85 energy price cap levels annex 9/oct 2026 changes

.pre-commit-config.yaml

@@ -21,7 +21,7 @@ repos:
 
     ### Python Tools ###
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.16.1
+    rev: v0.16.4
     hooks:
     -   id: ruff-check
         args: [--fix]
@@ -30,15 +30,15 @@ repos:
         name: "🐍 python · Format with Ruff"
 
 -   repo: https://github.com/abravalheri/validate-pyproject
-    rev: v0.25
+    rev: '0.26'
     hooks:
     -   id: validate-pyproject
         name: "🐍 python · Validate pyproject.toml"
         additional_dependencies: ["validate-pyproject-schema-store[all]"]
 
     ### Data & Config Validation ###
 -   repo: https://github.com/python-jsonschema/check-jsonschema
-    rev: 0.37.4
+    rev: 0.38.0
     hooks:
     -   id: check-github-workflows
         name: "🐙 github-actions · Validate gh workflow files"

asf_mission_data/pipeline/energy_price_cap_levels_annex_9/config.py

@@ -57,9 +57,9 @@
 SILVER_TABLES_NODES_MAP = {"1c Consumption adjusted levels": "silver_energy_price_cap_annex_9_1c_consumption_adjusted_levels_parquet"}
 
 BENCHMARK_CONSUMPTION = {  # MWh per year
-    "Gas": 11.5,
-    "Electricity: Single-Rate Metering Arrangement": 2.7,
-    "Electricity: Multi-Register Metering Arrangement": 3.9,
+    "Gas": 9.5,  # old TDCV before July 26 change was 11.5
+    "Electricity: Single-Rate Metering Arrangement": 2.5,  # old TDCV before July 26 change was 2.7
+    "Electricity: Multi-Register Metering Arrangement": 3.4,  # old TDCV before July 26 change was 3.9
 }
 
 VAT = 0.05

asf_mission_data/pipeline/energy_price_cap_levels_annex_9/gold.py

@@ -13,7 +13,6 @@
 from asf_mission_data.pipeline.energy_price_cap_levels_annex_9.config import (
     BENCHMARK_CONSUMPTION,
     COMPONENT_CATEGORY_MAP,
-    VAT,
 )
 from asf_mission_data.pipeline.energy_price_cap_levels_annex_9.schemas import (
     GOLD_1C_CONSUMPTION_ADJUSTED_LEVELS_WITH_VAT_SCHEMA,
@@ -73,41 +72,70 @@ def consumption_adjusted_levels_with_vat_df(
     """Add VAT as a tariff component and uprate the total values to include VAT.
 
     This function derives VAT-inclusive tariff values from the silver dataset, and
-    creates a new tariff component representing VAT (calculated as 5% of the
-    `Total_GB average` component) and adds it as a separate row. It also uprates
-    the `Total_GB average` values so that they include VAT.
+    creates a new tariff component representing VAT (calculated as the difference
+    between the `Total inc VAT` and `Total_GB average` components) and adds it as
+    a separate row. It also uprates the `Total_GB average` values so that they
+    include VAT, using the corresponding `Total inc VAT` values.
 
     Args:
         silver_df (pd.DataFrame): Silver-layer Annex 9 DataFrame containing tariff
             components, consumption levels, and annual values before VAT
-            adjustments.
+            adjustments. Must contain both `Total_GB average` and
+            `Total inc VAT` tariff components for every fuel.
 
     Returns:
-        pd.DataFrame: DataFrame containing the original tariff components,
-        VAT as a separate component, and updated `Total_GB average` values
-        that include VAT.
+        pd.DataFrame: DataFrame containing the original tariff components
+        (excluding `Total inc VAT`), VAT as a separate component, and updated
+        `Total_GB average` values that include VAT.
     """
+    for component in ("Total_GB average", "Total inc VAT"):
+        if not silver_df["Tariff component"].eq(component).any():
+            raise ValueError(f"Expected tariff component '{component}' not found in silver_df.")
 
-    # Add VAT as individual tariff component
-    if not silver_df["Tariff component"].eq("Total_GB average").any():
-        raise ValueError("Expected tariff component 'Total_GB average' not found in silver_df.")
+    # Columns that uniquely identify a row aside from "Tariff component",
+    # "value" and "metadata"
+    key_cols = [
+        "Payment method",
+        "Fuel",
+        "Consumption",
+        "28AD Charge Restriction Period",
+        "28AD Charge Restriction Period start",
+        "28AD Charge Restriction Period end",
+        "28AD Charge Restriction Period interval",
+    ]
 
-    vat_rows = silver_df[silver_df["Tariff component"] == "Total_GB average"].copy()
-    vat_rows["Tariff component"] = "VAT"
-    vat_rows["value"] *= VAT
+    total_gb_avg = silver_df[silver_df["Tariff component"] == "Total_GB average"].copy()
+    total_inc_vat = silver_df[silver_df["Tariff component"] == "Total inc VAT"].copy()
+
+    merged = total_gb_avg.merge(
+        total_inc_vat[key_cols + ["value"]],
+        on=key_cols,
+        how="left",
+        suffixes=("", "_inc_vat"),
+        validate="one_to_one",
+    )
 
-    # Uprate Total_GB average to include VAT
-    uprated_silver_df = silver_df.copy()
+    if merged["value_inc_vat"].isna().any():
+        raise ValueError("Some 'Total_GB average' rows have no matching 'Total inc VAT' row.")
 
