fix: price interpolation (#1154)

Use forward fill to interpolate time series data that represents prices:
- elecprice_marketprice_wh
- feed_in_tariff_wh

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

.env

@@ -11,7 +11,7 @@ DOCKER_COMPOSE_DATA_DIR=${HOME}/.local/share/net.akkudoktor.eos
 # -----------------------------------------------------------------------------
 # Image / build
 # -----------------------------------------------------------------------------
-VERSION=0.3.0.dev2607161979035365
+VERSION=0.3.0.dev2607171078037437
 PYTHON_VERSION=3.13.9
 
 # -----------------------------------------------------------------------------

config.yaml

@@ -6,7 +6,7 @@
 # the root directory (no add-on folder as usual).
 
 name: "Akkudoktor-EOS"
-version: "0.3.0.dev2607161979035365"
+version: "0.3.0.dev2607171078037437"
 slug: "eos"
 description: "Akkudoktor-EOS add-on"
 url: "https://github.com/Akkudoktor-EOS/EOS"

docs/_generated/openapi.md

@@ -1,6 +1,6 @@
 # Akkudoktor-EOS
 
-**Version**: `v0.3.0.dev2607161979035365`
+**Version**: `v0.3.0.dev2607171078037437`
 
 <!-- pyml disable line-length -->
 **Description**: This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.

openapi.json

@@ -8,7 +8,7 @@
       "name": "Apache 2.0",
       "url": "https://www.apache.org/licenses/LICENSE-2.0.html"
     },
-    "version": "v0.3.0.dev2607161979035365"
+    "version": "v0.3.0.dev2607171078037437"
   },
   "paths": {
     "/v1/admin/cache/clear": {

src/akkudoktoreos/optimization/genetic/geneticsolution.py

@@ -582,7 +582,7 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
             ),
             (
                 "feed_in_tariff_wh",
-                "linear",
+                "ffill",
                 "feed_in_tariff_amt_kwh",
                 1000.0,
             ),

src/akkudoktoreos/server/eos.py

@@ -1203,6 +1203,7 @@ async def fastapi_strompreis() -> list[float]:
             key="elecprice_marketprice_wh",
             start_datetime=start_datetime,
             end_datetime=end_datetime,
+            fill_method="ffill",
         )
         elecprice_list = elecprice_array.tolist()
     except Exception as e:

tests/single_test_optimization.py

@@ -153,6 +153,7 @@ async def prepare_optimization_real_parameters() -> GeneticOptimizationParameter
         key="elecprice_marketprice_wh",
         start_datetime=prediction_eos.ems_start_datetime,
         end_datetime=prediction_eos.end_datetime,
+        fill_method="ffill",
     )
     print(f"strompreis_euro_pro_wh: {strompreis_euro_pro_wh}")
 

tests/test_elecpriceakkudoktor.py

@@ -127,11 +127,12 @@ class TestElecPriceAkkudokor:
             len(provider) == 73
         )  # we have 48 datasets in the api response, we want to know 48h into the future. The data we get has already 23h into the future so we need only 25h more. 48+25=73
 
-        # Assert we get hours prioce values by resampling
+        # Assert we get hours price values by resampling
         np_price_array = await provider.key_to_array(
             key="elecprice_marketprice_wh",
             start_datetime=provider.ems_start_datetime,
             end_datetime=provider.end_datetime,
+            fill_method="ffill",
         )
         assert len(np_price_array) == provider.total_hours
 
@@ -204,6 +205,7 @@ class TestElecPriceAkkudokor:
             key="elecprice_marketprice_wh",
             start_datetime=provider.ems_start_datetime,
             end_datetime=provider.end_datetime,
+            fill_method="ffill",
         )
         assert isinstance(array, np.ndarray)
         assert len(array) == provider.total_hours

tests/test_elecpriceenergycharts.py

@@ -129,6 +129,7 @@ class TestElecPriceEnergyCharts:
             key="elecprice_marketprice_wh",
             start_datetime=provider.ems_start_datetime,
             end_datetime=provider.end_datetime,
+            fill_method="ffill",
         )
         assert len(np_price_array) == provider.total_hours
 
@@ -195,6 +196,7 @@ class TestElecPriceEnergyCharts:
             key="elecprice_marketprice_wh",
             start_datetime=provider.ems_start_datetime,
             end_datetime=provider.end_datetime,
+            fill_method="ffill",
         )
         assert isinstance(array, np.ndarray)
         assert len(array) == provider.total_hours

tests/test_elecpricefixed.py

@@ -241,7 +241,8 @@ class TestElecPriceFixed:
         hourly_array = await provider.key_to_array(
             key="elecprice_marketprice_wh",
             start_datetime=start_dt,
-            end_datetime=start_dt.add(hours=24)
+            end_datetime=start_dt.add(hours=24),
+            fill_method="ffill",
         )
 
         assert len(hourly_array) == 24
@@ -253,7 +254,8 @@ class TestElecPriceFixed:
             key="elecprice_marketprice_wh",
             start_datetime=start_dt,
             end_datetime=start_dt.add(hours=24),
-            interval="15 minutes"
+            interval="15 minutes",
+            fill_method="ffill",
         )
 
         assert len(quarter_hour_array) == 96  # 24 * 4
@@ -266,7 +268,8 @@ class TestElecPriceFixed:
             key="elecprice_marketprice_wh",
             start_datetime=start_dt,
             end_datetime=start_dt.add(hours=24),
-            interval="30 minutes"
+            interval="30 minutes",
+            fill_method="ffill",
         )
 
         assert len(half_hour_array) == 48  # 24 * 2

tests/test_elecpriceimport.py

@@ -112,6 +112,7 @@ class TestElecPriceImport:
             start_datetime=provider.ems_start_datetime,
             end_datetime=provider.ems_start_datetime + to_duration(f"{len(expected_values)} hours"),
             interval=to_duration("1 hour"),
+            fill_method="ffill",
         )
         # Allow for some difference due to value calculation on DST change
         npt.assert_allclose(result_values, expected_values, rtol=0.001)