From Smart Meter to Customer Segmentation: Using Energy API to Power Personalized Tariffs and Targeted EE Programs for Utilities

Personalized energy tariffs and targeted efficiency programs start with a deceptively hard question: what is a customer’s real cost-to-serve profile over time? You need to combine smart meter usage with dynamic wholesale prices, account for fuel switching risks, recognize cross-commodity exposure, and even weigh the carbon intensity of the grid at the times customers actually consume electricity. Stitching these signals together from multiple sources is where most projects stall: each data portal publishes on a different cadence, uses incompatible formats, and has its own quirks.

This post shows how to go from smart meter data to production-grade customer segmentation using a single, normalized REST surface: Energy API. Whether you’re building a tariff optimizer, a time-of-use (TOU) selector, or an outreach engine that nudges cohorts into the most carbon-efficient consumption windows, the workflow is the same: enrich interval usage with intraday electricity curves, overlay broader market context (gas, oil, carbon, coal), and quantify carbon intensity by geography and time. We’ll walk through endpoints, responses, field meanings, and practical implementation choices that keep your pipeline reliable and fast.

If you’re a utility, an energy retailer, a fintech building bill transparency tools, or an ESG team quantifying Scope 2 emissions in near real time, this article will help you move from raw interval meter reads to differentiated customer experiences—without weeks of ETL and brittle scraping code.

Why Energy API

Utility teams and energy developers often spend more time normalizing data than building features. Government and market operator portals are invaluable, but they are not product-friendly: naming conventions differ (BRENT vs DCOILBRENTEU), units change (USD/barrel vs EUR/MWh), publishing times drift by source, and APIs vary widely in structure. Energy API eliminates this integration tax by consolidating wholesale energy market data from official sources (e.g., OMIE, ENTSO-E, ESIOS, EIA/FRED, Ember) behind a single, consistent JSON schema.

Four developer-centric differentiators matter in practice:

• One normalized REST interface for electricity, gas, oil, coal, carbon, and grid carbon intensity. You can query TTF gas, Brent crude, EU ETS allowances, and German day-ahead electricity in the same call and receive a predictable JSON shape. That makes it trivial to enrich usage cohorts with multi-commodity context for risk scoring or education.
• Intraday electricity curves where sources publish them. For customer segmentation, the hourly (or 15-minute) shape is critical. Matching each interval of smart meter data against the correct wholesale interval price enables accurate cost and margin attribution, and lets you simulate “what if” migrations to different tariffs.
• Unified historical and forecast coverage. Historical series endpoints are formatted for charting and analytics, while forecast endpoints return deterministic day-ahead auction results for supported electricity markets. Your tariff selection logic can look backward for behavior and forward for cost.
• Operational visibility you can wire into your observability stack. The provider status endpoint gives you last-fetch health by data source so you can alert and fall back gracefully if a publisher delays or revises data. In production, that saves late-night pages and makes your pipeline resilient.

The result: instead of reconciling dozens of edge cases, you ship features—segmentation, tariff personalization, and efficiency program targeting—in days, not weeks.

Quick Start

Base URL:

https://energy-api.com/api/v1

Let’s pull the latest values for a cross-commodity snapshot in a single request. This is useful for contextualizing electric prices with gas and carbon, especially for hedging analysis and program messaging.

curl -G https://energy-api.com/api/v1/latest \
--data-urlencode "symbols=OMIE_ES_DA,TTF_GAS,EUA_CO2,BRENT_CRUDE" \
--data-urlencode "api_key=YOUR_API_KEY"

Example response (abridged for readability):

{
"success": true,
"date": "2026-06-11",
"base": "MIXED",
"rates": {
"OMIE_ES_DA": 89.73,
"TTF_GAS": 38.15,
"EUA_CO2": 67.40,
"BRENT_CRUDE": 74.82
},
"dates": {
"OMIE_ES_DA": "2026-06-11",
"TTF_GAS": "2026-06-11",
"EUA_CO2": "2026-06-11",
"BRENT_CRUDE": "2026-06-11"
},
"currencies": {
"OMIE_ES_DA": "EUR",
"TTF_GAS": "EUR",
"EUA_CO2": "EUR",
"BRENT_CRUDE": "USD"
}
}

Key fields:

• success: Boolean indicator for easy flow control.
• date: Canonical date of the consolidated response; see symbol-specific dates under dates.
• rates: Latest value by symbol. Query different commodities together with one shape.
• dates: Source-specific last published date per symbol. Use this to detect staleness.
• currencies: Currency per symbol for correct normalization downstream.

