clear all
clc
close all
global EV 
global CS_first CS_second CS_third Ct_available_EU Pt_available_EU pc periods N home_vehicles max_loss planning_periods cpt_available_EU
global list_of_total_switches_made_1st 
global frequency_of_switches_1st 
global total_x_1st
global total_y_1st
global list_of_total_z_1st
global frequency_of_z_1st
global EV_1st
global list_of_total_switches_made_2nd 
global frequency_of_switches_2nd
global total_x_2nd
global total_y_2nd
global list_of_total_z_2nd
global frequency_of_z_2nd
global EV_2nd
global list_of_total_switches_made_3rd
global frequency_of_switches_3rd
global total_x_3rd
global total_y_3rd
global list_of_total_z_3rd
global frequency_of_z_3rd
global EV_3rd
global no_home_vehicles
global home_vehicle_SOC_predictions_1st
global home_vehicle_SOC_predictions_2nd
global home_vehicle_SOC_predictions_3rd
%% Initialize all the required variables and parameters
%Choose the number of vehicles you want taking mid-home trips to discharge
%at homes - default = 20
no_home_vehicles = 20;
main_initialization
max_loss = -100; %maximum cost in cents an EV owner is willing to pay for charging
%Customer satisfaction variables
CS_first = 0;
CS_second = 0;
CS_third = 0;
%% Simulation - 1st scenario
EV_initial = EV;
first_scenario
%Customer satisfaction calculation for first scenario
for t = 1:periods
    for i = 1:N
        CS_first = CS_first + EV(i).y(t)*Pt_available_EU(t) - EV(i).x(t)*Ct_available_EU(t);
    end
end
first_scenario_plot_parameters
%% Analysis of travelling EV's that took home trips - first scenario
fprintf('FOR THE FIRST SCENARIO,\n\n');
for j = 1:length(home_vehicles)
    fprintf('Electric vehicle %i had the following states of charge at the associated arrival/departure times:\n', home_vehicles(j));
    for i = 1:length(EV(home_vehicles(j)).schedule)
        if rem(i,2) ~= 0
            fprintf('Arrival time at period %i => SOC of %i percent of maximum battery level\n', EV(home_vehicles(j)).schedule(i), EV(home_vehicles(j)).soc(EV(home_vehicles(j)).schedule(i))*100/EV(home_vehicles(j)).mc);
        else
            fprintf('Departure time at period %i => SOC of %i percent of maximum battery level\n', EV(home_vehicles(j)).schedule(i), EV(home_vehicles(j)).soc(EV(home_vehicles(j)).schedule(i))*100/EV(home_vehicles(j)).mc);
        end
    end
    fprintf('\n');
    fprintf('Estimated SOC percentage at the end of the simulation = %i percent\n', home_vehicle_SOC_predictions_1st(i)*100/EV(home_vehicles(j)).mc);
    fprintf('Actual SOC percentage at the end of the simulation = %i percent\n', EV(home_vehicles(j)).soc(EV(home_vehicles(j)).schedule(6))*100/EV(home_vehicles(j)).mc);
    fprintf('\n');
end
%% Simulation - 2nd scenario
EV = EV_initial;
second_scenario
%Customer satisfaction calculation for second scenario.
for i = 1:N
    for t = 1:periods
        CS_second = CS_second + EV(i).y(t)*Pt_available_EU(t) - EV(i).x(t)*Ct_available_EU(t);
    end
    CS_second = CS_second - pc*EV(i).z;
end