TariffKit
An offline electricity tariff engine for pricing, billing, and energy-system integrations. The first data provider supports PG&E residential rate plans under NEM 3.0 / the Net Billing Tariff (NBT); the package identity is deliberately not tied to one utility or tariff program.
The complete active single-family residential portfolio is vendored: E-1, E-ELEC, E-TOU-C, E-TOU-D, and EV2-A. CARE, FERA, Medical Baseline/D-MEDICAL, and event-injected SmartRate adjustments are modeled separately from their underlying plans.
Under NBT your export credit is not a time-of-use schedule: it is an hourly Avoided Cost Calculator value that swings from about $0.06/kWh at midday to about $1.19/kWh on an August evening. Knowing what a kWh is worth right now, and what it will be worth over the next two days, is the input to every useful solar-and-battery dispatch decision.
from tariffkit import RateEngine
engine = RateEngine()
point = engine.price_now()
print(point.import_price.total) # $/kWh to draw from the grid
print(point.export_price.total) # $/kWh earned by exporting
print(point.spread) # positive => exporting beats self-consuming
curve = engine.forecast(hours=48)
for hour in curve.best_export_hours(3):
print(hour.start, hour.export_price.total)
Why it works offline
PG&E publishes 20 years of hourly export rates per vintage, as CPUC Resolution
E-5301 requires (roughly 40 MB of CSV per vintage). But that file is a lossless
expansion of a 576-cell matrix per year (12 months × 2 day types × 24 hours) per
component. tariffkit collapses it at build time, verifying losslessness cell by
cell, so the entire five-vintage dataset ships inside the wheel at 268 KiB
and every lookup is a few list indexes.
The retail side is similar: generated effective-dated tables hold every active schedule. E-TOU-D additionally selects weekday versus weekend/observed-holiday periods from the vendored tariff calendar.
Nothing here touches the network at runtime.
Documentation
| Configuration | Settings, CCA setup, reading your bill |
| Library | Embedding in Python |
| Named account profiles | Tracking a changing service agreement over time, importing PG&E statements |
| Bill calculator | Computing a cycle from interval meter data |
| MQTT | Publishing, with Home Assistant discovery |
| REST API | HTTP service |
| Home Assistant | Custom component, Energy dashboard, stacked component charts, account history, response actions, opt-in Predbat |
| Predbat | Installing TariffKit and Predbat together, end to end |
| Predbat on Sigenergy | Sigenergy SigenStor specifics: entity mapping, sign and unit conversions, control |
| Home Assistant quality checklist | Self-assessment against the Integration Quality Scale, with exemptions |
| Containers | Local Home Assistant development stack and API/MQTT deployment proposal |
| Maintaining rate data | Regenerating export rates, updating the retail tariff and CCA cards |
| Packaging strategy | Architecture decision, boundaries, and release model |
| Release procedure | Versioning, Trusted Publishing, verification, and recovery |
Works with
Prices are published in the shapes these already read, via either the custom component or the MQTT publisher — no template plumbing on your side. The two surfaces differ for EMHASS and Predbat: MQTT always publishes their attributes, while the custom component asks for a window on demand and keeps Predbat opt-in.
| Custom component | MQTT | |
|---|---|---|
| Home Assistant Energy dashboard | Import/export price entities | Import/export price entities |
| EMHASS | tariffkit.get_emhass_forecast action, called with any window |
load_cost_forecast / prod_price_forecast attributes, always published |
| Predbat | raw_today / raw_tomorrow attributes, only once enabled in options |
raw_today / raw_tomorrow attributes, always published |
See docs/home-assistant.md and docs/mqtt.md for setup of each.
Install
pip install tariffkit # core, zero dependencies
pip install 'tariffkit[mqtt]' # + MQTT publisher with Home Assistant discovery
pip install 'tariffkit[web]' # + FastAPI service
pip install 'tariffkit[secrets]' # + OS keyring credential storage
pip install 'tariffkit[statements]' # + reading local PG&E statement PDFs
pip install 'tariffkit[all]'
The Home Assistant integration has been submitted to the default HACS store, but approval queues can take months. Until it is approved, install TariffKit as a custom repository:
Or add it manually:
- Open HACS in Home Assistant.
- Select the three-dot menu → Custom repositories.
- Enter
https://github.com/eman/tariffkit, choose Integration, and select Add. - Search HACS for TariffKit, open it, and select Download.
- Restart Home Assistant, then add TariffKit from Settings → Devices & services → Add integration.
