Add cumulative discounted cash flows to yearly finantial terms

src/ECModel.jl

@@ -873,6 +873,7 @@ Returns
 -------
     The output value is a NamedTuple with the following elements
     - NPV: the NPV of each user given the final profit_distribution adjustment by game theory techniques
+    - CUM_DCF: cumulative discounted cash flows
     - CAPEX: the annualized CAPEX
     - OPEX: the annualized operating costs (yearly maintenance and yearly peak and energy grid charges)
     - REP: the annualized replacement costs
@@ -983,9 +984,15 @@ function split_yearly_financial_terms(ECModel::AbstractEC, profit_distribution=n
         ],
         year_set, user_set_financial
     )
+    # Cumulative Discounted Cash Flows
+    CUM_DCF = JuMP.Containers.DenseAxisArray(
+        cumsum((Ann_reward .- CAPEX .- OPEX .- Ann_Replacement .+ Ann_Recovery).data .* ann_factor, dims=1),
+        year_set
+    )
 
     return (
         NPV=NPV,
+        CUM_DCF=CUM_DCF,
         CAPEX=CAPEX,
         OPEX=OPEX,
         OEM=Ann_Maintenance,
@@ -1037,10 +1044,11 @@ function business_plan(ECModel::AbstractEC,profit_distribution=nothing, user_set
     year_set = business_plan.year_set
 
     # Create an empty DataFrame
-    df_business = DataFrame(Year = Int[], CAPEX = Float64[], OEM = Float64[], EN_SELL = Float64[], EN_CONS = EN_SELL = Float64[], PEAK = Float64[], REP = Float64[], 
+    df_business = DataFrame(Year = Int[], CUM_DCF=Float[], CAPEX = Float64[], OEM = Float64[], EN_SELL = Float64[], EN_CONS = EN_SELL = Float64[], PEAK = Float64[], REP = Float64[], 
     REWARD = Float64[], RV = Float64[])
     for i in year_set
         Year = year_set[i+1]
+        CUM_DCF = 
         CAPEX = sum(business_plan.CAPEX[i, :])
         OEM = sum(business_plan.OEM[i, :])
         EN_SELL = sum(business_plan.EN_SELL[i, :])