This is already enough to create a “market context” widget in your segmentation UI or customer portal.

Core Endpoints for Personalized Tariffs and Segmentation

You can build a complete enrichment pipeline with a handful of endpoints. Below, we detail the most relevant ones to turn interval usage into actionable segments and tariff recommendations.

1) Discover Symbols: GET /symbols

Before you build, enumerate what’s available and filter by category, country, or provider to keep your system configurable.

curl -G https://energy-api.com/api/v1/symbols \
--data-urlencode "category=electricity" \
--data-urlencode "api_key=YOUR_API_KEY"

Sample response:

{
"success": true,
"count": 3,
"symbols": [
{
"symbol": "OMIE_ES_DA",
"name": "OMIE Spain Day-Ahead",
"category": "electricity",
"country_code": "ES",
"currency_code": "EUR",
"frequency": "daily",
"description": "OMIE day-ahead auction price for Spain."
},
{
"symbol": "EPEX_DE_DA",
"name": "EPEX Germany Day-Ahead",
"category": "electricity",
"country_code": "DE",
"currency_code": "EUR",
"frequency": "daily",
"description": "EPEX SPOT day-ahead price for Germany."
},
{
"symbol": "PVPC_ES_2TD",
"name": "Spain PVPC (2-period) Reference",
"category": "electricity",
"country_code": "ES",
"currency_code": "EUR",
"frequency": "hourly",
"description": "Spanish PVPC retail reference, 2-period tariff."
}
]
}

What to do with it:

• Drive product configuration and symbol selection via metadata (country_code, frequency).
• Map smart meter geography to appropriate electricity symbols.
• Gate feature flags (e.g., enable intraday curves only for symbols that support them).

2) Intraday Electricity Curves: GET /electricity/hourly

For tariff personalization, you’ll align each smart meter interval with the matching wholesale price interval. This endpoint returns the full hourly (or 15-minute where available) curve for a given symbol and date.

curl -G https://energy-api.com/api/v1/electricity/hourly \
--data-urlencode "symbol=OMIE_ES_DA" \
--data-urlencode "date=2026-06-11" \
--data-urlencode "api_key=YOUR_API_KEY"

Example response:

{
"success": true,
"symbol": "OMIE_ES_DA",
"date": "2026-06-11",
"currency": "EUR",
"unit": "MWh",
"interval": "hourly",
"values": [
{"timestamp": "2026-06-11T00:00:00Z", "price": 74.12},
{"timestamp": "2026-06-11T01:00:00Z", "price": 71.88},
{"timestamp": "2026-06-11T02:00:00Z", "price": 69.10},
{"timestamp": "2026-06-11T03:00:00Z", "price": 66.45}
// ... 24 items total (or 96 for 15-min markets)
],
"source": "OMIE"
}

Key fields:

• values[].timestamp: ISO UTC stamps; align your smart meter intervals to UTC or to the market’s local offset consistently.
• values[].price: Wholesale price in currency per MWh; convert to kWh if you calculate retail bill components (divide by 1000).
• interval: “hourly” vs “15m” informs your resampling logic.
• source: Auditable provenance for compliance.

Practical tip: When pairing with smart meter data, ensure your meter’s local time and DST handling are correct. If your meter records local time, transform timestamps to UTC before joining.

3) Day-Ahead Forecast (Deterministic): GET /forecast

Day-ahead auctions publish results for the next day. Use this endpoint to calculate tomorrow’s expected cost-to-serve for your portfolio and to simulate tariff options proactively.

curl -G https://energy-api.com/api/v1/forecast \
--data-urlencode "symbol=OMIE_ES_DA" \
--data-urlencode "api_key=YOUR_API_KEY"

Example response:

{
"success": true,
"symbol": "OMIE_ES_DA",
"date": "2026-06-12",
"interval": "hourly",
"currency": "EUR",
"unit": "MWh",
"values": [
{"timestamp": "2026-06-12T00:00:00Z", "price": 70.05},
{"timestamp": "2026-06-12T01:00:00Z", "price": 68.55}
// ...
],
"note": "Deterministic auction results (not a predictive model)."
}

With smart meter profiles (or cluster medians), you can compute next-day expected wholesale costs per customer cohort and surface the cheapest TOU option before customers consume.

