This folder has the workings and results from the grid use model which assesses:
(a) benefits from more efficient grid use 
(b) benefits from avoided costs of inefficient investment in batteries
(c) costs of transmission investment brought forward

Information on parameters used in the model are in the 'Parameter estimates' folder. 

The file 'Variable names.xlsx' has a list of names of variables used in the model.

The grid use scenarios (model files) are in the folder 'Models'. These Python scripts read data from the 'Data' folder and write output to the 'Output' folder.

In the Output folder there is a folder of results for each scenario. 

The models (.py files) in ' Models' folder are:
A. Main scenarios
(1) AoB_demand, tests the effects of implementing the proposal (AoB vs RCPD) on demand
(2) AoB_demand_and_DG_investment, adds potential effects on investment in batteries to the model in (1)
(3) AoB_demand_and_gen_investment, adds potential effects on grid generation investment to the model in (1)
(4) AoB_demand_Major_Capex, (1) with forecast revenue from unapproved major capex
(5) AoB_All_major_capex, combines (1), (2) and (3) and adds forecast revenue from unapproved major capex. Central scenario. 
(6) AoB_All, combines (1), (2) and (3) but excludes forecast revenue from unapproved major capex. Scenario for comparison with (7)
(7) AoB_WUNI, is a scenario for (5) with the WUNI project included in major capex and no other unapproved major capex included
B. Alternatives to the proposal
(8) MWH_Demand_Major_Capex, analogue of (4), tests the effects of shifting from an RCPD charge to a MWh charge, includes forecast revenue from unapproved major capex
(9) AoB_All_Major_Capex_Alternative, analogue of (5), tests the effects of shifting from an RCPD charge to a MWh charge, includes forecast revenue from unapproved major capex
C. Sensitivity scenarios
(10) AoB_All_Major_Capex_2024, implements (5) with the proposal starting in 2024 instead of 2022
(11) AoB_No_AoB_on_existing is a scenario for (5) where AoB charges only apply to future investments
(12) AoB_demand_No_AoB_on_existing a scenario for (4) where AoB charges only apply to future investments
(13) AoB_All_Major_Capex_30_70, a variant on (5) but with area of benefit charges allocated 30% on an economic basis (LCE) and 70% on a reliability basis (AMD) - effectively spreading benefit charges more widely
(14) AOB_All_Major_Capex_Gen_Benefits, a variant on (5) where benefits to generation of transmission investment for reliability purposes is increased from 1% to 37.6%.
(15) AoB_All_Major_Capex_Tiwai_Off, a variant on (5) where NZAS at Tiwai closes in 2030.
D. Parameter sensitivities for central scenario (5)
(16) AoB_All_Major_Capex_Demand_sensitivities, runs (5) with alternate parameter values for aggregate demand elasticities
(17) AoB_All_Major_Capex_DG_sensitivities, runs (5) with alternate parameter values for battery parameter values (supply response and rate of cost decline)
(18) AoB_All_Major_Capex_gen_sensitivities, runs (5) with alternate parameter values for grid-connected generation supply margin and investment parameter values 
(19) AoB_All_Major_Capex_gen_sensitivities_ex_DG, repeats (17) with battery investment excluded.
   

Each scenario output folder contains files that calculate 
(1) aggregate results ('Aggregates.py'), including present valued costs of battery investment brought forward 
(2) welfare gains and costs based on 
	(i) a consumer surplus measure ('Welfare_and_costs_CS.py', the central estimate)
	(ii) a compensating variation measure ('Welfare_and_costs.py', a sensitivity)

To run all scenarios (except the '..._sensitivities.py') in 'Models' and all 'Aggregates.py', 'Welfare_and_costs_CS.py', and 'Welfare_and_costs.py' files 
there is a file called 'Run_all.py' in 'Models'.

BUT file paths in all files will need changing before running all the files. 

To run all of the sensitivity files there is a 'Run_sensitivities.py' file.

In the 'Output' folder there is a file 'Results.py' that will collate results across the different scenarios and put them into the sub-folder 'Results'.

In the sub-folder 'Results' there are two files used to summarise results:
(1) 'Results_tables.py' - which calculates the main results files including 'net_benefits_all.csv' which calculates final summary costs and benefits by scenario. 
(2) 'Results_tables_working.py' - which producesd additional tables for working/reporting purposes, including summaries of sensitivity results.