diff --git a/src/gems/input_converter/data/model_configuration/st-storage.yaml b/src/gems/input_converter/data/model_configuration/st-storage.yaml
index 170af17e..5e1964de 100644
--- a/src/gems/input_converter/data/model_configuration/st-storage.yaml
+++ b/src/gems/input_converter/data/model_configuration/st-storage.yaml
@@ -18,7 +18,7 @@ template:
   template-parameters:
     - name: area
       cluster-type: st_storage
-      description: "Area identifier for the load component"
+      description: "Area identifier for the component"
       # exclude:
 
   component:
diff --git a/tests/antares_historic/test_link_model.py b/tests/antares_historic/test_link_model.py
index 8f345b33..dada65b3 100644
--- a/tests/antares_historic/test_link_model.py
+++ b/tests/antares_historic/test_link_model.py
@@ -10,11 +10,37 @@
     first_optim_relgap,
 )
 
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "LINK"  : CONSTANT DATA  ##
+
 LOAD_FILES_DIR = Path("tests/antares_historic/data")
 LINK_TEST_REL_ACCURACY = 1e-6
 LINK_TEST_SOLVER = "highs"
 MODIFICATION_RATIO = 1.2
 
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "LINK"  : TESTS  ##
+
+# General tests [OK : test_general_link]
+
+# Testing Boolean/discrete parameters
+## hurdles_cost [TODO]
+## loop_flow [TODO]
+## use_phase_shifter [TODO]
+## transmission_capacities [TODO]
+## asset_type [TODO]
+
+# Testing Float parameters
+## /
+
+# Testing Timeseries parameters
+## capacity_direct [OK : test_direct_capacity]
+## capacity_indirect [OK : test_indirect_capacity]
+## hurdle_cost_direct [OK : TODO ref to test in main branch]
+## hurdle_cost_indirect [OK : TODO ref to test in main branch]
+## Impedance [TODO]
+## Loopflow [TODO]
+## Pshift Min [TODO]
+## Pshift Max [TODO]
+
 
