error : Objective must be a scalar OptimizationExpression or a struct containing a scalar OptimizationExpression.

Hey ,

I doing multiobjecive optimization using matlab. but i got following error while runing this code.

Objective must be a scalar OptimizationExpression or a struct containing a scalar OptimizationExpression.

Line: 215 ; wavepower_optimization.Objective=NPC_bat + NPC_sc + NPC_fw;

%%%%full code

close all;
clear all;
clc;
load('wave_p.mat');
%%%%%%55555  non variable input
P_owc=Wave_KW;;%%%%% [10000x1]
P_load= 40+10*rand(length(Wave_KW),1)    ;%%%%% [10000x1]

wavepower_optimization=optimproblem;

delta_t=0.0224;
%%%% variables 
% HESS
% Total power output from the HESS will be the sum of power capacity of each ESS 

P_hess=P_owc-P_load;
%P_hess(t) = P_bat(t) + P_fw(t) + P_sc(t);
P_bat=zeros(length(Wave_KW),1);
P_fw=zeros(length(Wave_KW),1);
P_sc=zeros(length(Wave_KW),1);

%%%%%%%%%
P_bat_lower=0;
P_fw_lower=0;
P_sc_lower=0;

P_bat_upper=100;
P_fw_upper=100;
P_sc_upper=100;

r=0.06;
y_bat=10;
y_fw=15;
y_sc=25;
l_owc=10;
u_sc=1;
u_bat=1;
u_fw=1;
m_fw=0.9;
m_bat=0.7;
m_sc=0.9;


eta_d_bat=0.8;
eta_c_bat=0.8;

eta_d_fw=0.8;
eta_c_fw=0.8;

eta_d_bat=0.8;
eta_c_bat=0.8;

eta_d_sc=0.8;
eta_c_sc=0.8;


E_bat_min=0;
E_bat_max=1200;
E_fw_min=0;
E_fw_max=1200;

E_sc_min=0;
E_sc_max=1200;

LPSP_desired=80;
%%%%%%%555
P_bat=optimvar('P_bat',length(Wave_KW),'LowerBound',P_bat_lower,'UpperBound',P_bat_upper);
P_fw=optimvar('P_fw',length(Wave_KW),'LowerBound',P_fw_lower,'UpperBound',P_fw_upper);
P_sc=optimvar('P_sc',length(Wave_KW),'LowerBound',P_sc_lower,'UpperBound',P_sc_upper);


%%%% p_bat (-) is discharging
%%%% p_bat (+) is charging


%%%% p cosntrains
wavepower_optimization.Constraints.econs1=P_bat+P_fw+P_sc==P_hess
%%%%%% define


% Battery pack
%Discharging mode;
%E_bat(t+1)=E_bat(t)-(delta_t.*P_bat(t))/eta_d_bat;  t = 1, 2,….T;




E_bat=cumsum(delta_t*(P_bat-sqrt(P_bat.^2))*0.5/eta_d_bat + delta_t*(P_bat-sqrt(P_bat.^2))*0.5/eta_c_bat)
%E_bat=func_E_bat(delta_t,P_bat,eta_d_bat,eta_c_bat);
%(P_bat-sqrt(P_bat.^2))/2       P_bat.*(P_bat<=0)

%Charging mode;
%E_bat(t+1)=E_bat(t)+ (delta_t.*P_bat(t).*eta_c_bat; t = 1, 2,….T;

%P_bat = E_bat/delta_t;  % battery power
SOC_bat= E_bat./E_bat_max;  % battery SOC

% Flywheel
%Discharging mode;
%E_fw(t+1)=E_fw(t)-(delta_t.*P_fw(t))/eta_d_fw;  t = 1, 2,….T;
%Charging mode;
%E_fw(t+1)=E_fw(t)+ (delta_t.*P_fw(t).eta_c_fw; t = 1, 2,….T;
E_fw=cumsum(delta_t*(P_fw-sqrt(P_fw.^2))*0.5/eta_d_fw + delta_t*(P_fw-sqrt(P_fw.^2))*0.5/eta_c_fw)

%E_fw=func_E_fw(delta_t,P_fw,eta_d_fw,eta_c_fw);

%P_fw = E_fw/delta_t;  % Flywheel power
SOC_fw= E_fw./E_fw_max;  % Flywheel SOC


% Supercapacitor bank
%Discharging mode;
%E_sc(t+1)=E_sc(t)-(delta_t.*P_sc(t))/eta_d_sc;  t = 1, 2,….T;
%Charging mode;
%E_sc(t+1)=E_sc(t)+ (delta_t.*P_sc(t).eta_c_sc; t = 1, 2,….T;
E_sc=cumsum(delta_t.*(P_sc-sqrt(P_sc.^2))*0.5./eta_d_sc + delta_t.*(P_sc-sqrt(P_sc.^2))*0.5./eta_c_sc)
%E_sc=func_E_sc(delta_t,P_sc,eta_d_sc,eta_c_sc)


