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Historical Sweden Nord Pool Day-Ahead Prices

Historical Sweden Nord Pool Day-Ahead Prices

You need reliable, queryable history of Sweden’s Nord Pool day-ahead power prices to drive finance workflows—budgeting, valuation, hedging backtests, and P&L attribution. By the end of this guide, you’ll be able to pull and parse the Sweden Nord Pool Day-Ahead timeseries from the Energy API, handle units and dates correctly, and wire it into your analytics or treasury models.

What you’ll query: Sweden Nord Pool Day-Ahead (EUR/MWh)

The dataset in focus is the Sweden Nord Pool Day-Ahead electricity price index.

Illustration: Historical Sweden Nord Pool Day-Ahead Prices
  • Symbol name: Sweden Nord Pool Day-Ahead
  • Symbol code: NORDPOOL_SE_DA
  • Unit: EUR/MWh
  • Authentication: api_key query parameter (use the literal placeholder YOUR_API_KEY for examples)

All examples below use the timeseries endpoint and the NORDPOOL_SE_DA symbol. Prices are quoted in EUR per megawatt-hour and designed for daily financial analysis such as forward hedging comparisons, variance analysis, cost forecasts, and settlement models.

Endpoint and parameters

The Energy API timeseries endpoint returns daily indexed values between a requested start and end date for one or more symbols. You will use:

  • HTTP method: GET
  • URL: https://energy-api.com/api/v1/timeseries
  • Query parameters:
    • start: inclusive start date (YYYY-MM-DD)
    • end: inclusive end date (YYYY-MM-DD)
    • symbols: comma-separated list of symbol codes (use NORDPOOL_SE_DA)
    • api_key: your API key

Authentication is via the api_key query parameter. Do not include unrelated “base” conversions here when you need energy commodities like TTF_GAS or EUA_CO2 together; simply request each energy symbol by its code. The response includes a per-symbol currency field so you can maintain correct units downstream.

Quick start curl (copy/paste)

Run this to fetch a historical window for Sweden’s day-ahead power price:

curl -G "https://energy-api.com/api/v1/timeseries" --data-urlencode "start=2026-01-01" --data-urlencode "end=2026-03-31" --data-urlencode "symbols=NORDPOOL_SE_DA" --data-urlencode "api_key=YOUR_API_KEY"

Official sample responses you will encounter

Below are complete JSON response examples. The first is the official sample block from the live documentation, shown verbatim. The second is a real response for NORDPOOL_SE_DA that you should use as your reference when parsing the Sweden series. Additional examples are included to help you test your parsers and verify field handling.

Official sample (from docs)

{
"success": true,
"date": "2026-11-05",
"base": "EUR",
"rates": {
"OMIE_ES_DA": 238.6863
},
"dates": {
"OMIE_ES_DA": "2026-11-05"
},
"currencies": {
"OMIE_ES_DA": "EUR"
},
"base_filter_note": null,
"missing_symbols": null
}

This official sample shows the shape of the response for a day-ahead market (here, Spain). Your Sweden implementation will follow the same schema but with the Sweden symbol code and values.

Real API response for Sweden Nord Pool Day-Ahead

{"success":true,"date":"2026-11-05","base":"EUR","rates":{"NORDPOOL_SE_DA":5.9014},"dates":{"NORDPOOL_SE_DA":"2026-11-05"},"currencies":{"NORDPOOL_SE_DA":"EUR"},"base_filter_note":null,"missing_symbols":null}

Use this as the concrete guide for field names and how to read Sweden’s price and date. The key you will read is rates.NORDPOOL_SE_DA, and the associated unit is currencies.NORDPOOL_SE_DA = EUR, with values expressed in EUR/MWh.

Official sample again (useful for parser tests)

{
"success": true,
"date": "2026-11-05",
"base": "EUR",
"rates": {
"OMIE_ES_DA": 238.6863
},
"dates": {
"OMIE_ES_DA": "2026-11-05"
},
"currencies": {
"OMIE_ES_DA": "EUR"
},
"base_filter_note": null,
"missing_symbols": null
}

Keep one copy of the official block in your test suite to validate your JSON parsing logic without depending on live requests.

Real API response for Sweden (duplicate for validation)

{"success":true,"date":"2026-11-05","base":"EUR","rates":{"NORDPOOL_SE_DA":5.9014},"dates":{"NORDPOOL_SE_DA":"2026-11-05"},"currencies":{"NORDPOOL_SE_DA":"EUR"},"base_filter_note":null,"missing_symbols":null}

A second copy of the Sweden response helps you verify idempotent parsing across repeated payloads (for example, ensuring you don’t double-insert on retries and can safely upsert by symbol+date).

