Dose who know about Optimization with Summation objective function?

Hello, I want make objective function for 24-h Charging / Discharging scheduling.

So, I made like this

for 1:24
    for 1:5
        fun = a*P_char*C_cost1 - (1-a)P_dischar*C_cost2 %% a=charging signal, P = charging discharging power, C = charging discharging cost
        
    end
end

but this function didn't consider other times cost, they just think current time step only.

How can I fix my function? Plz help me. thank you :)

Answer 1

[Alan Weiss]

Maybe you should update fun to remember the entire sum, not just the final one. And maybe you should name your indices.

fun = optimexpr;
for i = 1:24
    for j = 1:5
        fun = fun + a(i)*P_char(i)*C_cost1(j) - (1-a(i))*P_dischar(i)*C_cost2(j) %% a=charging signal, P = charging discharging power, C = charging discharging cost
        
    end
end

I may have messed up the i and j indices, but I hope that you get the idea. You could probably create the expression without any loops, too, and it would be more efficient to do so. See Expressions for Objective Functions.

Alan Weiss

MATLAB mathematical toolbox documentation

[JunGi Kim]

Really thank you for your answer.

for minlp, I write objective fuction like this, from above question.

fun = @(x) sum(x(1)*x(2)*cost_p(i) - x(3)*x(4)*cost_p(i));

How can I fix my func? to use j at x?

[JunGi Kim]

and I send my code for get answer.

cur_soc = Init_ev_SOC;
for i=1:5
    for j=1:num_EV
%objective Function
        % minimize 
fun = @(x) x(1)*x(2)*cost_1(i) - x(3)*x(4)*cost_2(i);

% x(1) = charging mode (1,0) , x(2) = charging power,
% x(3) = discharging mode(1,0), x(4) = discharging power


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
                          % constraints %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%Non-linear Constraints (cl <= nlcon(x) <= cu)
nlcon = @(x) [
    (x(1)*x(2) - x(3)*x(4))/ev_bat;
    ];

cl = [];
cu = [];

%Inequality Constraints (Ax <= b)
A = [];
b = [];

%Equality Constraints (Aeqx = beq)

Aeq = [];
beq = [];


% Initial Guess
x0 = [0 0 1 10];

% Bounds (lb<=x<=ub)
lb = zeros(4,1);
ub = [1, charging_rate, 1,charging_rate];

%range of n to solve for
% Set
xtype = 'BCBC';

Opt = opti('fun', fun,'ineq', A,b, 'eq', Aeq, beq, 'nl',nlcon,cl,cu,'bounds', lb, ub, 'x0', x0, 'xtype', xtype);

% Solve

[x,fval,exitflag,info] = solve(Opt)

deltaSoC = (x(1)*x(2) - x(3)*x(4))/ev_bat
cur_soc(j) = cur_soc(j) + deltaSoC
cur_soc(j,1);

    end
end

[Alan Weiss]

I am still not sure that I understand you.

First, are you using the problem-based approach or the solver-based approach? I thought at first you were using the problem-based approach, but now I am not so sure.

For the problem-based approach, you need to create an optimization problem and optimization variables. Your objective function should not be a function handle, but instead should be an optimization expression in the optimization variables. You can use this approach only for recent MATLAB versions.

For the solver-based approach, you need to get your indices straight.

I do not understand what the command opti('fun', fun,...) does.

Good luck,

Alan Weiss

MATLAB mathematical toolbox documentation

Answer 2

[Muhammad Umair Javed]

Hi Kim

I am also working on a mixed integer nonlinear problem and using MINLP MATLAB toolbox, and using SCIP solver. I am just wondering how you to give a nonlinear objective function in this suit?

Thanking you in anticipation

Umaie