit p = 15%).
    ESSnet/Eurostat SDC Handbook §4.2 (Hundepool et al.) — sensitive cells in magnitude tables
  • PII handling — identifiers are excluded from the analytic path; only disclosure-controlled aggregates are reported.
    NIST SP 800-122; NISTIR 8053
Published results
Customer class Total consumption (therms) Contributors Status
COMMERCIAL * — Withheld
INDUSTRIAL * — Withheld
RESIDENTIAL 1,817,189 995 Published
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Consumption profile

Total consumption by customer class — published groups (therms)
Consumption distribution & inequality
0.852
Gini coefficient
Gini 1912; Lorenz 1905
7.535
Coefficient of variation
std ÷ mean
1775
Median use / account (therms/yr)
across 1200 accounts
177
High outliers
Tukey 1.5·IQR
Lorenz curve — cumulative use vs. cumulative accounts
Percentiles (therms/yr)
10th836
25th1164
Median1775
75th3218
90th10304
Customer class × month
Total consumption — class (rows) × month (columns); blanks were suppressed (therms)
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Geography & spatial clustering

Random
Spatial pattern
not significant
0.092
Moran's I
expected -0.167
0.3
z-score
over 7 areas
0.7672
p-value
two-tailed
Total consumption by area (therms) — uncolored areas are suppressed

No significant spatial pattern — values look randomly placed.

1 hot spot (Getis-Ord Gi*, p < 0.05).

Global Moran's I, rook contiguity; normality-assumption inference. Moran (1950); Cliff & Ord (1973). Basemap © OpenStreetMap/Carto.
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Weather & seasonality

56.2%
Weather-sensitive (heating-driven)
ASHRAE G14; PRISM
100.0% / 0.0%
Heating / cooling split
of weather-driven use
—
Weather-normalized annual
restated at normal year
0.874
Model fit (R²)
degree-day regression

E = 417 + 2.5241·HDD  ·  base 65°F · 11 months

Seasonal use — 72.6% above winter baseline, peak Feb
Average monthly consumption vs. winter baseline (therms)
Winter-baseline (minimum-month) method. Standard seasonal decomposition.
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Benchmarking — Energy Use Intensity

85.3
Median EUI (kBtu/ft²/yr)
EPA ENERGY STAR; DOE/EIA CBECS
1200
Buildings benchmarked
floor area & ≥ 2 months
1 kWh = 3.412 kBtu; 1 therm = 100 kBtu (EIA)
reference constants v2024.1
EUI distribution across buildings (published classes)
By customer class (site EUI, kBtu/ft²/yr)
ClassBldgsp25Medianp75vs nat'l
RESIDENTIAL 995 53.785.4138.1 285%
COMMERCIAL 174 38.283.3172.7 119%
INDUSTRIAL 31 34.8108.8174.7 —
Within-dataset EUI percentiles vs. class peers. “vs nat'l” is coarse all-fuel context (CBECS 2018 / RECS 2020), not the ENERGY STAR 1–100 score. Small classes withheld.
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Energy burden & equity

Burden = annual energy cost ÷ tract median household income at $1.52/therms. Bands: ≤6% affordable · 6–10% moderate · >10% high (ACEEE).

4.11%
Median tract burden
across 33 tracts
1
High-burden tracts
> 10% of income
18.2%
Households high-burden
139 of 765
42
Tracts suppressed
below min-count
Energy burden by census tract (% of income)
Energy burden = annual energy cost ÷ median household income; ≤6% / 6–10% / >10% cut points (6% affordability from the Home Energy Affordability Gap [Fisher, Sheehan & Colton]; used by DOE/NREL LEAD & ACEEE — convention, not statute). Income: ACS 5-year B19013. Rate: EIA average retail price. Tract-level per DOE/NREL LEAD; metered-commodity burden is a lower bound on total home-energy burden.
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Measurement & verification (IPMVP Option C)

Baseline model fit on 5 months before Jul 2023; savings measured over the following 6 reporting months. Synthetic demo with no intervention — avoided energy near 0% is the method working correctly.

32.8%
Avoided energy
1937 therms/meter
5912
Adjusted baseline (CBL)
therms/meter expected
3975
Reporting actual
therms/meter metered
0.929
Baseline fit (R²)
degree-day model
Reporting period: metered actual vs. adjusted baseline (therms/meter)
IPMVP Option C (EVO 10000-1:2016); ASHRAE Guideline 14; base-65°F degree days (US EIA / NOAA).
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Differential privacy — an alternative release

An alternative to suppression: instead of hiding small groups, calibrated Laplace noise is added to each count (ε = 1.0, scale b = 1.0) so no individual's presence can be inferred while totals stay useful. Mean absolute error ±0.7 across 3 groups.

True vs. differentially private counts by customer class
Laplace mechanism, ε-differential privacy. Dwork, McSherry, Nissim & Smith (2006); Dwork & Roth (2014); US Census Bureau 2020 DAS.
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Appendix — policy & citations

Disclosure-control settings
Governing standard15/15 rule
Minimum group size (k)15
Dominance (top-n ≤ p)1 ≤ 0.15
Min accounts for models15
GroupingCustomer class
Standards & sources cited
  • k-anonymity — Sweeney (2002); ESSnet/Eurostat SDC Handbook
  • (n,k)-dominance — ESSnet SDC Handbook §4.2; CPUC 15/15
  • Inequality — Gini (1912); Lorenz (1905)
  • Spatial — Moran (1950); Cliff & Ord (1973)
  • Weather / M&V — ASHRAE Guideline 14; IPMVP Option C; PRISM
  • Benchmarking — EPA ENERGY STAR; DOE/EIA CBECS/RECS
  • Load — NREL UMP; BPA M&V Peak Demand
  • Burden — ACEEE; US Census ACS
  • Differential privacy — Dwork et al. (2006); US Census 2020 DAS
  • PII — NIST SP 800-122; NISTIR 8053; NIST SP 800-188
  • Methods & Formulas — every rule & analysis with its formula-as-implemented and primary citation

Synthetic sample data — for demonstration, not distribution. Generated by UnitTrack, a Polish Clover Solutions product · 2026-07-27 19:37.