Field-by-field: what to read for finance workflows

  • success: Boolean. Check true before proceeding.
  • date: Top-level date associated with the payload. Use dates.NORDPOOL_SE_DA for the symbol-specific effective date when storing or validating.
  • base: “EUR”. This indicates the base currency context. Your actual price unit comes from currencies.NORDPOOL_SE_DA.
  • rates.NORDPOOL_SE_DA: The Sweden day-ahead price value for the effective date, denominated in EUR/MWh.
  • dates.NORDPOOL_SE_DA: The ISO date string (YYYY-MM-DD) for that rate. Treat this as the price’s delivery or market date key in your warehouse.
  • currencies.NORDPOOL_SE_DA: “EUR”. Confirms the per-symbol currency/unit alignment.
  • base_filter_note: null in samples. You can log this field in case filters are ever applied to your request.
  • missing_symbols: null when all requested symbols are present. Check this before assuming completeness across a list.

Python example: fetch and parse Sweden Nord Pool Day-Ahead

This snippet calls the same endpoint and extracts the fields you need to populate a financial timeseries table keyed by symbol and date.

import os
import sys
import json
import urllib.parse
import urllib.request

def fetch_sweden_dayahead(start, end, api_key):
base_url = "https://energy-api.com/api/v1/timeseries"
query = {
"start": start,
"end": end,
"symbols": "NORDPOOL_SE_DA",
"api_key": api_key
}
url = base_url + "?" + urllib.parse.urlencode(query)
with urllib.request.urlopen(url) as resp:
payload = resp.read().decode("utf-8")
data = json.loads(payload)
return data

def normalize_to_rows(data):
rows = []
if not data.get("success"):
raise RuntimeError("API returned success=false")
symbol = "NORDPOOL_SE_DA"
# The timeseries schema returns a single value per symbol/date in the examples shown.
# Use the per-symbol dicts to map date and currency precisely.
price = data["rates"].get(symbol)
dt = data["dates"].get(symbol)
ccy = data["currencies"].get(symbol)
if price is not None and dt is not None:
rows.append({
"symbol": symbol,
"date": dt,
"price_eur_per_mwh": price,
"currency": ccy
})
return rows

if __name__ == "__main__":
api_key = os.environ.get("ENERGY_API_KEY", "YOUR_API_KEY")
try:
data = fetch_sweden_dayahead(start="2026-01-01", end="2026-03-31", api_key=api_key)
except Exception as e:
print("HTTP error:", e, file=sys.stderr)
sys.exit(1)

rows = normalize_to_rows(data)
for r in rows:
print(r)

Store the rows in your database keyed by (symbol, date). If you plan to backfill long histories, call the endpoint iteratively across smaller windows (for example, one quarter per request) and upsert on arrival.

Time semantics, timezone, and non-trading days

  • Granularity: Day-ahead is a daily series. Use the “dates” field as the canonical index for your time dimension.
  • Timezone: Dates are delivered as YYYY-MM-DD. Treat them as logical market dates; your warehouse can store them as DATE without timezone. If you need a timestamp, attach a normalized midnight UTC for consistency in joins.
  • Weekends/holidays: Day-ahead power prices exist for every delivery day, including weekends and many holidays. Don’t assume gaps are due to non-trading days; always check missing_symbols and validate presence of the expected date key.
  • Clock changes: Daylight saving changes do not alter the daily granularity in this endpoint. Your financial models should continue using daily rows without special handling.

Units and currency handling in finance models

  • Unit: EUR/MWh for NORDPOOL_SE_DA.
  • Per-symbol currency: Read currencies.NORDPOOL_SE_DA; do not hardcode EUR globally if consuming multiple symbols.
  • Conversions: If you need to translate to a different financial reporting currency, apply your own FX layer outside of this request. Do not add base=USD when mixing energy indices like TTF_GAS or EUA_CO2—request energy symbols directly and convert downstream.
  • Scaling: Values are quoted directly in EUR/MWh. Store as decimal with adequate precision for your P&L tolerances.

Data engineering patterns that save time

  • Idempotent upserts: Use symbol+date as a primary key to avoid duplicates when retrying or reprocessing.
  • Windowing: For long backfills, split your historical range into quarterly or monthly windows and call them sequentially. This avoids overly large payloads and simplifies retry/recovery.
  • Caching: Cache the last successful day’s payload for 24 hours to avoid repeat lookups in intraday financial dashboards that do not require mid-day refreshes.
  • Monitoring: Alert on missing_symbols not being null and on empty rates for NORDPOOL_SE_DA when a date is expected.
  • Schema stability: Keep the exact field names—rates, dates, currencies—so your parser remains aligned with the endpoint schema.

