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main_AWE_HPS.m
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% main_AWE_HPS calculates the economic performance of a grid-connected HPS with ground-gen fixed-wing AWE power and power smoothing storage
% This function performs energy yield, storage performance, arbitrage revenue and storage degradation
% to compute the economic output of a fixed-wing airborne wind energy system
% over one year of operation at a certain DAM and wind environment.
% Author
% Bart Zweers,
% Delft University of Technology
% clc;
clearvars;
addpath(genpath([pwd '/inputFiles']));
addpath(genpath('C:\Users\bartz\Documents\GitHub\MSc_Bart_Zweers\src'));
addpath(genpath('C:\Users\bartz\Documents\GitHub\MSc_Bart_Zweers\inputFiles'));
addpath(genpath('C:\Users\bartz\Documents\GitHub\MSc_Bart_Zweers\lib'));
%% System inputs
% inputs = loadInputs('inputFile_100kW_AWEHPS.yml');
inputs.subsidy = 110; % Subsidized electricity price [EUR/MWh] 110 from german AWE
inputs.batt_size = 140; % kWh
inputs.batt_type = 1; % P/E or C rate
inputs.batt_price = 130; % [EUR/kWh] source: https://www.nrel.gov/docs/fy21osti/79236.pdf
inputs.batt_eff = 0.90; % Round trip efficiency [%]
inputs.N_li_cycles = 1e4; % [lifetime cycles]
inputs.N_li_years = 10; % [lifetime years]
inputs.UC_price = 6e4; % [EUR/Wh] source: https://www.nrel.gov/docs/fy21osti/79236.pdf
inputs.UC_eff = 1; % Round trip efficiency [%]
inputs.N_UC_cycles = 1e6; % [lifetime cycles]
inputs.N_UC_years = 16; % [lifetime years]
inputs.batt_min = 0.1; % SoC lower limit strage system [-]
inputs.batt_max = 0.9; % SoC upper limit strage system [-]
inputs.business.N_y = 25; % project years
inputs.business.r_d = 0.08; % cost of debt
inputs.business.r_e = 0.12; % cost of equity
inputs.business.TaxRate = 0.25; % Tax rate (25%)
inputs.business.DtoE = 70/30; % Debt-Equity-ratio
inputs.r = inputs.business.DtoE/(1+ inputs.business.DtoE)*inputs.business.r_d*(1-inputs.business.TaxRate) + 1/(1+inputs.business.DtoE)*inputs.business.r_e;
Scen1.ICC = 439e3; % Capital cost kite system without intermediate storage
Scen1.OMC = 12.2e3; % Operational cost kite system without intermediate storage
%% Scenario parameters
[inputs.DAM, inputs.vw, inputs.vol] = Param(readtable('DAM_NL_2019.csv'), ncread('NL_Wind.nc','u100'),ncread('NL_Wind.nc','v100'));
Scen3.w = 4;
Scen3.var = 0.17;
Scen4.w = 4;
Scen4.var = 0.17;
%% AWE performance
% AWE kite power hourly [kW]
[Scen1.P, Scen1.Cf, Scen1.AEP] = AWEperf(inputs.vw, [0 0 0 0 6823.05494180757 20750.8552913604 40035.5511607199 63415.6188669052 85700.7504181529 99999.9999634139 99999.9999993995 100000.000000000 99999.9999612856 99999.9999939655 99999.9999993012 99999.9999999965 100000.000000000 100000.000000000 100000.000000000 100000 100000.000000000]'...
, 4, 10);
% AWE power smoothing timeseries [kW]
[Scen1.P_sm, Scen1.E_sm, Scen1.E_res, Scen2.E_batt_req, Scen1.E_UC_req] = AWEsm(inputs.vw, Scen1.P, [0 0 0 0 39.2114406427936 93.0947366719285 207.022440717841 412.999777754543 702.156555319391 810.070535420744 805.462031428633 808.180879889064 809.929699115073 813.114155193377 816.935309245319 821.167178788006 825.732017996912 830.577439826927 835.618275680234 840.916791101337 847.169221886612]/1e3...
, [0 0 0 0 199.110877845002 87.6714004467267 85.5139407777646 87.3579932218051 93.3237218054094 80.8992375788376 79.9581035213846 79.4595074569484 79.1889899452987 79.0790839654564 79.0738117712405 79.1297853113387 79.2192139488680 79.3068747121754 79.3241622327488 79.2940943437130 79.9040793712790]...
