feat: electricity fee provider framework and generic providers (#1235)

Add new provider class for electricity fees providers.

Add the generic providers:
- ElecFeeFixed
- ElecFeeImport

The providers provide predictions for:

- elecfee_consumption_amt_wh:
  Total fixed fee for consumed energy per Wh [amount/Wh]. This is the accumulation of all
  fixed per-Wh fees payable on "consumed energy - such as network charge, concession fee,
  and electricity charge - into a single amount.
- elecfee_consumption_percent_amt:
  Total fixed surcharge on consumed energy, given as a percentage of the monetary amount
  already charged for that energy [%]. This is the accumulation of all percentage-based
  surcharges payable on top of the consumed-energy fee - such as VAT - into a single
  percentage. This is a percentage of the fee amount, not a per-Wh rate.
- elecfee_feedin_amt_wh:
  Total fixed deduction from feed-in energy per Wh [amount/Wh]. This is the accumulation of
  all fixed per-Wh charges deducted from feed-in energy - such as metering fees or
  grid-operator handling "charges - into a single amount. Applied after the percentage-based
  deduction, i.e. it reduces the price by a flat amount per Wh rather than by a share of the
  raw price.
- elecfee_feedin_percent_amt:
  Total percentage deducted from the raw feed-in price (spot price) [%]. This is the
  accumulation of all percentage-based deductions payable on the feed-in tariff - such as a
  marketing or balancing fee retained by the aggregator - into a single percentage. It is
  applied as `raw_price * (100 - percent) / 100`, i.e. it scales down the raw price rather
  than adding a surcharge to it.

A new _apply_fee() method is added to the base class for ElecPrice and FeedInTariff to be used to
add the fees in a consistent way. Fees are taken from the active ElecFee provider and applied
to the raw prices given to the _apply_fee() method.

The optional application of fees is added to:

- ElecPriceAkkudoktor
- ElecPriceFixed
- ElecPriceEnergyCharts
- ElecPriceSMARD
- FeedInTariffEnergyCharts
- FeedInTariffFixed
- FeedInTariffSMARD

The import providers ElecPriceImport and FeedInTariffImport do not apply fees by intentention.

The following providers currently do not handle fees defined by ElecFee:

- ElecPriceTibber
- FeedInTariffAkkudoktor
- FeedInTariffDvhubOnline
- FeedInTariffTibber

The tests for this feature are either added or existing tests are extended.

The documentation was extended for the electricity fee provider settings.

Besides this feature further improvements are added:

* feat: add SMARD quarter-hour electricty price and feed-in tariff provider

* feat: to_series method for TimeWindows and ValueTimeWindows

  Additional to to_array the time window sequence can now also produce a pandas series.
  Test have been extended to cover the series generation.

* feat: use time windows in fixed feedin tariff provider

  Feedin tariff can now be configured by time windows - not a single value.

* feat: EOSdash select for PVLib inverters and modules

  Provide PVLib inverter and module names in config selection.

* feat: EOSdash lazy select for big option sets

  Add a new form for lazy selection of big option sets. Filtering and
  generation of the option set is done server-side.

* fix: use raw data for ETS/ median prediction

  Use to raw time series data for ETS/ median prediction to avoid interference
  by e.g. dynamic grid charges.

* fix: EOSdash config drops by type only on details resolve

  Drop configuration by type and path. Prevents dropping of configuration items
  with same type and level but different path.

* fix: EOSdash configuration section closes on update

  Open section if searching or if last update touched this category — including
  updates on deeply nested sub-fields.

* chore: make elecfeefixed, elecpricefixed and feedintarifffixed warn about no windows and default to 0

  Missining configuration creates default 0 value and a warning instead of an exception.

* fix: test setup for providers

  Reset db state on each test run.

* chore: improve config option naming for elecpricefixed.

* chore: adapt elecpricefixed test to changed time_windows naming

* chore: factorized common price provider helpers to priceabc.py

  Factorized common price provider helpers to priceabc.py. Add tests for these helpers.
  Reduce/ change testing of elecpriceabc.py and feedintariffabc.py to cover
  only specifics. Rest of testing is already covered by test_priceabc.py.

* chore: update version

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>

tests/test_feedintariffenergycharts.py

@@ -5,16 +5,17 @@ from pathlib import Path
 from unittest.mock import Mock, patch
 
 import numpy as np
+import pandas as pd
 import pytest
 import requests
 
 from akkudoktoreos.core.coreabc import get_ems
+from akkudoktoreos.prediction.elecfeefixed import ElecFeeFixed
 from akkudoktoreos.prediction.elecpriceenergycharts import (
-    ElecPriceEnergyCharts,
     EnergyChartsElecPrice,
 )
 from akkudoktoreos.prediction.feedintariffenergycharts import FeedInTariffEnergyCharts
-from akkudoktoreos.utils.datetimeutil import to_datetime
+from akkudoktoreos.utils.datetimeutil import to_datetime, to_duration
 
 DIR_TESTDATA = Path(__file__).absolute().parent.joinpath("testdata")
 