Validating and storing the Sweden series

When you persist the daily price, record the following columns for transparent finance workflows:

  • date (DATE): from dates.NORDPOOL_SE_DA
  • symbol (STRING): NORDPOOL_SE_DA
  • price_eur_per_mwh (DECIMAL): from rates.NORDPOOL_SE_DA
  • currency (STRING): from currencies.NORDPOOL_SE_DA
  • ingested_at (TIMESTAMP): server-side timestamp when your job ran

This structure supports reconciliations, roll-forwards, and audit trails when your treasury or risk team replays scenarios or checks month-end close numbers.

Finance workflows powered by NORDPOOL_SE_DA

  • Budgeting and forecasting: Feed historical EUR/MWh into OPEX projections for Sweden sites; compare plan vs. actual at the daily level and roll to months.
  • Hedging backtests: Align daily day-ahead prices with your hedge execution logs to compute variance and slippage.
  • Exposure tracking: Aggregate daily price x metered volume to attribute energy cost and measure sensitivity to price shocks.
  • Pricing and margin: For energy-linked products, mark to the Sweden day-ahead and track gross margin under different consumption profiles.

Error handling and resilience

  • HTTP-level failures: Implement retries with exponential backoff. Preserve idempotency by upserting on symbol+date.
  • Success=false: Halt processing and log payload. Do not ingest partials when success is false.
  • Missing symbols: If missing_symbols is not null, skip posting incomplete results and trigger a requery for the affected date window.
  • Data validation: Assert that currencies.NORDPOOL_SE_DA is “EUR” and that dates.NORDPOOL_SE_DA matches the date column you intend to write.

Testing with real JSON

Use these copies as fixtures in your test suite to ensure your parsers are deterministic.

Docs sample fixture

{
"success": true,
"date": "2026-11-05",
"base": "EUR",
"rates": {
"OMIE_ES_DA": 238.6863
},
"dates": {
"OMIE_ES_DA": "2026-11-05"
},
"currencies": {
"OMIE_ES_DA": "EUR"
},
"base_filter_note": null,
"missing_symbols": null
}

Sweden Nord Pool Day-Ahead fixture

{"success":true,"date":"2026-11-05","base":"EUR","rates":{"NORDPOOL_SE_DA":5.9014},"dates":{"NORDPOOL_SE_DA":"2026-11-05"},"currencies":{"NORDPOOL_SE_DA":"EUR"},"base_filter_note":null,"missing_symbols":null}

Operational checklist

  • Authentication: Provide api_key as a query parameter. Use a secure secret store and inject at runtime.
  • Date range: Use ISO format YYYY-MM-DD. Start/end are inclusive; plan your batching around calendar quarters or months.
  • Symbol correctness: Always pass symbols=NORDPOOL_SE_DA for Sweden day-ahead.
  • Currency/unit alignment: Read currencies.NORDPOOL_SE_DA; store values as EUR/MWh without transforming in-place.
  • Backfills: Perform deterministic replays and reconcile row counts by date range to confirm no gaps.

Frequently asked questions

Q1: How do I authenticate?
A: Supply your key via the api_key query parameter on every request. Example: api_key=YOUR_API_KEY.

Q2: Which fields should I store for finance-grade auditing?
A: Store date (from dates.NORDPOOL_SE_DA), symbol (NORDPOOL_SE_DA), price (from rates.NORDPOOL_SE_DA), and currency (from currencies.NORDPOOL_SE_DA). Also record your ingestion timestamp for audit trails.

Q3: Can I request multiple energy indices at once?
A: Yes, by comma-separating symbols. If combining with other energy indices (e.g., TTF_GAS, EUA_CO2), do not add base=USD in the same request; read per-symbol currencies and convert externally if needed.

Q4: How should I handle missing data?
A: Check missing_symbols. If it’s not null or a symbol is absent in rates/dates, retry the specific window and avoid inserting partial rows.

Q5: Are weekend or holiday dates returned?
A: Day-ahead prices are daily. Expect values across weekends and many holidays; do not assume gaps based on business-day logic alone.

Where to go next

Register for a 7-day trial (50 calls) and start pulling Sweden Nord Pool Day-Ahead history into your finance models. The Starter plan begins at $19.99/month. Create an account here: Register. For parameter details and more examples, read the Documentation.

Keywords
Nord Pool day-ahead prices Sweden energy API historical power prices finance workflows data parsing techniques

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