 def link_test_procedure(
     study_name: str,
diff --git a/tests/antares_historic/test_sts_model.py b/tests/antares_historic/test_sts_model.py
new file mode 100644
index 00000000..1b737dbb
--- /dev/null
+++ b/tests/antares_historic/test_sts_model.py
@@ -0,0 +1,349 @@
+import os
+from dataclasses import replace
+from pathlib import Path
+from time import time
+
+import numpy as np
+import pandas as pd
+import pytest
+from antares.craft import STStorageProperties
+
+from gems.input_converter.src.logger import Logger
+from tests.antares_historic.utils import (
+    convert_study,
+    createSTSTestAntaresStudy,
+    first_optim_relgap,
+)
+
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "SHORT TERM STORAGE"  : CONSTANT DATA  ##
+
+LOAD_FILES_DIR = Path("tests/antares_historic/data")
+STS_TEST_REL_ACCURACY = 1e-6
+STS_TEST_SOLVER = "highs"
+MODIFICATION_RATIO = 1.2
+LOAD_TIME_SERIE_FILES_STS = [
+    "load_matrix_1.txt",
+    # "load_matrix_2.txt", #uncomment to test with different load profile
+    # "load_matrix_original.txt",
+]
+
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "SHORT TERM STORAGE"  : TESTS  ##
+
+# General tests [OK:sts_list_general_test]
+
+# Testing Boolean/discrete parameters
+## initial_level_optim [TODO]
+## enabled [TODO]
+## penalize_variation_injection [TODO]
+## penalize_variation_withdrawal [TODO]
+
+# Testing Float parameters
+## injection_nominal_capacity [OK : test_injection_nominal_capacity]
+## withdrawal_nominal_capacity [OK: test_withdrawal_nominal_capacity]
+## reservoir_capacity [OK: test_reservoir_capacity]
+## efficiency [OK : test_efficiency]
+## efficiency_withdrawal [OK : test_efficiency_withdrawal]
+## initial_level [OK : test_initial_level]
+
+# Testing Timeseries parameters
+## p_max_injection [TODO]
+## p_max_withdrawal [TODO]
+## lower_rule_curve [TODO]
+## upper_rule_curve [TODO]
+## storage_inflows [TODO]
+## cost_injection [TODO]
+## cost_withdrawal [TODO]
+## cost_level [TODO]
+## cost_variation_injection [TODO]
+## cost_variation_withdrawal [TODO]
+
+
+def sts_test_procedure(
+    study_name: str,
+    study_path: Path,
+    sts_properties: STStorageProperties,
+    load_time_serie_file: Path,
+    exec_folder: Path,
+) -> None:
+    createSTSTestAntaresStudy(
+        study_name,
+        study_path,
+        load_time_serie_file,
+        sts_properties,
+    )
+    original_study_path, converted_study_path = convert_study(
+        study_path, study_name, ["short-term-storage"]
+    )
+    rel_gap = first_optim_relgap(
+        exec_folder, original_study_path, converted_study_path, STS_TEST_SOLVER
+    )
+    assert rel_gap < STS_TEST_REL_ACCURACY
+
+
+def sts_test_procedure_float_param(
+    sts_properties: STStorageProperties,
+    tested_param: str,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    # Run base test
+    study_name_base = f"e2e_{str(int(100*time()))}"
+
+    createSTSTestAntaresStudy(
+        study_name_base,
+        auto_generated_studies_path,
+        LOAD_FILES_DIR / load_time_serie_file,
+        sts_properties,
+    )
+    original_study_path, converted_study_path = convert_study(
+        auto_generated_studies_path, study_name_base, ["short-term-storage"]
+    )
+    rel_gap = first_optim_relgap(
+        antares_exec_folder, original_study_path, converted_study_path, STS_TEST_SOLVER
+    )
+    assert rel_gap < STS_TEST_REL_ACCURACY
+
+    ref_value_param = getattr(sts_properties, tested_param)
+
+    for modification in [MODIFICATION_RATIO, 1 / MODIFICATION_RATIO]:
+        sts_properties_perturbated = replace(
+            sts_properties, **{tested_param: ref_value_param * modification}
+        )
+
+        study_name_perturbated = f"e2e_{str(int(100*time()))}"
+
+        createSTSTestAntaresStudy(
+            study_name_perturbated,
+            auto_generated_studies_path,
+            LOAD_FILES_DIR / load_time_serie_file,
+            sts_properties_perturbated,
+        )
+        rel_gap = first_optim_relgap(
+            antares_exec_folder,
+            auto_generated_studies_path / study_name_perturbated,
+            converted_study_path,
+            STS_TEST_SOLVER,
+        )
+        assert rel_gap > 100 * STS_TEST_REL_ACCURACY
+
+
+@pytest.fixture(scope="session")
+def sts_list_general_test() -> list[STStorageProperties]:
+    return [
+        STStorageProperties(
+            group="battery",
+            injection_nominal_capacity=100,
+            withdrawal_nominal_capacity=100,
+            reservoir_capacity=300,
+            efficiency=1,
+            initial_level=0.5,
+        ),
+        STStorageProperties(
+            group="battery",
+            injection_nominal_capacity=100,
+            withdrawal_nominal_capacity=100,
+            reservoir_capacity=300,
+            efficiency=0.8,
+            initial_level=0.5,
+        ),
+        STStorageProperties(
+            group="battery",