@@ -35,8 +36,25 @@ def provider(config_eos):
     )
     provider = FeedInTariffEnergyCharts()
     provider.highest_orig_datetime = None
-    provider.records.clear()
     assert provider.enabled()
+    provider._db_reset_state()
+    return provider
+
+
+
+@pytest.fixture
+def elecfee_provider(config_eos):
+    """Fixture to create a ElecFeeFixed instance."""
+    config_eos.merge_settings_from_dict(
+        {
+            "elecfee": {
+                "provider": "ElecFeeFixed",
+            },
+        }
+    )
+    provider = ElecFeeFixed()
+    assert provider.enabled()
+    provider._db_reset_state()
     return provider
 
 
@@ -94,7 +112,7 @@ class TestFeedInTariffEnergyCharts:
             await provider._update_data(force_update=True)
 
         result = await provider.key_to_raw_series(
-            key="feed_in_tariff_wh",
+            key="feed_in_tariff_raw_wh",
             start_datetime=start,
             end_datetime=start.add(hours=provider.config.prediction.hours),
         )
@@ -127,9 +145,9 @@ class TestFeedInTariffEnergyCharts:
 
         with (
             patch.object(provider, "_request_forecast", return_value=energy_charts_data) as request,
-            patch.object(ElecPriceEnergyCharts, "_predict_ets", side_effect=fake_ets),
+            patch.object(FeedInTariffEnergyCharts, "_predict_ets", side_effect=fake_ets),
             patch.object(
-                ElecPriceEnergyCharts,
+                FeedInTariffEnergyCharts,
                 "_predict_median",
                 side_effect=AssertionError("median fallback must not be used"),
             ),
@@ -141,7 +159,7 @@ class TestFeedInTariffEnergyCharts:
             # second update reuses the retained 35-day history without another request.
             assert request.call_count == 1
             assert len(ets_history_lengths) == 2
-            assert all(length > 800 * 4 for length, _ in ets_history_lengths)
+            assert all(length > 2 * 168 * 4 for length, _ in ets_history_lengths)
             assert all(seasonal_periods == 168 * 4 for _, seasonal_periods in ets_history_lengths)
 
             await provider.update_data(force_enable=True, force_update=True)
@@ -185,10 +203,10 @@ class TestFeedInTariffEnergyCharts:
             deprecated=False,
         )
 
-        def fake_predict(history, slots, slots_per_hour):
-            return np.full(slots, 0.00005)
+        def fake_predict(history, hours, slots_per_hour=1):
+            return np.full(hours, 0.00005)
 
