# -*- coding: utf-8 -*-
"""
Analyse revenue and prices, checking total revenue is collected 
and looking for decomposition of revenue.

With RCPD, revenue is AC to load and DC to south island generation

With AoB, revenue is AC and DC to load and generation according to benefits
from existing and future assets. Plus load pays for a residual that declines
through time

"""
import numpy as np
import pandas as pd
import random
import matplotlib
import matplotlib.pyplot as plt
import itertools

in_fn = "C:/Users/theot/Dropbox (Sense.)/2018-19 EA TPM CBA (Shared)/Step 3/AoB model/Output/All_major_capex/"
out_fn="C:/Users/theot/Dropbox (Sense.)/2018-19 EA TPM CBA (Shared)/Step 3/AoB model/Output/All_major_capex/"

# Objective, function that takes two files as arguments and returns a file of
# analysis for revenue

# DG costs  - assumed capital cost per MW and rate of growth
dg_capex_per_mw=733000
dg_capex_g = 0.93 

#Discount rate
r=1.06

# Demand results
rcpd = pd.read_csv(in_fn+"rcpd.csv") 
aob = pd.read_csv(in_fn+"aob.csv")
gen_rcpd = pd.read_csv(in_fn+"gen_rcpd.csv") 
gen_aob = pd.read_csv(in_fn+"gen_aob.csv")



# Parameters
# A. TRANSMISSION REVENUE
# (i) Load
load_revenue=rcpd[['bb','type','m_yr']].copy()
load_revenue['rcpd']=rcpd.pk_rev+rcpd.dg_rev+rcpd.sh_rev+rcpd.off_rev
load_revenue['aob']=aob.pk_rev+aob.dg_rev+aob.sh_rev+aob.off_rev
load_revenue['change']=load_revenue.aob-load_revenue.rcpd
load_revenue['percentage_change']=load_revenue.aob/load_revenue.rcpd-1
load_revenue.to_csv(out_fn+"load_revenue.csv")
load_tot_rev=load_revenue[['m_yr','rcpd','aob']].groupby(['m_yr']).sum().reset_index()

# (ii) Generation
gen_revenue=gen_rcpd[['bb','m_yr']].copy()
gen_revenue['gen_rcpd']=gen_rcpd.pk_rev+gen_rcpd.dg_rev+gen_rcpd.sh_rev+gen_rcpd.off_rev
gen_revenue['gen_aob']=gen_aob.pk_rev+gen_aob.dg_rev+gen_aob.sh_rev+gen_aob.off_rev
gen_revenue['change']=gen_revenue.gen_aob-gen_revenue.gen_rcpd
gen_revenue['percentage_change']=gen_revenue.gen_aob/gen_revenue.gen_rcpd-1
gen_revenue.to_csv(out_fn+"gen_revenue.csv")
gen_tot_rev = gen_revenue[['m_yr','gen_rcpd','gen_aob']].groupby(['m_yr']).sum().reset_index()

# Totals
total_revenue = load_tot_rev[['m_yr','rcpd','aob']]
total_revenue = total_revenue.merge(gen_tot_rev)
total_revenue.columns=['m_yr','load_rcpd','load_aob','gen_rcpd','gen_aob']
total_revenue['rcpd']=total_revenue.load_rcpd+total_revenue.gen_rcpd
total_revenue['aob']=total_revenue.load_aob+total_revenue.gen_aob
total_revenue.to_csv(out_fn+"total_revenue.csv")

# B. DEMAND VOLUMES

# (i) Demand
load_q=rcpd[['bb','type','m_yr']].copy()
load_q['rcpd']=rcpd.pk_q+rcpd.dg_q+rcpd.sh_q+rcpd.off_q
load_q['aob']=aob.pk_q+aob.dg_q+aob.sh_q+aob.off_q
load_q['change']=load_q.aob-load_q.rcpd
load_q['percentage_change']=load_q.aob/load_q.rcpd-1
load_tot_q=load_q[['m_yr','rcpd','aob']].groupby(['m_yr']).sum().reset_index()
load_tot_q['percentage_change']=load_tot_q.aob/load_tot_q.rcpd-1
load_q.to_csv(out_fn+"load.csv")
load_tot_q.to_csv(out_fn+"total_load.csv")