4) Carbon Intensity by Country: GET /carbon-intensity

Grid carbon intensity varies intraday. If you’re segmenting customers for efficiency programs or carbon-aware demand response, this endpoint gives you the intensity in gCO2eq/kWh for a country and date range.

curl -G https://energy-api.com/api/v1/carbon-intensity \
--data-urlencode "country=DE" \
--data-urlencode "api_key=YOUR_API_KEY"

Sample response:

{
"success": true,
"country": "DE",
"unit": "gCO2eq/kWh",
"frequency": "hourly",
"values": [
{"timestamp": "2026-06-11T00:00:00Z", "intensity": 385},
{"timestamp": "2026-06-11T01:00:00Z", "intensity": 372}
// ...
],
"source": "Ember/ENTSO-E"
}

Pairing hourly price with hourly carbon intensity lets you build a “two-axis” segmentation: price-elastic customers get TOU incentives, while climate-motivated customers receive nudges to shift into lower-intensity hours.

5) Cost Estimate (Wholesale) for Back-of-Envelope: POST /cost-estimate

Need a quick monthly cost estimate per cohort? This endpoint multiplies the latest price by a kWh-per-month assumption. While it doesn’t include taxes or network charges, it’s a fast way to sanity-check offers or filter candidates before more detailed bill simulation.

curl -X POST https://energy-api.com/api/v1/cost-estimate \
-H "Content-Type: application/json" \
-d '{
"symbol": "OMIE_ES_DA",
"kwh_per_month": 250
}' \
--data-urlencode "api_key=YOUR_API_KEY"

Example response:

{
"success": true,
"symbol": "OMIE_ES_DA",
"kwh_per_month": 250,
"latest_price": 89.73,
"currency": "EUR",
"unit": "MWh",
"estimate": {
"wholesale_only": 22.43
},
"note": "Wholesale-only estimate; excludes taxes, network charges, and hourly usage shaping."
}

Pro tip: Use cost-estimate to triage cohorts, then run a full intraday simulation (electricity/hourly × interval usage) for shortlisted customers or offers.

Endpoint Reference Deep Dive (All Features, Field Meanings, and Practical Use)

Below is a complete tour of the Energy API surface, with pragmatic guidance on when to use each feature and how to interpret responses in customer segmentation, tariff modeling, and efficiency program design.

1. GET /symbols

Purpose: Discover available instruments across electricity, gas, oil, coal, carbon, and carbon intensity. Filter by category, base currency preference, or provider to drive UI configuration and routing logic.

• Key params: base (e.g., EUR), category (e.g., electricity), provider (e.g., omie, eia, fred).
• Business value: Prevent hardcoding; build dynamic symbol menus and maintainable routing.
• Tip: Cache symbol metadata; refresh daily or when you deploy.

2. GET /latest

Purpose: Latest price snapshot for one or more symbols. Perfect for dashboard tiles, risk context, and price-aware messaging. Multiple commodities in one call is a major ergonomics win.

• Params: symbols (comma-separated), base (optional), category (optional).
• Response fields: rates, currencies, and dates per symbol for staleness detection.
• Usage: Pair electricity with EUA_CO2 to communicate clean/cheap correlations (or lack thereof).

3. GET /historical

Purpose: Backfill a specific past date when doing “as of” analysis (e.g., reconstructing a bill or investigating an anomaly). If a date is non-publishing, you still get the nearest prior.

• Params: date, symbols.
• Use case: Retroactive tariff comparison for onboarding or churn analysis.

curl -G https://energy-api.com/api/v1/historical \
--data-urlencode "date=2025-09-15" \
--data-urlencode "symbols=BRENT_CRUDE,TTF_GAS" \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"date": "2025-09-15",
"base": "MIXED",
"rates": {
"BRENT_CRUDE": 71.45,
"TTF_GAS": 36.20
},
"currencies": {
"BRENT_CRUDE": "USD",
"TTF_GAS": "EUR"
}
}

Field meanings:

• rates: As-of adjusted values; useful when the publishing calendar has gaps (weekends/holidays).
• currencies: Keep a consistent conversion policy in your analytics stack.

