Update calculator.py

Author: HWAN-OH

calculator.py

@@ -3,8 +3,8 @@
 
 def calculate_5yr_tco(config, user_inputs):
     """
-    Calculates 5-year TCO with correct initial CAPEX reporting.
-    초기 CAPEX 보고 로직이 수정된 버전입니다.
+    Calculates 5-year TCO with detailed cost breakdowns for CAPEX and OPEX.
+    CAPEX와 OPEX에 대한 상세 비용 내역을 포함하여 5년 TCO를 계산합니다.
     """
     demand_profile = user_inputs['demand_profile']
     energy_mix = user_inputs['energy_mix']
@@ -15,7 +15,7 @@ def calculate_5yr_tco(config, user_inputs):
     asset_lifetime = config.get('asset_lifetime_years', 20)
     discount_rate = econ_assumptions['discount_rate']
 
-    # --- 1. Calculate Initial CAPEX (at t=0) ---
+    # --- 1. Calculate Initial CAPEX (at t=0) and details ---
     initial_capex = 0
     capex_details = {}
     peak_demand_kw_yr1 = demand_profile['peak_demand_mw'].iloc[0] * 1000
@@ -27,8 +27,9 @@ def calculate_5yr_tco(config, user_inputs):
             capex_details[f"{source}_capex"] = capex
             initial_capex += capex
 
-    # --- 2. Calculate PV of all costs over the simulation period ---
+    # --- 2. Initialize variables for loop ---
     results = []
+    opex_breakdown_pv = {}
     total_opex_pv = 0
     total_replacement_capex_pv = 0
     total_demand_pv_kwh = 0
@@ -43,7 +44,7 @@ def calculate_5yr_tco(config, user_inputs):
         annual_capex_replacement = 0
         fc_params = tech_params.get('hydrogen_SOFC', {})
         stack_lifetime = fc_params.get('stack_lifetime_years', 4)
-        if (simulation_year - 1) > 0 and (simulation_year - 1) % stack_lifetime == 0 and energy_mix.get('hydrogen_SOFC', 0) > 0:
+        if simulation_year > 1 and (simulation_year - 1) % stack_lifetime == 0 and energy_mix.get('hydrogen_SOFC', 0) > 0:
             fc_capacity_kw = peak_demand_kw_yr1 * (energy_mix['hydrogen_SOFC'] / 100)
             replacement_rate = fc_params.get('stack_replacement_cost_rate', 0.4)
             replacement_cost = (fc_capacity_kw * fc_params.get('capex_per_kw', 0)) * replacement_rate
@@ -52,61 +53,67 @@ def calculate_5yr_tco(config, user_inputs):
 