+            injection_nominal_capacity=100,
+            withdrawal_nominal_capacity=100,
+            reservoir_capacity=100,
+            efficiency=0.8,
+            initial_level=0.5,
+        ),
+        STStorageProperties(
+            group="battery",
+            injection_nominal_capacity=100,
+            withdrawal_nominal_capacity=100,
+            reservoir_capacity=100,
+            efficiency=0.8,
+            initial_level=0.2,
+        ),
+        STStorageProperties(
+            group="battery",
+            injection_nominal_capacity=100,
+            withdrawal_nominal_capacity=100,
+            reservoir_capacity=300,
+            efficiency_withdrawal=0.9,
+            efficiency=0.85,
+            initial_level=0.5,
+        ),
+    ]  # ,
+
+
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_general_sts(
+    sts_list_general_test: list[STStorageProperties],
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    for sts_properties in sts_list_general_test:
+        study_name = f"e2e_general_test_{str(int(100*time()))}"
+        sts_test_procedure(
+            study_name,
+            auto_generated_studies_path,
+            sts_properties,
+            LOAD_FILES_DIR / load_time_serie_file,
+            antares_exec_folder,
+        )
+
+
+@pytest.mark.parametrize("injection_nominal_capacity_base", [50.0, 100.0, 200.0])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_injection_nominal_capacity(
+    injection_nominal_capacity_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=injection_nominal_capacity_base,
+        withdrawal_nominal_capacity=200,
+        reservoir_capacity=300,
+        efficiency=1,
+        initial_level=0.5,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "injection_nominal_capacity",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
+
+
+@pytest.mark.parametrize("withdrawal_nominal_capacity_base", [50.0, 100.0, 200.0])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_withdrawal_nominal_capacity(
+    withdrawal_nominal_capacity_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=200,
+        withdrawal_nominal_capacity=withdrawal_nominal_capacity_base,
+        reservoir_capacity=300,
+        efficiency=1,
+        initial_level=0.5,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "withdrawal_nominal_capacity",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
+
+
+@pytest.mark.parametrize("reservoir_capacity_base", [100.0, 200.0, 300.0])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_reservoir_capacity(
+    reservoir_capacity_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=80,
+        withdrawal_nominal_capacity=80,
+        reservoir_capacity=reservoir_capacity_base,
+        efficiency=1,
+        initial_level=0.5,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "reservoir_capacity",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
+
+
+@pytest.mark.parametrize("efficiency_base", [0.5, 0.6, 0.7])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_efficiency(
+    efficiency_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=80,
+        withdrawal_nominal_capacity=80,
+        reservoir_capacity=200,
+        efficiency=efficiency_base,
+        initial_level=0.5,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "efficiency",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
+
+
+@pytest.mark.parametrize("efficiency_withdrawal_base", [0.5, 0.6, 0.7])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_efficiency_withdrawal(
+    efficiency_withdrawal_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=80,
+        withdrawal_nominal_capacity=80,
+        reservoir_capacity=200,
+        efficiency_withdrawal=efficiency_withdrawal_base,
+        efficiency=0.5 / MODIFICATION_RATIO,
+        initial_level=0.5,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "efficiency_withdrawal",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
+
+
+@pytest.mark.parametrize("initial_level_base", [0.3, 0.5, 0.7])
+@pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES_STS)
+def test_initial_level(
+    initial_level_base: float,
+    load_time_serie_file: str,
+    auto_generated_studies_path: Path,
+    antares_exec_folder: Path,
+) -> None:
+    sts_properties = STStorageProperties(
+        group="battery",
+        injection_nominal_capacity=80,
+        withdrawal_nominal_capacity=80,
+        reservoir_capacity=250,
+        initial_level=initial_level_base,
+    )
+
+    sts_test_procedure_float_param(
+        sts_properties,
+        "initial_level",
+        load_time_serie_file,
+        auto_generated_studies_path,
+        antares_exec_folder,
+    )
diff --git a/tests/antares_historic/test_thermal_model.py b/tests/antares_historic/test_thermal_model.py
index bbe3dee2..760b5803 100644
--- a/tests/antares_historic/test_thermal_model.py
+++ b/tests/antares_historic/test_thermal_model.py
@@ -14,6 +14,7 @@
     first_optim_relgap,
 )
 
