NZ residential electricity demand — diurnal load shape & three-slice fractions (compiled synthesis)
Compiled research — triangulated estimates, not measured fractions
A Perplexity deep-research synthesis. No single NZ source publishes the share of daily household electricity in these three time windows — the fractions are derived by triangulating GREEN Grid, the EECA/EPECentre PV-calculator database (~18,000 ICPs), the EECA 2024 solar-value study, and BRANZ HEEP/BEES/EEUD end-use shares. Treat as evidence-informed estimates (data_quality: medium). Seasonal variation is large and ripple-control penetration is the single biggest uncertainty.
Summary
Derives the fraction of a typical NZ household’s daily electricity consumption falling in three time-of-day slices — solar_day (09–15, ~6 h), evening_peak (17–21, ~4 h), night_base (the remaining ~14 h) — for the Neobiome Intelligence electricity engine. Best total-load annual estimate 0.22 / 0.38 / 0.40; heating-stripped (space + water heating removed) 0.27 / 0.34 / 0.39 — the frame matching the model’s elec_nonheat demand. Strong seasonal swing (winter evening sharper). Replaces the model’s 0.30/0.40/0.30 placeholder. Provides the “Research B” option-set for the workbook profiles sheet; companion to CR_020 (Research A), which estimates a lower evening fraction.
Key claims
- claim: "Best annual-average TOTAL-load three-slice split of daily NZ household electricity is ~0.22 / 0.38 / 0.40 (solar_day 09–15 / evening_peak 17–21 / night_base rest), triangulated from GREEN Grid, EECA/EPECentre and BRANZ end-use data — no single NZ source publishes the exact fractions."
- claim: "Heating-stripped three-slice split (space + water heating, ~62% of residential electricity, removed) is ~0.27 / 0.34 / 0.39 — the appropriate frame for a model that handles space and water heating as separate domains."
- claim: "Seasonal variation is large: winter ~0.17 / 0.42 / 0.41 vs summer ~0.26 / 0.31 / 0.43; the evening-peak power roughly doubles winter-over-summer (GREEN Grid ~0.94 kW vs ~0.44 kW), driven by space heating."
- claim: "About 38% of the winter evening peak (17–21) is heating — ~21% identifiable space heating + ~17% hot water — per the GREEN Grid peak decomposition; stripping heating flattens and lowers the evening peak."
- claim: "NZ residential load data is almost exclusively per-ICP (connection), gross demand (pre-solar); the largest source is the EECA/EPECentre PV Solar Calculator database (~18,000 ICPs, 10 regions, 32 archetypes; Wood et al. 2017), larger and more representative than GREEN Grid (n=44, heat-pump-over-represented)."Diurnal shape (GREEN Grid period averages, per dwelling)
| Period | Hours | Winter kW | Summer kW |
|---|---|---|---|
| Morning 07–09 | 2 | 0.76 | 0.58 |
| Daytime 09–17 | 8 | 0.48 | 0.33 |
| Evening 17–21 | 4 | 0.94 | 0.44 |
| Night 21–07 | 10 | 0.41 | 0.24 |
Three-slice fractions
| Slice | Total annual | Winter | Summer | Heating-stripped |
|---|---|---|---|---|
| solar_day (09–15) | 0.22 | 0.17 | 0.26 | 0.27 |
| evening_peak (17–21) | 0.38 | 0.42 | 0.31 | 0.34 |
| night_base (rest, 14h) | 0.40 | 0.41 | 0.43 | 0.39 |
Neobiome Intelligence relevance
Feeds the electricity engine’s profiles → demand_distribution (stages ① E1 / ② E2). Because the model splits space + water heating into a separate domain, the heating-stripped fractions are the conceptually-correct shape for elec_nonheat. Carried as the “Research B” option in the workbook demand-shape selector, alongside CR_020 (Research A), which reconstructs a lower evening fraction (~0.20–0.26) from the same GREEN Grid period-averages — the two diverge on the evening peak (the load-bearing number for battery sizing), so both are held pending primary-data resolution (RT_224/RT_225).
Conflict with already-ingested end-use shares
CR_019 cites EEUD 2022 residential-electricity end-use as space heating 32% / water 30%, whereas the ingested RD_007 gives space ~20% / water ~27%. Treat CR_019’s heating share (and the heating-stripped fractions derived from it) as the synthesis’s own (medium confidence); RD_007 remains the primary for end-use shares.
Research targets
Documents to retrieve
- RT_224 — EECA/EPECentre PV Solar Calculator load-profile database (Wood, Miller, McNab, Lemon 2017; ~18,000 ICPs, 10 regions, 32 archetypes; ir.canterbury.ac.nz) — the largest NZ residential diurnal-profile source; per-ICP gross; openly retrievable; the best path to a sourced demand shape.
- RT_225 — EECA 2024 Miller, Understanding the value of residential solar PV & storage in NZ + Appendix One (Assessing residential solar at different time scales) — half-hourly NZ demand + solar across 4 main centres.
Research gaps
- RT_226 — A NZ heating-stripped (appliance-only; space + water heating excluded) residential diurnal load profile — the exact shape the NI
elec_nonheatcell needs; not published openly (derivable from GREEN Grid circuit-level microdata or EPECentre archetypes).
Connections
Links to
Sources (1): RD_007
Referenced by
Sources (3): CR_020 · OT_061 · RD_021
EDT domains (1): D01: Renewable Energy & Storage Systems