-        with patch.object(provider, "_predict_prices", side_effect=fake_predict):
+        with patch.object(provider, "_predict", side_effect=fake_predict):
             # First: successful update seeds history and highest_orig_datetime.
             with patch.object(provider, "_request_forecast", return_value=energy_charts_data):
                 await provider.update_data(force_enable=True, force_update=True)
@@ -218,3 +236,165 @@ class TestFeedInTariffEnergyCharts:
         ):
             with pytest.raises(requests.exceptions.ReadTimeout):
                 await provider.update_data(force_enable=True, force_update=True)
+
+    @pytest.mark.asyncio
+    async def test_update_data_no_fees_configured_defaults_gross_to_raw(self, provider):
+        """Without an ElecFee provider configured, feed_in_tariff_wh must equal the raw series.
+
+        _apply_fees() catches the KeyError from an absent ElecFee provider and
+        defaults both fee components to 0, so gross should be indistinguishable
+        from raw in that case.
+        """
+        start = to_datetime("2025-01-15 00:00:00", in_timezone="Europe/Berlin")
+        get_ems().set_start_datetime(start)
+        raw_slots = provider.config.prediction.hours * 4
+        energy_charts_data = EnergyChartsElecPrice(
+            license_info="",
+            unix_seconds=[int(start.add(minutes=15 * i).timestamp()) for i in range(raw_slots)],
+            price=[100.0] * raw_slots,
+            unit="EUR/MWh",
+            deprecated=False,
+        )
+
+        with patch.object(provider, "_request_forecast", return_value=energy_charts_data):
+            await provider._update_data(force_update=True)
+
+        raw = await provider.key_to_series(
+            key="feed_in_tariff_raw_wh",
+            start_datetime=start,
+            end_datetime=start.add(hours=provider.config.prediction.hours),
+            interval=to_duration("15 minutes"),
+        )
+        gross = await provider.key_to_series(
+            key="feed_in_tariff_wh",
+            start_datetime=start,
+            end_datetime=start.add(hours=provider.config.prediction.hours),
+            interval=to_duration("15 minutes"),
+        )
+        pd.testing.assert_series_equal(gross, raw, check_names=False)
+
+    @pytest.mark.asyncio
+    async def test_update_data_applies_feedin_fees(self, provider, config_eos):
+        """feed_in_tariff_wh must reflect the configured feed-in fee deduction.
+
+        Per _apply_fees(): gross = raw * (100 - percent_amt) / 100 - amt_wh,
+        i.e. fees are deducted from what the producer receives, the inverse
+        direction of the consumption-side markup.
+        """
+        feedin_amt_kwh = 0.001  # flat fee/kWh deducted from the feed-in payout
+        feedin_percent_amt = 5.0  # percentage deducted from the feed-in payout
+        config_eos.merge_settings_from_dict(
+            {
+                "elecfee": {
+                    "provider": "ElecFeeFixed",
+                    "elecfeefixed": {
+                        "feedin_amt_kwh": {
+                            "windows": [
+                                {"start_time": "00:00", "duration": "24 hours", "value": feedin_amt_kwh},
+                            ],
+                        },
+                        "feedin_percent_amt": {
+                            "windows": [
+                                {"start_time": "00:00", "duration": "24 hours", "value": feedin_percent_amt},
+                            ],
+                        },
+                    },
+                },
+            }
+        )
+        start = to_datetime("2025-01-15 00:00:00", in_timezone="Europe/Berlin")
+        get_ems().set_start_datetime(start)
+        await ElecFeeFixed()._update_data(force_update=True)
+
+        raw_slots = provider.config.prediction.hours * 4
+        energy_charts_data = EnergyChartsElecPrice(
+            license_info="",
+            unix_seconds=[int(start.add(minutes=15 * i).timestamp()) for i in range(raw_slots)],
+            price=[100.0] * raw_slots,  # 100 EUR/MWh = 0.1 EUR/kWh
+            unit="EUR/MWh",
+            deprecated=False,
+        )
+        with patch.object(provider, "_request_forecast", return_value=energy_charts_data):
+            await provider._update_data(force_update=True)
+
+        raw_result = await provider.key_to_series(
+            key="feed_in_tariff_raw_wh",
+            start_datetime=start,
+            end_datetime=start.add(minutes=15),
+            interval=to_duration("15 minutes"),
+        )
+        gross_result = await provider.key_to_series(
+            key="feed_in_tariff_wh",
+            start_datetime=start,
+            end_datetime=start.add(minutes=15),
+            interval=to_duration("15 minutes"),
+        )
+        raw_kwh = raw_result.iloc[0] * 1000
+        gross_kwh = gross_result.iloc[0] * 1000
+        assert raw_kwh == pytest.approx(0.1)
+        expected_gross_kwh = raw_kwh * (100.0 - feedin_percent_amt) / 100.0 - feedin_amt_kwh
+        assert gross_kwh == pytest.approx(expected_gross_kwh)
+
+    @pytest.mark.asyncio
+    async def test_update_data_covers_full_horizon_after_stale_fetch_outage(self, provider):
+        """Regression test: needed_slots must include the gap when a fetch outage
+        leaves highest_orig_datetime behind the current ems_start_datetime.
+
+        Same bug/fix as ElecPriceEnergyCharts: `covered_slots` must be allowed
+        to go negative when highest_orig_datetime is older than
+        ems_start_datetime, rather than clamped to 0, or the predicted tail
+        ends before ems_start_datetime + prediction.hours whenever an outage
+        persists long enough for the two to diverge.
+        """
+        provider.config.prediction.hours = 48
+
+        start = to_datetime("2026-01-15 00:00:00", in_timezone="Europe/Berlin")
+        get_ems().set_start_datetime(start)
+
+        raw_start = start.subtract(days=35)
+        raw_slots = int((start - raw_start).total_seconds() // 900) + 1
+        energy_charts_data = EnergyChartsElecPrice(
+            license_info="",
+            unix_seconds=[int(raw_start.add(minutes=15 * i).timestamp()) for i in range(raw_slots)],
+            price=[50.0 + float(i % 96) for i in range(raw_slots)],
+            unit="EUR/MWh",
+            deprecated=False,
+        )
+
+        def fake_ets(history, seasonal_periods, hours):
+            return np.full(hours, 0.00005)
+
+        with (
+            patch.object(provider, "_request_forecast", return_value=energy_charts_data),
+            patch.object(FeedInTariffEnergyCharts, "_predict_ets", side_effect=fake_ets),
+        ):
+            await provider.update_data(force_enable=True, force_update=True)
+
+        last_good = provider.highest_orig_datetime
+        assert last_good is not None
+
+        # Advance ems_start_datetime well past the last known data point, as
+        # if a fetch outage has persisted for a while.
+        outage_gap_hours = 20
+        new_start = to_datetime(last_good).add(hours=outage_gap_hours)
+        get_ems().set_start_datetime(new_start)
+
+        with (
+            patch.object(
+                provider, "_request_forecast", side_effect=requests.exceptions.ReadTimeout("boom")
+            ),
+            patch.object(FeedInTariffEnergyCharts, "_predict_ets", side_effect=fake_ets),
+        ):
+            await provider.update_data(force_enable=True, force_update=True)
+
+        assert provider.highest_orig_datetime == last_good
+
+        horizon_end = new_start.add(hours=provider.config.prediction.hours)
+        raw_result = await provider.key_to_series(
+            key="feed_in_tariff_raw_wh",
+            start_datetime=horizon_end.subtract(minutes=15),
+            end_datetime=horizon_end,
+            interval=to_duration("15 minutes"),
+        )
+        assert len(raw_result) == 1
+        assert not raw_result.isna().any()