CLI
tariffkit now # current import/export price
tariffkit forecast --hours 48 # the upcoming curve
tariffkit forecast --format json # machine-readable
tariffkit mqtt --broker 192.168.1.100 # publish hourly, with HA discovery
tariffkit serve # REST API on :8000
tariffkit bill intervals.csv # compute a cycle from meter data
tariffkit info # which data is loaded, and from where
tariffkit account init home # track a service agreement's history
tariffkit account source home show ha # inspect profile grid-import/export entities
Configuration
Defaults target a PG&E-bundled residential customer. Point it at your own
service agreement via ~/.config/tariffkit/config.toml:
supplier = "bundled" # or "cca"
interconnection_year = 2026 # selects the NBT vintage and ACC Plus row
pto_date = "2026-06-03" # starts the nine-year rate lock
acc_plus_segment = "residential"
base_services_charge_tier = 3
TARIFFKIT_* environment variables override any file setting.
Long-lived PG&E, Home Assistant, InfluxDB, and MQTT credentials can be stored
outside that file with tariffkit credentials set; see
Configuration.
What the numbers include
- Import price is the marginal per-kWh cost: generation + distribution for
the season and period, plus the flat riders. The AB 205 Base Services Charge
is a fixed $/day amount and is deliberately excluded: folding it into a
$/kWh figure would corrupt any marginal dispatch decision. Read it separately
via
engine.daily_fixed_charge(). - Export credit is the generation component plus the delivery component,
plus your ACC Plus adder. Values past your nine-year lock are still returned
but flagged
locked=False; PG&E publishes them for illustration only.
Edge cases in PG&E's published data
Found by round-tripping the vendored matrices against all 1.75 million source rows. The library handles each; they are documented because they are surprising.
- The autumn DST hour. The fall-back day has 25 real hours but only 24 rate
labels. PG&E gives the repeated 01:00 PST the
HS2label, so it is priced as 2am. Pricing it by wall-clock hour returns the wrong value for that hour. - Far-future drift. From 2036 onward PG&E's own hour labels stop tracking
Pacific daylight time, and NBT25/26/00 duplicate some holidays onto the
following day. Each vintage records the last year verified exact; prices past
it are returned with
exact=False. Every year inside a nine-year rate lock is exact, and those years are already published as illustrative only. - Vintages disagree about holidays in those same late years, so the holiday calendar used for a lookup is the one embedded in that vintage's own file.
- Only the June 2026 tariff sheets are vendored, for each of the three schedules. Earlier timestamps raise rather than silently back-dating current rates onto an older billing period.
- E-TOU-C's baseline credit is not in the marginal price. It applies to the
first N kWh of a cycle, which is a quantity rather than a time, so
price_atreports it asbaseline_creditand the billing engine applies it.
CCA customers
If a Community Choice Aggregator supplies your generation, PG&E still delivers, and under NEM 3.0 you receive only the delivery component of the export credit from PG&E; generation compensation comes from the CCA.
An MCE rate card is vendored (generation by season/period, the Cost Relief Credit, Deep Green premium, and the 10% Solar Bonus Credit):
supplier = "cca"
[cca]
name = "MCE"
rate_card = "mce"
pcia_rate = 0.03476 # $/kWh, from your bill
franchise_fee_surcharge = 0.00042 # $/kWh, from your bill
For other CCAs, supply generation_rates directly; see
docs/configuration.md. Until generation rates and a
franchise fee are configured, CCA mode returns delivery-only prices flagged
complete = False rather than quietly understating your rates.
Note that a CCA customer's PCIA is a charge, while a bundled customer's is a credit, so CCA service can cost several cents per kWh more on import.
Keeping rates current
Every vendored dataset is regenerated from the document that publishes it, by
tools.regen. Nothing is hand-transcribed and nothing is hand-edited.
python -m tools.regen # rebuild every dataset
python -m tools.regen --check # exit 1 if a publisher moved
python -m tools.regen tariff --for-date 2025-12-15 # rebuild a superseded vintage
python -m tools.regen.export --download # the 843 MB export-rate archive
Export matrices come from PG&E's CSV archive, which is large enough to have its own entry point; everything else comes from a published PDF. Nothing is written unless the rendered file survives being read back by the library code that will consume it, so a generator that drifts from the schema fails instead of shipping.
A weekly CI job runs --check, so a rate change surfaces as a failing build
rather than as silent drift. Export files are updated by October 1 of any
year the CPUC adopts a new Avoided Cost Calculator; retail rates change more
often, via advice letters — three times in the first half of 2026 alone — which
is why a superseded vintage can be rebuilt from the filing that adopted it. See
docs/data.md.
Data sources
See docs/data.md for the source of every vendored table and why OpenEI's URDB is deliberately not used.
License
MIT
Metadata
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Total release size: 1.1 MB
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