4. GET /timeseries

Purpose: Pull a historical series across a time window, keyed by date. Ideal for cohort trend analysis, seasonality modeling, and charting.

• Params: start, end, symbols, base.
• Tip: Align windowing with your program cadence (e.g., rolling 90 days for TOU selection logic).

curl -G https://energy-api.com/api/v1/timeseries \
--data-urlencode "start=2025-01-01" \
--data-urlencode "end=2025-03-31" \
--data-urlencode "symbols=BRENT_CRUDE,TTF_GAS" \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"base": "MIXED",
"start_date": "2025-01-01",
"end_date": "2025-03-31",
"rates": {
"BRENT_CRUDE": {
"2025-01-02": 76.30,
"2025-01-03": 75.90
},
"TTF_GAS": {
"2025-01-02": 46.80,
"2025-01-03": 47.10
}
},
"frequencies": {
"BRENT_CRUDE": "daily",
"TTF_GAS": "daily"
},
"currencies": {
"BRENT_CRUDE": "USD",
"TTF_GAS": "EUR"
}
}

Use these fields to build stable time-indexed data frames. frequencies helps you resample correctly when switching across instruments.

5. GET /fluctuation

Purpose: Compute change over a period (start_value, end_value, absolute, percent) without manual looping. Useful for risk alerts and explaining price movements to customers in context (“gas down 12% since last bill”).

• Params: start, end, symbols, base.
• Best practice: Use to trigger comms for cohorts likely to benefit from switching.

curl -G https://energy-api.com/api/v1/fluctuation \
--data-urlencode "start=2026-05-01" \
--data-urlencode "end=2026-06-01" \
--data-urlencode "symbols=TTF_GAS,EUA_CO2" \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"period": {"start": "2026-05-01", "end": "2026-06-01"},
"symbols": {
"TTF_GAS": {
"start_value": 41.25,
"end_value": 38.15,
"change": -3.10,
"change_pct": -7.51
},
"EUA_CO2": {
"start_value": 70.90,
"end_value": 67.40,
"change": -3.50,
"change_pct": -4.94
}
}
}

Practical use: Segment customers for educational messaging that ties recent market movements to actionable efficiency steps.

6. GET /ohlc

Purpose: Candle series (weekly/monthly/quarterly) for volatility analysis and long-horizon dashboards. Ideal for portfolio steering and explaining high-level trends to non-technical stakeholders.

• Params: symbols, period (weekly|monthly|quarterly), start, end.
• Business value: Plug directly into chart libraries and risk analytics.

curl -G https://energy-api.com/api/v1/ohlc \
--data-urlencode "symbols=BRENT_CRUDE,WTI_CRUDE" \
--data-urlencode "period=monthly" \
--data-urlencode "start=2025-01-01" \
--data-urlencode "end=2025-06-30" \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"period": "monthly",
"data": {
"BRENT_CRUDE": [
{"period": "2025-01", "open": 77.10, "high": 79.80, "low": 74.90, "close": 76.30, "data_points": 22},
{"period": "2025-02", "open": 76.40, "high": 78.50, "low": 74.60, "close": 75.90, "data_points": 20}
],
"WTI_CRUDE": [
{"period": "2025-01", "open": 71.00, "high": 73.10, "low": 69.80, "close": 70.50, "data_points": 22}
]
}
}

Field tips: data_points indicates how many inputs contributed to the candle; use it to judge completeness in partial months.

7. GET /electricity/latest

Purpose: Fetch all electricity symbols’ latest values at once, or filter by country for a localized dashboard.

• Params: country (ISO-2), base.
• Use: Power a “market pulse” panel for your tariff modeling team.

curl -G https://energy-api.com/api/v1/electricity/latest \
--data-urlencode "country=DE" \
--data-urlencode "api_key=YOUR_API_KEY"

Response shape mirrors /latest but scoped to electricity.

8. GET /electricity/hourly

We covered this above. This is your workhorse for aligning smart meter intervals with wholesale prices for accurate cost modeling and tariff simulation.

