simulation id rbd

src/calculation_target_reliability/router.py

@@ -59,7 +59,7 @@ async def get_target_reliability(
     # )
     
     if not simulation_id:
-        simulation_id = "default"
+        simulation_id = "6825d5b9-c165-45fe-b553-8c71c1a15903"
 
     results = await get_simulation_results(
         simulation_id=simulation_id,

src/calculation_target_reliability/service.py

@@ -48,9 +48,9 @@ async def get_simulation_results(*, simulation_id: str, token: str):
         "Content-Type": "application/json"
     }
 
-    calc_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/default?nodetype=RegularNode"
+    calc_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/{simulation_id}?nodetype=RegularNode"
     # plot_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/plot/{simulation_id}?nodetype=RegularNode"
-    calc_plant_result = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/default/plant"
+    calc_plant_result = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/{simulation_id}/plant"
 
     async with httpx.AsyncClient(timeout=300.0) as client:
         calc_task = client.get(calc_result_url, headers=headers)

src/calculation_time_constrains/service.py

@@ -1112,7 +1112,7 @@ class OptimumCostModel:
     
     async def get_failures_prediction(self, simulation_id: str, location_tag):
         # calc_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/{simulation_id}?nodetype=RegularNode"
-        plot_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/plot/default/{location_tag}?use_location_tag=1"
+        plot_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/plot/{simulation_id}/{location_tag}?use_location_tag=1"
         # calc_plant_result = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/{simulation_id}/plant"
 
         
@@ -1144,6 +1144,37 @@ class OptimumCostModel:
         
         return calculate_failures_per_month(time_series)
     
+    async def get_simulation_results(self):
+        headers = {
+            "Authorization": f"Bearer {self.token}",
+            "Content-Type": "application/json"
+        }
+
+        calc_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/default?nodetype=RegularNode"
+        # plot_result_url = f"{RBD_SERVICE_API}/aeros/simulation/result/plot/{simulation_id}?nodetype=RegularNode"
+        calc_plant_result = f"{RBD_SERVICE_API}/aeros/simulation/result/calc/default/plant"
+
+        async with httpx.AsyncClient(timeout=300.0) as client:
+            calc_task = client.get(calc_result_url, headers=headers)
+            # plot_task = client.get(plot_result_url, headers=headers)
+            plant_task = client.get(calc_plant_result, headers=headers)
+
+            # Run all three requests concurrently
+            calc_response, plant_response = await asyncio.gather(calc_task, plant_task)
+
+            calc_response.raise_for_status()
+            # plot_response.raise_for_status()
+            plant_response.raise_for_status()
+
+            calc_data = calc_response.json()["data"]
+            # plot_data = plot_response.json()["data"]
+            plant_data = plant_response.json()["data"]
+
+            return {
+                "calc_result": calc_data,
+                # "plot_result": plot_data,
+                "plant_result": plant_data
+            }
 
     async def calculate_cost_all_equipment(
         self,
@@ -1170,6 +1201,10 @@ class OptimumCostModel:
 
             print("Processing cost calculations...")
             
+            importance_results = await self.get_simulation_results()
+            
+            equipment_birbaum = {imp['aeros_node']['node_name']: imp['contribution'] for imp in importance_results["calc_result"]}
+
             # Process each equipment's costs
             fleet_results = []
             total_corrective_costs = np.zeros(max_interval)
@@ -1185,10 +1220,16 @@ class OptimumCostModel:
                 service_cost = equipment.service_cost
                 
                 failures_prediction = await self.get_failures_prediction(
-                    simulation_id = "864f1558-79cc-40b1-8d1f-8e7339d9d8ce",
+                    simulation_id = "6825d5b9-c165-45fe-b553-8c71c1a15903",
                     location_tag=location_tag
                 )
                 
+                energy_price_per_mwh = 1000000
+                
+                birnbaum = equipment_birbaum.get(location_tag, 0)
+                mw_lost_when_failed = birnbaum * 660
+                cost_per_hour_downtime = mw_lost_when_failed * energy_price_per_mwh
+
                 # # Get pre-fetched reliability data
                 # failure_rate = all_reliabilities.get(location_tag, {})
                 # # failure_rate = self._get_equipment_fr(location_tag, self.token)
@@ -1197,7 +1238,7 @@ class OptimumCostModel:
                 # Calculate costs using vectorized operations
                 predicted_costs = self._calculate_costs_vectorized(
                     preventive_cost=overhaul_cost + service_cost,
-                    failure_replacement_cost=cost_per_failure,
+                    failure_replacement_cost=cost_per_failure + cost_per_hour_downtime,
                     failures_prediction=failures_prediction
                 )