import numpy as np import matplotlib.pyplot as plt # 参数设置 R1 = 1.2e-3 R2 = 9.2e-3 Cin = 1.1e6 Cwall = 1.86e8 PN = 8.0 q_out = -15.0 q_in0 = 20.0 dt = 60 # 时间步长，单位为秒 T = 24 * 60 * 60 # 模拟时间总长，单位为秒 # 定义微分方程 def differential_equation(q_in, q_wall, t): d_qin_dt = (q_wall - q_in) / (R1 * Cin) + (q_out - q_in) / (R2 * Cin) d_qwall_dt = (q_in - q_wall) / (R1 * Cwall) return d_qin_dt, d_qwall_dt # 模拟过程 t = np.arange(0, T, dt) num_steps = len(t) q_in = np.full((6, num_steps), q_in0) q_wall = np.copy(q_in) P_total = np.zeros(num_steps) # 计算室内温度和用电功率 for i in range(num_steps): dq_in_dt, dq_wall_dt = differential_equation(q_in[:, i], q_wall[:, i], t[i]) q_in[:, i+1] = q_in[:, i] + dq_in_dt * dt q_wall[:, i+1] = q_wall[:, i] + dq_wall_dt * dt P_h = PN * np.ones(6) # 所有住户设备开启 P_total[i] = np.sum(P_h) # 绘制总用电功率曲线 plt.plot(t / 3600, P_total) plt.xlabel('Time (hours)') plt.ylabel('Total Power (kW)') plt.title('Total Power Consumption') plt.grid(True) 转换为matlab代码

将Python代码转换为MATLAB代码可以按照以下方式进行：

% 参数设置
R1 = 1.2e-3;
R2 = 9.2e-3;
Cin = 1.1e6;
Cwall = 1.86e8;
PN = 8.0;
q_out = -15.0;
q_in0 = 20.0;
dt = 60; % 时间步长，单位为秒
T = 24 * 60 * 60; % 模拟时间总长，单位为秒

% 定义微分方程
differential_equation = @(q_in, q_wall, t) [(q_wall - q_in) / (R1 * Cin) + (q_out - q_in) / (R2 * Cin); (q_in - q_wall) / (R1 * Cwall)];

% 模拟过程
t = 0:dt:T;
num_steps = length(t);
q_in = repmat(q_in0, 6, num_steps);
q_wall = q_in;
P_total = zeros(1, num_steps);

% 计算室内温度和用电功率
for i = 1:num_steps
    [dq_in_dt, dq_wall_dt] = differential_equation(q_in(:, i), q_wall(:, i), t(i));
    q_in(:, i+1) = q_in(:, i) + dq_in_dt * dt;
    q_wall(:, i+1) = q_wall(:, i) + dq_wall_dt * dt;
    
    P_h = PN * ones(6, 1); % 所有住户设备开启
    P_total(i) = sum(P_h);
end

% 绘制总用电功率曲线
plot(t / 3600, P_total / 1000);
xlabel('Time (hours)');
ylabel('Total Power (kW)');
title('Total Power Consumption');
grid on;

注意，在MATLAB中，需要使用`repmat`函数来创建多行相同初始状态的矩阵，使用`ones`函数创建多行相同数值的矩阵。另外，MATLAB中的函数句柄可以使用`@`符号来定义。