9. GET /electricity/pvpc

Purpose: Hourly Spanish PVPC retail reference prices for a given date. If you’re comparing wholesale-based estimates with regulated retail references, this gives you the official hourly retail benchmark.

curl -G https://energy-api.com/api/v1/electricity/pvpc \
--data-urlencode "date=2026-06-11" \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"date": "2026-06-11",
"currency": "EUR",
"interval": "hourly",
"tariffs": [
{
"symbol": "PVPC_ES_2TD",
"values": [
{"timestamp": "2026-06-11T00:00:00Z", "price": 0.1423},
{"timestamp": "2026-06-11T01:00:00Z", "price": 0.1398}
]
}
],
"note": "Retail reference values; may include regulated components."
}

Practical use: Compare your personalized offers against the PVPC benchmark and justify savings transparently.

10. GET /gas/latest

Purpose: Snapshot TTF_GAS (EU) and HENRY_HUB (US) together. Gas influences electricity marginal prices in many hours; include it to explain wholesale drivers to stakeholders and in your risk models.

curl -G https://energy-api.com/api/v1/gas/latest \
--data-urlencode "api_key=YOUR_API_KEY"

Response includes TTF_GAS, HENRY_HUB, with currencies and last-published dates.

11. GET /emissions/latest

Purpose: Latest EUA_CO2 price. Carbon allowance prices are increasingly part of risk and cost narratives. Use to contextualize long-run retail strategy.

curl -G https://energy-api.com/api/v1/emissions/latest \
--data-urlencode "api_key=YOUR_API_KEY"

Use case: Display EUA alongside electricity when customers are climate-motivated; pairs well with carbon-intensity series.

12. GET /coal/latest

Purpose: Latest coal markers such as COAL_ROTTERDAM (API2) and COAL_NEWCASTLE. For markets with coal in the generation mix, these series help explain intensity and pricing correlations.

curl -G https://energy-api.com/api/v1/coal/latest \
--data-urlencode "api_key=YOUR_API_KEY"

Tip: Combine with carbon intensity to show why certain hours are dirtier and to motivate targeted load shifting programs.

13. GET /carbon-intensity

We covered this above. It is central to segmentation strategies that combine price and emissions signals at the interval level.

14. GET /forecast

Covered above. Deterministic day-ahead results let you advise customers proactively.

15. POST /cost-estimate

Covered above. Ideal for fast triage before full interval simulations.

16. GET /status

Purpose: Operational visibility into last-fetch status per data provider. In production pipelines, wire this into your health checks and alerting. If a source delays publication, you can temporarily fall back to the previous day or pause cohort refreshes.

curl -G https://energy-api.com/api/v1/status \
--data-urlencode "api_key=YOUR_API_KEY"

{
"success": true,
"providers": [
{
"name": "OMIE",
"last_success_at": "2026-06-11T10:15:03Z",
"last_attempt_at": "2026-06-11T10:15:03Z",
"status": "ok"
},
{
"name": "ENTSO-E",
"last_success_at": "2026-06-11T09:58:11Z",
"last_attempt_at": "2026-06-11T09:58:11Z",
"status": "ok"
},
{
"name": "EIA",
"last_success_at": "2026-06-10T22:30:00Z",
"last_attempt_at": "2026-06-10T22:30:00Z",
"status": "ok"
}
]
}

Use last_success_at to detect upstream delays and switch your app’s UI into a “data delayed” state gracefully.

Implementation Blueprint: From Smart Meter to Segmentation

Here’s a reference workflow you can adapt to your stack:

• Normalize intervals: Convert smart meter timestamps to UTC. Deduplicate and handle DST gaps/overlaps.
• Fetch intraday price curves: GET /electricity/hourly for each customer’s market symbol and date window. If you have millions of intervals, batch by date and symbol, not by customer.
• Join usage × price: Compute interval wholesale cost (kWh × EUR/MWh ÷ 1000). Aggregate by TOU bucket to profile sensitivity.
• Overlay carbon intensity: GET /carbon-intensity for the customer’s country; compute interval emissions (kWh × gCO2eq/kWh).
• Add market context: Pull gas, oil, coal, and EUA via /latest or /timeseries for explanatory analytics and cohort messaging.
• Forecast tomorrow: GET /forecast to simulate next-day cost on representative profiles; recommend best-fit tariff proactively.
• Operational guardrails: Monitor GET /status; if delayed, re-use last known curves and annotate UIs accordingly.