# (ii) Generation quantites
gen_q=gen_rcpd[['bb','type','m_yr']].copy()
gen_q['rcpd']=gen_rcpd.pk_q+gen_rcpd.dg_q+gen_rcpd.sh_q+gen_rcpd.off_q
gen_q['aob']=gen_aob.pk_q+gen_aob.dg_q+gen_aob.sh_q+gen_aob.off_q
gen_q['change']=gen_q.aob-gen_q.rcpd
gen_q['percentage_change']=gen_q.aob/gen_q.rcpd-1
gen_tot_q=gen_q[['m_yr','rcpd','aob']].groupby(['m_yr']).sum().reset_index()
gen_tot_q['percentage_change']=gen_tot_q.aob/gen_tot_q.rcpd-1
gen_q.to_csv(out_fn+"generation.csv")
gen_tot_q.to_csv(out_fn+"total_generation.csv")

# C. EXPENDITURE

load_e=rcpd[['bb','type','m_yr']].copy()
load_e['rcpd']=rcpd.pk_e+rcpd.dg_e+rcpd.sh_e+rcpd.off_e
load_e['aob']=aob.pk_e+aob.dg_e+aob.sh_e+aob.off_e
load_e['change']=load_e.aob-load_e.rcpd
load_e['percentage_change']=load_e.aob/load_e.rcpd-1
load_e.to_csv(out_fn+"expenditure.csv")
load_tot_e=load_e[['m_yr','rcpd','aob']].groupby(['m_yr']).sum().reset_index()
load_tot_e.to_csv(out_fn+"total_expenditure.csv")

# Average prices - inclusive of transmission costs
load_p=rcpd[['bb','type','m_yr']].copy()
load_p['rcpd']=load_e.rcpd/load_q.rcpd
load_p['aob']=load_e.aob/load_q.aob
load_p['change']=load_p.aob-load_p.rcpd
load_p['percentage_change']=load_p.aob/load_p.rcpd-1
load_tot_p=pd.DataFrame(load_tot_e['m_yr'].copy())
load_tot_p['rcpd']=load_tot_e.rcpd/load_tot_q.rcpd
load_tot_p['aob']=load_tot_e.aob/load_tot_q.aob
load_tot_p['change']=load_tot_p.aob-load_tot_p.rcpd
load_tot_p['percentage_change']=load_tot_p.aob/load_tot_p.rcpd-1
load_p.to_csv(out_fn+"average_prices.csv")
load_tot_p.to_csv(out_fn+"total_average_prices.csv")

# DG investment
dg=pd.DataFrame(load_tot_e['m_yr'].copy())
dg['rcpd_mw']=rcpd.groupby(['m_yr'])['dg_max'].sum().reset_index()['dg_max']
dg['rcpd_inv']=dg.rcpd_mw.diff()*(dg_capex_per_mw*(dg_capex_g**(dg.m_yr-2017)))
dg['rcpd_q']=rcpd.groupby(['m_yr'])['dg_q'].sum().reset_index()['dg_q']
dg['aob_mw']=aob.groupby(['m_yr'])['dg_max'].sum().reset_index()['dg_max']
dg['aob_inv']=dg.aob_mw.diff()*(dg_capex_per_mw*(dg_capex_g**(dg.m_yr-2017)))
dg['aob_q']=aob.groupby(['m_yr'])['dg_q'].sum().reset_index()['dg_q']
dg['mw_change']=dg.aob_mw-dg.rcpd_mw
dg['mw_percentage_change']=dg.aob_mw/dg.rcpd_mw-1
dg['mw_cost']=dg_capex_per_mw*(dg_capex_g**(dg.m_yr-2017))
dg['inv_change']=dg.aob_inv-dg.rcpd_inv
dg['pv_inv_change']=dg.inv_change*(1/(r**(dg.m_yr-2019)))
dg.to_csv(out_fn+'total_dg.csv')
dg.pv_inv_change.sum()