%P_sc = E_sc/delta_t;  % SC power
SOC_sc= E_sc/E_sc_max;  % SC SOC

% Constraints
wavepower_optimization.Constraints.cons1=E_bat>=E_bat_min;
wavepower_optimization.Constraints.cons2=E_bat<=E_bat_max;

wavepower_optimization.Constraints.cons3=E_fw>=E_fw_min;
wavepower_optimization.Constraints.cons4=E_fw<=E_fw_max;


wavepower_optimization.Constraints.cons5=E_sc>=E_sc_min;
wavepower_optimization.Constraints.cons6=E_sc<=E_sc_max;
% Power balance
%P_owc(t)+ P_hess(t) = P_load(t)

% OWC constraints 
% % turbine generated power range
%omega_owc_min <= omega_owc(t) <= omega_owc_max % turbine safe operation speed range
%%%% why
% HESS constraints
%P_hess_min <= P_hess(t) <= P_hess_max
%E_hess_min <= E_hess(t) <= E_hess_max
%SOC_hess_min <= SOC_hess(t) <= SOC_hess_max
%%%%why

% Battery constraints
%P_bat_min <= P_bat(t) <= P_bat_max
%E_bat_min <= E_bat(t) <= E_bat_max
%SOC_bat_min <= SOC_bat(t) <= SOC_bat_max


% Flywheel constraints
%P_fw_min <= P_fw(t) <= P_fw_max
%E_fw_min <= E_fw(t) <=E_fw_max 
%SOC_fw_min <= SOC_fw(t) <= SOC_fw_max
%omega_fw_min <= omega_fw(t) <= omega_fw_max



% SC constraints
%P_sc_min <= P_sc(t) <= P_sc_max
%E_sc_min <= E_sc(t) <= E_sc_max
%SOC_sc_min <= SOC_sc(t) <= SOC_sc_max
% Loss of power supply probability (LPSP)
%0 < LPSP <= LPSP_desired

%P_supply(t).* delta_t = (P_owc(t).*delta_t + E_hess(t-1) - E_hess_min).*eta_inv
%LPS(t) = (P_load(t)-P_supply(t)).*delta_t when P_load(t) > P_supply(t)
%LPS(t) = 0 when P_load(t) < P_supply(t)
 %LPS  = func_LPS(delta_t,P_owc,P_load)
 P_supply=P_owc+delta_t.*(E_bat+E_fw+E_sc);
 LPS = ( (P_load-P_supply) + sqrt((P_load-P_supply).^2))*0.5.*delta_t;
 
 
%%%%%%%%%%
LPSP=sum(LPS./(P_load.*delta_t))*100; %? %cannot type the exact equation
%LPSP = func_LPSP(LPS,P_owc,P_load,delta_t)

wavepower_optimization.Constraints.cons2=LPSP<=LPSP_desired;

% NPC = Cap(cost) + O&M(cost)+ Rep(cost)
% Cap(Cost)=u_s*P_s*CRF where, u_s = Unit cost in $/kW, 

%Cap_Cost = func_cap_cost(u_s,P_sc,CRF)
% P_s = Power capacity in kW, s is the index for bat, fw and sc
% "Capital recovery factor" CRF = r*(1+r)^y/((1+r)^y-1) where r is the interest rate and y is the life span of each component 


% O&M(Cost)= m_s*u_s* P_s where m_s is a pre-defined percentage 
% Rep(Cost)= u_s*P_s*(l_owc-y)/y  where l_owc is life span of OWC plant and y is life span of each component 
   %battery


%NPC_bat = func_NPC_bat(P_bat,u_bat,y_bat,r,m_bat,l_owc);
CRF_bat = r*(1+r)^y_bat/((1+r)^y_bat-1);
NPC_bat = u_bat*P_bat*CRF_bat + m_bat*u_bat*P_bat + u_bat*P_bat*(l_owc-y_bat)/y_bat ; 

%NPC_sc= func_NPC_sc(P_sc,u_sc,y_sc,r,m_sc,l_owc);
CRF_fw = r*(1+r)^y_fw/((1+r)^y_fw-1);
NPC_fw = u_fw*P_fw*CRF_fw + m_fw*u_fw*P_fw+ u_fw*P_fw*(l_owc-y_fw)/y_fw  ;

%NPC_fw = func_NPC_fw(P_fw,u_fw,y_fw,r,m_fw,l_owc);
CRF_sc = r*(1+r)^y_sc/((1+r)^y_sc-1);
NPC_sc = u_sc*P_sc*CRF_sc + m_sc*u_sc*P_sc+ u_sc*P_sc*(l_owc-y_sc)/y_sc; 

%TCE=func_TCE(NPC_bat, NPC_sc,NPC_fw,P_load);
% Objective Function
%Min(TCE)

% Objective Function


%TCE=(NPC_bat + NPC_sc + NPC_fw);

wavepower_optimization.Objective=NPC_bat + NPC_sc + NPC_fw;
%%%%%%%%%%%%%%%%
x0.P_bat=randn(length(Wave_KW),1)*P_bat_max;
x0.P_fw=randn(length(Wave_KW),1)*P_fw_max;
x0.P_sc=randn(length(Wave_KW),1)*P_sc_max;

%x = particleswarm(problem)
[sol,mincost]=solve(wavepower_optimization,x0)

Answer 1

[Ulisses Anastácio de Oliveira]

I guess you should use:

wavepower_optimization.Objective = sum(NPC_bat + NPC_sc + NPC_fw);