Performance practices:

• Cache symbol metadata and recent intraday curves; invalidate by date.
• Vectorize joins (e.g., groupby on timestamps) and prefer columnar formats (Parquet) downstream.
• Parallelize by date rather than by customer to maximize re-use of the same market curve across many customers under the same tariff zone.

Developer Code Examples

cURL: Multi-Commodity Latest in One Call

curl -G https://energy-api.com/api/v1/latest \
--data-urlencode "symbols=EPEX_DE_DA,TTF_GAS,EUA_CO2,COAL_ROTTERDAM" \
--data-urlencode "api_key=YOUR_API_KEY"

Python: Join Smart Meter Intervals with Intraday Prices

import requests
import pandas as pd

BASE = "https://energy-api.com/api/v1"

def get_intraday(symbol, date, api_key):
r = requests.get(
f"{BASE}/electricity/hourly",
params={"symbol": symbol, "date": date, "api_key": api_key},
timeout=30
)
r.raise_for_status()
data = r.json()
return pd.DataFrame(data["values"]).assign(price_unit=data.get("unit", "MWh"))

# Example smart meter data (UTC, kWh)
meter = pd.DataFrame({
"timestamp": pd.date_range("2026-06-11", periods=24, freq="H", tz="UTC"),
"kwh": [0.8, 0.7, 0.6] + [1.0]*21
})

api_key = "YOUR_API_KEY"
curve = get_intraday("OMIE_ES_DA", "2026-06-11", api_key)
curve["timestamp"] = pd.to_datetime(curve["timestamp"], utc=True)

df = meter.merge(curve, on="timestamp", how="left")
# Convert EUR/MWh to EUR/kWh
df["eur_per_kwh"] = df["price"] / 1000.0
df["wholesale_cost_eur"] = df["kwh"] * df["eur_per_kwh"]

print(df[["timestamp","kwh","price","wholesale_cost_eur"]].head())

JavaScript: Forecast Tomorrow’s Cost for a Cohort Median Profile

async function fetchJSON(url, params) {
const qs = new URLSearchParams(params);
const res = await fetch(`${url}?${qs.toString()}`);
if (!res.ok) throw new Error(`HTTP ${res.status}`);
return res.json();
}

async function forecastCost(symbol, kwhByHour, apiKey) {
const data = await fetchJSON("https://energy-api.com/api/v1/forecast",
{ symbol, api_key: apiKey }
);

const prices = data.values; // hourly timestamps with EUR/MWh
let total = 0.0;

for (const row of prices) {
const hour = new Date(row.timestamp).getUTCHours();
const kwh = kwhByHour[hour] || 0;
total += kwh * (row.price / 1000.0); // EUR/kWh
}

return { date: data.date, estimated_wholesale_eur: Number(total.toFixed(2)) };
}

// Example: simple median cohort profile
const kwhByHour = { "18": 1.4, "19": 1.6, "20": 1.7, "21": 1.3 };
forecastCost("OMIE_ES_DA", kwhByHour, "YOUR_API_KEY")
.then(console.log)
.catch(console.error);

Error Handling and Troubleshooting

Energy API returns descriptive errors with a consistent shape. Handle them centrally and surface actionable messages in logs or UIs.

• 401 — Missing or invalid api_key. Ensure credentials are correctly passed.
• 404 — No data for the given symbols/date. Check date windows, symbol typos, and publisher calendars.
• 422 — Validation error (missing params, invalid format). Validate input types before calling.
• 429 — Rate limit exceeded. Implement exponential backoff and retry with jitter.

Error response shape:

{
"success": false,
"error": "Human-readable message."
}

Operational best practices:

• Check /status before nightly batch jobs. If a provider is delayed, annotate dashboards and proceed with the prior day where acceptable.
• For intraday joins, guard against incomplete curves. Validate count of expected intervals (24 hourly or 96 × 15-minute) before billing simulations; if short, retry periodically.
• Keep a small cache of previous valid curves to ensure your UX remains responsive during transient upstream delays.

