Can someone please know from the following code what’s the reason for in-feasibility error and suggest the solution of error?

cvx_clear

%------------input data --------------------------------------%

Input_data = xlsread(‘h-24-realtestdata.xlsx’);

% -------------- Parameters --------------------------- %

n = Input_data(:,20);

T = 24; % Time horizon

e = 2; % Number of eVB’s

alpha_e = 1.5; % eVB depreciation cost coefficent

soc_cap = 60; % eVB’s capacity

soc_min = 0.15*soc_cap; % eVB’s lower bound
soc_max = 0.9*soc_cap; % eVB’s upper bound

P_max = 10; % Maximum charging power

P_gridmax = 1000;

soc_inc(1:T,1:e) = 15;

P_min = 0;

% --------------- CVX Begin ---------------------%

cvx_begin

% -------------------Define solver -----------------------%

cvx_solver MOSEK

% ------------------- Continuous Variables -----------------------------%

variables P_gridbuy(T,1) P_gridsell(T,1) P_cha(T,e) P_discha(T,e) soc_short(T,e);

% ------------------ Expressions -------------------------------------%

expressions soc(T,e) A(T,e) B(T,e) C(T,e)

% -------------------- Binary Variables ----------------------%

variable b_buysell(T,1) binary;

variable b_chadischa(T,e) binary;

variable b_sw(T,e) binary;

% ------------------- Initial SOC ---------------------%

soc(1,1:e) = 40;

% --------------------- SOC evolution equations ----------------------%

for t=1:T-1

soc(t+1,1:e) = soc(t,1:e) + P_cha(t,1:e)- P_discha(t,1:e) -(A(t,1:e) + B(t,1:e)- C(t,1:e)) + soc_inc(t+1,1:e).*b_sw(t,1:e);

end

% --------------------- Objective function ----------------------------%

minimize(sum(Input_data(:,19).*(P_gridbuy - P_gridsell) + sum(soc_short(T,1:e),2) + sum(alpha_e*P_cha.^2,2)…

+ sum(alpha_e*P_discha.^2,2)));

%------------------------- Constraints -----------------------------%

subject to

P_gridbuy + sum(P_discha,2) == P_gridsell + sum(P_cha,2);

soc + soc_short >= soc_max.*b_sw
P_gridbuy >= 0;
P_gridsell >= 0;
P_gridbuy <= P_gridmax*(1 - b_buysell);

P_gridsell <= P_gridmax

*b_buysell;*

P_cha >= 0;

P_discha >= 0;

P_cha <= P_maxb_chadischa;

P_cha >= 0;

P_discha >= 0;

P_cha <= P_max

P_discha <= P_max*(1 - b_chadischa);

soc_min <= soc_short <= soc_max

soc_min <= soc <= soc_max;

sum(b_sw,2) >= n;

0 <= P_cha <= (1-b_sw)*P_max

0 <= P_discha <= (1-b_sw)*P_max

% ----------- Linearization constraints -------------%

% following constraints converts the product of continuous and binary variables {(soc + P_cha - P_discha)*b_sw} in the soc evolution
% to the auxilary variables (A, B, C)-----------------------%
A <= soc_max*b_sw;

A >= soc_min

*b_sw;*

A <= soc - soc_min(1-b_sw);

A <= soc - soc_min

A >= soc - soc_max*(1-b_sw);

B <= P_max

*b_sw;*

B >= P_minb_sw;

B >= P_min

B <= P_cha - P_min*(1-b_sw);

B >= P_cha - P_max*(1-b_sw);

C <= P_max

*b_sw;*

C >= P_minb_sw;

C >= P_min

C <= P_discha - P_min*(1-b_sw);

C >= P_discha - P_max*(1-b_sw);

` cvx_end`