, [0,137.381331953625,137.209204335937,0,-39.7295922699621,7.03564325810917e-14,0], [0 0 0 0 6823.05494180757 20750.8552913604 40035.5511607199 63415.6188669052 85700.7504181529 99999.9999634139 99999.9999993995 100000.000000000 99999.9999612856 99999.9999939655 99999.9999993012 99999.9999999965 100000.000000000 100000.000000000 100000.000000000 100000 100000.000000000]');
%% Scenario 1 AWE + UC
% AWE+UC energy and profit performance
[Scen1.R_arb, Scen1.R_kite, Scen1.f_repl, Scen1.CapEx, Scen1.OpEx] = Scenperf(Scen1.P, zeros(8760,1), inputs.DAM, inputs.subsidy, Scen1.E_sm,...
inputs.N_UC_years, inputs.N_UC_cycles, inputs.UC_price, Scen1.E_UC_req, Scen1.ICC, Scen1.OMC);
% AWE + UC economic metrics
[Scen1.LCoE, Scen1.LRoE, Scen1.LPoE, Scen1.Payb] = EcoMetrics(inputs.r,Scen1.R_kite,Scen1.AEP,Scen1.CapEx,Scen1.OpEx, inputs.business.N_y);
Scen1.NPV = NPV(inputs.r,Scen1.R_kite,Scen1.CapEx,Scen1.OpEx, inputs.business.N_y);
[Scen1.IRR,~] = fsolve(@(r) NPV(r,Scen1.R_kite,Scen1.CapEx,Scen1.OpEx, inputs.business.N_y),0,optimoptions('fsolve','Display','none'));
%% Scenario 2 AWE + Batt
% AWE + Batt energy and profit performance
[Scen2.R_arb, Scen2.R_kite, Scen2.f_repl, Scen2.CapEx, Scen2.OpEx] = Scenperf(Scen1.P, zeros(8760,1), inputs.DAM, inputs.subsidy, Scen1.E_sm, ...
inputs.N_li_years, inputs.N_li_cycles, inputs.batt_price, Scen2.E_batt_req, Scen1.ICC, Scen1.OMC);
% AWE + Batt economic metrics
[Scen2.LCoE, Scen2.LRoE, Scen2.LPoE, Scen2.Payb] = EcoMetrics(inputs.r,Scen2.R_kite,Scen1.AEP,Scen2.CapEx,Scen2.OpEx, inputs.business.N_y);
Scen2.NPV = NPV(inputs.r,Scen2.R_kite,Scen2.CapEx,Scen2.OpEx, inputs.business.N_y);
[Scen2.IRR,~] = fsolve(@(r) NPV(r,Scen2.R_kite,Scen2.CapEx,Scen2.OpEx, inputs.business.N_y),0,optimoptions('fsolve','Display','none'));
%% Scenario 3 Batt arbitrage
% Batt arbitrage bidding dispatch
[Scen3.SoC,Scen3.P] = Dispatcher(Scen3.w, Scen3.var, inputs.DAM, zeros(8760,1), zeros(8760,1), inputs.batt_min*Scen2.E_batt_req, inputs.batt_max*Scen2.E_batt_req,...
Scen2.E_batt_req, inputs.batt_type, inputs.batt_eff);
% Batt arbitrage energy and profit performance
[Scen3.R_arb, Scen3.R_kite, Scen3.f_repl, Scen3.CapEx, Scen3.OpEx] = Scenperf(zeros(8760,1), Scen3.P, inputs.DAM, inputs.subsidy, zeros(8760,1), ...
inputs.N_li_years, inputs.N_li_cycles, inputs.batt_price, Scen2.E_batt_req, 0, 0);
% Batt arbitrage economic metrics
Scen3.arb_E = sum(abs(min(Scen3.P,0)))/1e3;
[Scen3.LCoE, Scen3.LRoE, Scen3.LPoE, Scen3.Payb] = EcoMetrics(inputs.r,Scen3.R_arb,Scen3.arb_E,Scen3.CapEx,Scen3.OpEx, inputs.business.N_y);
Scen3.NPV = NPV(inputs.r,Scen3.R_arb,Scen3.CapEx,Scen3.OpEx, inputs.business.N_y);
[Scen3.IRR,~] = fsolve(@(r) NPV(r,Scen3.R_arb,Scen3.CapEx,Scen3.OpEx, inputs.business.N_y),0,optimoptions('fsolve','Display','none'));
[Scen3.LF, Scen3.VoSA] = StorageMetrics(Scen3.R_arb,Scen3.P,Scen2.E_batt_req,inputs.batt_type);
%% Scenario 4 AWE + Batt arbitrage
% AWE + Batt arbitrage bidding dispatch
[Scen4.SoC,Scen4.P] = Dispatcher(Scen4.w, Scen4.var, inputs.DAM, Scen1.P_sm, Scen1.E_res, inputs.batt_min*Scen2.E_batt_req, inputs.batt_max*Scen2.E_batt_req,...