         total_replacement_capex_pv += annual_capex_replacement * discount_factor
 
-        # Annual OPEX
-        # ... (OPEX calculation logic remains the same)
-        annual_opex = 0
-        total_emissions_kg = 0
+        # Annual OPEX Calculation
+        opex_details_annual = {}
         initial_grid_price = scenario_params.get('grid_price_per_kwh', 0.12)
         initial_ng_price = scenario_params.get('gas_fuel_cost_per_kwh', 0.08)
+
         grid_kwh = annual_demand_kwh * (energy_mix.get('grid', 0) / 100)
-        grid_price = initial_grid_price * ((1 + econ_assumptions['grid_escalation']) ** (simulation_year - 1))
-        annual_opex += grid_kwh * grid_price
-        total_emissions_kg += grid_kwh * tech_params.get('grid', {}).get('carbon_emission_factor', 0)
+        opex_details_annual['grid_purchase_cost'] = grid_kwh * (initial_grid_price * ((1 + econ_assumptions['grid_escalation']) ** (simulation_year - 1)))
+        
+        total_emissions_kg = grid_kwh * tech_params.get('grid', {}).get('carbon_emission_factor', 0)
+        
+        opex_details_annual['o&m_cost'] = 0
+        opex_details_annual['h2_fuel_cost'] = 0
+        opex_details_annual['ng_fuel_cost'] = 0
+
         for source in ['solar', 'wind', 'hydrogen_SOFC', 'NG_SOFC']:
             if energy_mix.get(source, 0) > 0:
                 source_params = tech_params.get(source, {})
                 capacity_kw = peak_demand_kw_yr1 * (energy_mix[source] / 100)
-                annual_opex += (capacity_kw * source_params.get('capex_per_kw', 0)) * source_params.get('opex_rate', 0.015)
+                opex_details_annual['o&m_cost'] += (capacity_kw * source_params.get('capex_per_kw', 0)) * source_params.get('opex_rate', 0.015)
+                
                 if source == 'hydrogen_SOFC':
-                    energy_kwh = annual_demand_kwh * (energy_mix[source] / 100)
-                    fuel_cost = econ_assumptions['h2_fuel_cost'] * ((1 + econ_assumptions['fuel_escalation']) ** (simulation_year - 1))
-                    annual_opex += energy_kwh * fuel_cost
+                    opex_details_annual['h2_fuel_cost'] += (annual_demand_kwh * (energy_mix[source] / 100)) * (econ_assumptions['h2_fuel_cost'] * ((1 + econ_assumptions['fuel_escalation']) ** (simulation_year - 1)))
                 elif source == 'NG_SOFC':
-                    energy_kwh = annual_demand_kwh * (energy_mix[source] / 100)
-                    fuel_cost = initial_ng_price * ((1 + econ_assumptions['fuel_escalation']) ** (simulation_year - 1))
-                    annual_opex += energy_kwh * fuel_cost
-                    total_emissions_kg += energy_kwh * source_params.get('carbon_emission_factor', 0)
+                    ng_kwh = annual_demand_kwh * (energy_mix[source] / 100)
+                    opex_details_annual['ng_fuel_cost'] += ng_kwh * (initial_ng_price * ((1 + econ_assumptions['fuel_escalation']) ** (simulation_year - 1)))
+                    total_emissions_kg += ng_kwh * source_params.get('carbon_emission_factor', 0)
+
+        opex_details_annual['carbon_tax_cost'] = 0
         if econ_assumptions['carbon_tax_year'] and simulation_year >= econ_assumptions['carbon_tax_year']:
-            annual_opex += (total_emissions_kg / 1000) * econ_assumptions['carbon_tax_price']
+            opex_details_annual['carbon_tax_cost'] = (total_emissions_kg / 1000) * econ_assumptions['carbon_tax_price']
+        
+        annual_opex = sum(opex_details_annual.values())
 
+        # Accumulate Present Values
         total_opex_pv += annual_opex * discount_factor
         total_demand_pv_kwh += annual_demand_kwh * discount_factor
+        for key, value in opex_details_annual.items():
+            opex_breakdown_pv[key] = opex_breakdown_pv.get(key, 0) + (value * discount_factor)
 
         results.append({'year': actual_year, 'annual_opex': annual_opex})
 
     # --- 3. Final Summary Calculation ---
-    total_capex_pv_for_tco = initial_capex + total_replacement_capex_pv
-    tco_5yr = total_capex_pv_for_tco + total_opex_pv
+    total_capex_pv = initial_capex + total_replacement_capex_pv
+    tco_5yr = total_capex_pv + total_opex_pv
 
-    # For LCOE, we need to annualize the total investment over the asset lifetime
+    # For LCOE, annualize the total investment over the asset lifetime
     if discount_rate > 0:
         crf = (discount_rate * (1 + discount_rate) ** asset_lifetime) / ((1 + discount_rate) ** asset_lifetime - 1)
     else:
         crf = 1 / asset_lifetime
-    annualized_total_investment = total_capex_pv_for_tco * crf
-    
-    # Average annual OPEX (PV)
-    avg_annual_opex_pv = total_opex_pv / len(demand_profile)
+    annualized_total_investment = total_capex_pv * crf
 
-    # Average annual demand (PV)
-    avg_annual_demand_pv_kwh = total_demand_pv_kwh / len(demand_profile)
+    avg_annual_opex_pv = total_opex_pv / config.get('simulation_period_years', 5)
+    avg_annual_demand_pv_kwh = total_demand_pv_kwh / config.get('simulation_period_years', 5)
 
     summary = {
         '5_Year_TCO': tco_5yr,
         'Total_Initial_CAPEX': initial_capex,
-        'Total_CAPEX_PV': total_capex_pv_for_tco,
+        'Total_CAPEX_PV': total_capex_pv,
         'Total_OPEX_PV': total_opex_pv,
         'LCOE_Avg_5yr': ((annualized_total_investment + avg_annual_opex_pv) / avg_annual_demand_pv_kwh) * 1000 if avg_annual_demand_pv_kwh > 0 else 0
     }
 
-    return pd.DataFrame(results), summary, capex_details, {}
+    return pd.DataFrame(results), summary, capex_details, opex_breakdown_pv