-    uprated_silver_df.loc[
-        (uprated_silver_df["Tariff component"] == "Total_GB average"),
-        "value",
-    ] *= 1 + VAT
+    # VAT component = Total inc VAT - Total_GB average
+    vat_rows = merged.copy()
+    vat_rows["value"] = vat_rows["value_inc_vat"] - vat_rows["value"]
+    vat_rows["Tariff component"] = "VAT"
+    vat_rows = vat_rows.drop(columns="value_inc_vat")
+
+    # Uprated Total_GB average = Total inc VAT value
+    uprated_total_gb_avg = merged.copy()
+    uprated_total_gb_avg["value"] = uprated_total_gb_avg["value_inc_vat"]
+    uprated_total_gb_avg = uprated_total_gb_avg.drop(columns="value_inc_vat")
 
-    # Remove now redundant "Total inc VAT" rows that were present only in the Dual fuel table
-    uprated_silver_df = uprated_silver_df[uprated_silver_df["Tariff component"] != "Total inc VAT"]
+    # All other rows, unchanged (drop original Total_GB average and Total inc VAT rows)
+    other_rows = silver_df[~silver_df["Tariff component"].isin(["Total_GB average", "Total inc VAT"])].copy()
 
-    return pd.concat([uprated_silver_df, vat_rows], ignore_index=True)
+    return pd.concat(
+        [other_rows, uprated_total_gb_avg, vat_rows],
+        ignore_index=True,
+    )
 
 
 @check_output(

asf_mission_data/pipeline/energy_price_cap_levels_annex_9/oct_2026_changes_checks.py

@@ -0,0 +1,120 @@
+# %% [markdown]
+# ### Checks for TDCV and electricity VAT changes for Oct - Dec 2026 and Jan - Mar 2027 price cap periods
+
+# %%
+import pandas as pd
+
+from asf_mission_data import storage
+from asf_mission_data.pipeline.energy_price_cap_levels_annex_9.config import (
+    BENCHMARK_CONSUMPTION,
+)
+
+# %%
+silver_df = storage.read_parquet(
+    "s3://asf-mission-data-dev/data/silver/energy_price_cap_levels/annex_9/latest/1c_consumption_adjusted_levels/1c_consumption_adjusted_levels.parquet"
+)
+
+# %%
+start_date_to_check = "2026-10-01"
+
+# %%
+# Levels table checks
+gold_levels_df = storage.read_parquet(
+    "s3://asf-mission-data-dev/data/gold/energy_price_cap_levels/annex_9/latest/1c_consumption_adjusted_levels_with_vat/1c_consumption_adjusted_levels_with_vat.parquet"
+)
+df = gold_levels_df
+
+# %%
+# VAT check, should be zero
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Consumption"] == "Typical consumption")
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Electricity: Single-Rate Metering Arrangement")
+    & (df["Tariff component"] == "VAT")
+]
+
+# %%
+# Total bill check, should match final dual fuel bill matches what is published on Ofgem page
+df = gold_levels_df
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Consumption"] == "Typical consumption")
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Dual fuel (implied)")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+# Electricity bill check
+df = gold_levels_df
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Consumption"] == "Typical consumption")
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Electricity: Single-Rate Metering Arrangement")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+# Component rates and standing charges check
+gold_tariff_component_rates_df = storage.read_parquet(
+    "s3://asf-mission-data-dev/data/gold/energy_price_cap_levels/annex_9/latest/tariff_component_rates/tariff_component_rates.parquet"
+)
+df = gold_tariff_component_rates_df
+
+# %%
+# Electricity checks
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Electricity: Single-Rate Metering Arrangement")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+# Gas checks
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Gas")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+# Check annual_bill_fixed_and_variable_contributions_df
+# Consumption-based cost (£/yr) should match the unit rate (incl VAT) * TDCV
+gold_annual_bill_fixed_and_variable_contributions_df = storage.read_parquet(
+    "s3://asf-mission-data-dev/data/gold/energy_price_cap_levels/annex_9/latest/annual_bill_fixed_and_variable_component_contributions/annual_bill_fixed_and_variable_component_contributions.parquet"
+)
+df = gold_annual_bill_fixed_and_variable_contributions_df
+
+# %%
+# Electricity checks
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Electricity: Single-Rate Metering Arrangement")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+electricity_tdcv = BENCHMARK_CONSUMPTION.get("Electricity: Single-Rate Metering Arrangement") * 1_000  # kWh/year
+electricity_unit_rate = 26.322252  # p/kWh
+electricity_tdcv * electricity_unit_rate / 100  # should match annual consumption-based cost
+
+# %%
+# Gas checks
+df[
+    (df["28AD Charge Restriction Period start"] == pd.to_datetime(start_date_to_check))
+    & (df["Payment method"] == "Other Payment Method")
+    & (df["Fuel"] == "Gas")
+    & (df["Tariff component"] == "Total_GB average")
+]
+
+# %%
+gas_tdcv = BENCHMARK_CONSUMPTION.get("Gas") * 1_000  # kWh/year
+gas_unit_rate = 7.966458  # p/kWh
+gas_tdcv * gas_unit_rate / 100  # should match annual consumption-based cost
+
+# %%