Scen2.E_batt_req, inputs.batt_type, inputs.batt_eff);
% AWE + Batt arbitrage energy and profit performance
[Scen4.R_arb, Scen4.R_kite, Scen4.f_repl, Scen4.CapEx, Scen4.OpEx] = Scenperf(Scen1.P, Scen4.P, inputs.DAM, inputs.subsidy, Scen1.E_sm, ...
inputs.N_li_years, inputs.N_li_cycles, inputs.batt_price, Scen2.E_batt_req, Scen1.ICC, Scen1.OMC);
% AWE + Batt arbitrage economic metrics
Scen4.R = Scen4.R_arb + Scen4.R_kite;
Scen4.arb_E = sum(abs(min(Scen4.P,0)))/1e3;
Scen4.E_dis = Scen1.AEP + Scen4.arb_E;
[Scen4.LCoE, Scen4.LRoE, Scen4.LPoE, Scen4.Payb] = EcoMetrics(inputs.r,Scen4.R,Scen4.E_dis,Scen4.CapEx,Scen4.OpEx, inputs.business.N_y);
Scen4.NPV = NPV(inputs.r,Scen4.R,Scen4.CapEx,Scen4.OpEx, inputs.business.N_y);
[Scen4.IRR,~] = fsolve(@(r) NPV(r,Scen4.R,Scen4.CapEx,Scen4.OpEx, inputs.business.N_y),0,optimoptions('fsolve','Display','none'));
[Scen4.LF, Scen4.VoSA] = StorageMetrics(Scen4.R_arb,Scen4.P,Scen2.E_batt_req,inputs.batt_type);
%% Display
Scen4.f_cycles = (sum(abs(Scen4.P)) + sum(Scen1.E_sm))/(Scen2.E_batt_req*inputs.N_li_cycles);
Scen2.f_cycles = sum(Scen1.E_sm)/(Scen2.E_batt_req*inputs.N_li_cycles);
Scen4.arbprof = Scen4.R_arb - inputs.batt_price*Scen2.E_batt_req*(Scen4.f_cycles-Scen2.f_cycles);
% disp('---------------------------------------------------------')
% disp(['window = ',num2str(round(Scen4.w,2)),' hrs'])
% disp(['variance = ',num2str(round(Scen4.var,4)),' EUR/MWh'])
% disp(['Scenario 4 E_{dis} = ',num2str(round(Scen4.arb_E,4)),' MWh'])
% disp(['Scenario 4 IRR = ',num2str(round(Scen4.IRR*1e2,4)),' %'])
% disp(['Scenario 4 Arbitrage profit = ',num2str(round(Scen4.arbprof,4)),' EUR'])
Scen1.t_cyc = [0,1.05000000000000,59,60.0500000000000,64.0500000000000,75.0700000000000,79.0700000000000];
Scen1.P_e = [0,137.795628013230,131.353472847588,0,-24.6278969333646,-0.0354535056597164,0];
Scen1.P_m = [0,199.746972005509,191.796732567887,0,-19.1015675261193,-0.0274979846727906,0];
Scen1.P_m_avg = 148250.920152283/1e3;
%% Plots
% Scenario parameters
%%%%%%%%%%%%%%%%%%%%%
% plotScenParam(inputs.DAM, inputs.vw)
% AWE performance
%%%%%%%%%%%%%%%%%
% plotAWEperf(Scen1.P, [0 0 0 0 6823.05494180757 20750.8552913604 40035.5511607199 63415.6188669052 85700.7504181529 99999.9999634139 99999.9999993995 100000.000000000 99999.9999612856 99999.9999939655 99999.9999993012 99999.9999999965 100000.000000000 100000.000000000 100000.000000000 100000 100000.000000000]'...
% , inputs.vw, Scen1.P_e, Scen1.P_m, Scen1.P_m_avg, Scen1.t_cyc)
% Storage performance
%%%%%%%%%%%%%%%%%%%%%
% plotStorperf( Scen1, Scen2, Scen4)
% Arbitrage operation
%%%%%%%%%%%%%%%%%%%%%
% plotArbOpp(inputs, Scen1,Scen2, Scen3, Scen4)
% Plots Scenario 1
%%%%%%%%%%%%%%%%%%
% Scen1.SoC = zeros(8760,1);
% plotScenario(5950, inputs, Scen1, Scen1, Scen1.E_UC_req, inputs.N_UC_cycles)
% Plots Scenario 2
%%%%%%%%%%%%%%%%%%
% plotScenario(5950, inputs, Scen1, Scen2, Scen2.E_batt_req, inputs.N_li_cycles)
% Plots Scenario 3
%%%%%%%%%%%%%%%%%%
% Scen3.E_res = zeros(8760,1);
% Scen3.E_sm = zeros(8760,1);
% Scen3.P_sm = zeros(8760,1);
% plotScenario(5950, inputs, Scen3, Scen3, Scen2.E_batt_req, inputs.N_li_cycles)
% Plots Scenario 4
%%%%%%%%%%%%%%%%%%
% plotScenario(5950, inputs, Scen1, Scen4, Scen2.E_batt_req, inputs.N_li_cycles)
% Discussion
%%%%%%%%%%%%
% plotDiscuss(inputs, Scen1, Scen2, Scen3, Scen4)