Real-World Use Cases

1) Personalized Tariff Engine for Residential Customers

Goal: Assign each customer the most cost-effective TOU product based on historic interval usage and tomorrow’s day-ahead curve. You’ll fetch intraday prices via GET /electricity/hourly for each day in a calibration window (e.g., last 30 days), compute wholesale spend by TOU bucket, then query GET /forecast to simulate expected cost tomorrow across candidate tariffs. Tie-break with customer preferences (e.g., limit peak differentials).

Endpoints: /electricity/hourly, /forecast, optionally /carbon-intensity to layer an emissions-aware tie-breaker for customers who value sustainability.

2) Targeted Energy Efficiency (EE) Outreach by Cohort

Goal: Build cohorts who would benefit most from shifting load out of high-price and high-intensity hours. First, compute each customer’s “peak exposure index” using intraday price joins. Then, enrich each interval with GET /carbon-intensity to measure avoided emissions if the customer moves 10–20% of peak load into off-peak windows. Prioritize outreach to cohorts with the highest combined cost and carbon savings.

Endpoints: /electricity/hourly, /carbon-intensity, /fluctuation (to contextualize recent changes), /latest (to coordinate campaign timing with market conditions).

3) Executive ESG Dashboard with Cross-Commodity Context

Goal: Present a single-pane-of-glass view for leadership—electricity benchmarks, gas and oil context, coal markers, EUA_CO2, and grid carbon intensity—all normalized. Use GET /latest for a quick snapshot, GET /timeseries for charts, GET /ohlc for monthly trend visualization, and GET /status to display source health badges. This dashboard underpins informed decisions on tariff mix, hedging posture, and EE budget allocations.

Endpoints: /latest, /timeseries, /ohlc, /carbon-intensity, /status.

FAQ

How often does the TTF gas price update?

TTF_GAS is published on an exchange schedule and reflected by Energy API shortly after upstream publication. Use the dates field in /latest or the frequencies metadata to verify the most recent publishing day, and consult /status to confirm upstream health before running batch jobs.

Can I get historical energy prices going back 5 years?

Use GET /timeseries with an appropriate start and end window to retrieve historical series. Coverage varies by symbol and provider; rely on the frequencies and returned date keys to determine completeness. For long-range charts, GET /ohlc is an efficient alternative.

Does the API support multiple commodities in one response?

Yes. Pass multiple symbols to GET /latest or GET /timeseries and receive a unified JSON schema keyed by symbol. This is ideal for contextualizing electricity alongside gas, oil, coal, and carbon in a single, lightweight request.

How do I simulate tomorrow’s bill impact before customers consume?

Use GET /forecast for a supported electricity symbol to retrieve the day-ahead hourly curve, then multiply interval prices by a representative kWh profile (e.g., a cohort median). Convert from EUR/MWh to EUR/kWh by dividing by 1000, then aggregate into tariff buckets for “what if” comparisons.

What’s the best way to join carbon intensity with price?

Fetch hourly carbon intensity for the customer’s country using GET /carbon-intensity and join on the UTC timestamp. Compute interval emissions (kWh × gCO2eq/kWh) alongside interval cost. This powers dual-optimization strategies for price and emissions.

Conclusion + CTA

Personalized tariffs and targeted efficiency programs demand reliable, granular market data. The bottleneck isn’t the math—it’s wrangling disparate sources, reconciling units, and handling publishing calendars at scale. Energy API removes that friction by unifying electricity, gas, oil, coal, carbon, and grid carbon intensity behind a single, predictable JSON schema with production-ready endpoints for intraday curves, historical series, deterministic day-ahead forecasts, and operational health checks.

With a handful of calls, you can enrich interval smart meter data, quantify true cost-to-serve, segment customers by price and emissions impact, and deploy proactive tariff recommendations. Instead of building fragile scrapers and ad hoc translators, your team can focus on delivering measurable savings and emissions reductions to customers—fast.

If you’re ready to move from prototype to production, explore the endpoints, wire them into your pipeline, and start shipping. Energy API is the fastest path from zero to a working, reliable energy data stack. Try Energy API for free and put personalized tariffs and targeted EE programs within reach of your next sprint.