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "THERMAL CLUSTER"  : CONSTANT DATA  ##
 LOAD_FILES_DIR = Path("tests/antares_historic/data")
 THERMAL_TEST_REL_ACCURACY = 5 * 1e-5
 THERMAL_TEST_SOLVER = "highs"
@@ -24,6 +25,42 @@
     # "load_matrix_original.txt",
 ]
 
+## TESTING PROCEDURE FOR GEMS MODEL REPRENSENTING ANTARES v9.3 "THERMAL CLUSTERS"  : TESTS  ##
+
+# General tests [OK:test_general_thermal]
+
+# Testing Boolean/discrete parameters
+## group: [TODO]
+## gen_ts: [TODO]
+## must_run: [TODO]
+## law_forced: [TODO]
+## law_planned: [TODO]
+## cost_generation: [TODO]
+
+
+# Testing Float parameters
+## nominal_capacity [OK : test_nominal_capacity]
+## min_stable_power: [OK : test_min_stable_power]
+## min_up_time: [OK : test_min_up_time]
+## min_down_time: [OK : test_min_down_time]
+## marginal_cost: [OK : test_marginal_cost_marketbid_equals]
+## spread_cost: [TODO]
+## fixed_cost: [OK : test_fixed_cost]
+## startup_cost: [OK : test_startup_cost]
+## market_bid_cost: [OK : test_marginal_cost_marketbid_equals]
+## spinning: [TODO]
+## volatility_forced: [TODO]
+## volatility_planned: [TODO]
+## efficiency:  [TODO]
+## variable_o_m_cost: [TODO]
+## co2, nh3, so2:, nox, pm2_5, pm5, pm10, nmvoc, op1, op2, op3, op4, op5 [TODO]
+
+
+# Testing Timeseries parameters
+## series (availability) : [TODO]
+## co2_cost_matrix : [TODO]
+## fuel_cost_matrix : [TODO]
+
 
 def thermal_test_procedure(
     study_name: str,
@@ -421,7 +458,7 @@ def test_marginal_cost_marketbid_equals(
 @pytest.mark.parametrize("base_min_down_time", [2, 4, 6])
 @pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES)
 def test_min_down_time(
-    base_min_down_time: float,
+    base_min_down_time: int,
     load_time_serie_file: str,
     auto_generated_studies_path: Path,
     antares_exec_folder: Path,
@@ -498,7 +535,7 @@ def test_min_down_time(
 @pytest.mark.parametrize("base_min_up_time", [3, 4, 6])
 @pytest.mark.parametrize("load_time_serie_file", LOAD_TIME_SERIE_FILES)
 def test_min_up_time(
-    base_min_up_time: float,
+    base_min_up_time: int,
     load_time_serie_file: str,
     auto_generated_studies_path: Path,
     antares_exec_folder: Path,
diff --git a/tests/antares_historic/utils.py b/tests/antares_historic/utils.py
index 5db6f398..9222b03f 100644
--- a/tests/antares_historic/utils.py
+++ b/tests/antares_historic/utils.py
@@ -175,3 +175,48 @@ def createLinkTestAntaresStudy(
     link.set_capacity_direct(pd.DataFrame(direct_capacity))
     link.set_capacity_indirect(pd.DataFrame(indirect_capacity))
     addHybridBehavior(parent_dir_path / study_name)
+
+
+def createSTSTestAntaresStudy(
+    study_name: str,
+    parent_dir_path: Path,
+    load_time_serie_file: Path,
+    sts_properties: STStorageProperties,
+    # sts_data_frame: pd.DataFrame,
+) -> None:
+    study = create_study_local(
+        study_name=study_name,
+        version=ANTARES_VERSION_CREATED_STUDIES,
+        parent_directory=parent_dir_path,
+    )
+    load_timeserie = pd.read_csv(load_time_serie_file)
+    area = study.create_area(
+        area_name="unique", properties=AreaProperties(energy_cost_unsupplied=20000)
+    )
+    area.set_load(load_timeserie)
+    cluster1 = area.create_thermal_cluster(
+        "prod",
+        ThermalClusterProperties(
+            unit_count=2,
+            nominal_capacity=200,
+            marginal_cost=10,
+            market_bid_cost=10,
+            group=ThermalClusterGroup.NUCLEAR,
+        ),
+    )
+    cluster1.set_series(pd.DataFrame(data=200 * np.ones((8760, 1))))
+
+    cluster2 = area.create_thermal_cluster(
+        "prod2",
+        ThermalClusterProperties(
+            unit_count=1,
+            nominal_capacity=400,
+            marginal_cost=100,
+            market_bid_cost=100,
+            group=ThermalClusterGroup.NUCLEAR,
+        ),
+    )
+    cluster2.set_series(pd.DataFrame(data=400 * np.ones((8760, 1))))
+
+    cluster3 = area.create_st_storage("sts", sts_properties)
+    addHybridBehavior(parent_dir_path / study_name)