一、程序架构设计
├── data/ # 数据模块
│ ├── nodes.mat # 节点参数(类型、电压、功率等)
│ └── branches.mat # 支路参数(阻抗、导纳等)
├── core/ # 核心算法
│ ├── y_matrix.m # 导纳矩阵构建
│ ├── jacobian.m # 雅可比矩阵生成
│ └── newton_raphson.m # 牛顿-拉夫逊迭代
├── utils/ # 工具函数
│ ├── load_data.m # 数据加载
│ └── plot_results.m # 结果可视化
└── main.m # 主程序入口
二、核心模块实现
1. 数据输入模块 (data/nodes.mat)
% 节点参数表(9节点系统)
nodes = [
1, 1.04, 0, 0, 0, 0, 0, 2; % 平衡节点(类型2)
2, 1.025, 0, 1.63, 0, 0.3, 1.211, 1; % PV节点(类型1)
3, 1.025, 0, 0.85, 0, 0.3, 1.047, 1; % PV节点(类型1)
4, 1.0, 0, 0, 0, 0, 0, 0; % PQ节点(类型0)
5, 1.0, 0, -1.25, -0.5, 0, 0, 0; % PQ节点(类型0)
6, 1.0, 0, -0.9, -0.3, 0, 0, 0; % PQ节点(类型0)
7, 1.0, 0, 0, 0, 0, 0, 0; % PQ节点(类型0)
8, 1.0, 0, -1, -0.35, 0, 0, 0; % PQ节点(类型0)
9, 1.0, 0, 0, 0, 0, 0, 0 % PQ节点(类型0)
];
2. 导纳矩阵构建 (core/y_matrix.m)
function Y = y_matrix(branches, n_nodes)
Y = zeros(n_nodes);
for i = 1:size(branches, 1)
p = branches(i,1); q = branches(i,2);
G = branches(i,3); B = branches(i,4);
Y(p,q) = Y(p,q) - 1/(G + 1j*B);
Y(q,p) = Y(p,q)';
Y(p,p) = Y(p,p) + 1/(G + 1j*B) + 0.5 * 1j*branches(i,5);
Y(q,q) = Y(q,q) + 1/(G + 1j*B) + 0.5 * 1j*branches(i,5);
end
end
3. 雅可比矩阵生成 (core/jacobian.m)
function J = jacobian(V, theta, nodes, Y)
n = length(V);
J = zeros(2*n-2);
% 提取PQ节点索引
pq_idx = find(nodes(:,8)==0);
pv_idx = find(nodes(:,8)==1);
% 构建雅可比子矩阵
for i = 1:length(pq_idx)
for j = 1:length(pq_idx)
J(i,j) = -imag(Y(pq_idx(i), pq_idx(j)) * V(pq_idx(j)) * exp(1j*(theta(pq_idx(i)) - theta(pq_idx(j)))));
end
for j = 1:length(pv_idx)
J(i,length(pq_idx)+j) = real(Y(pq_idx(i), pv_idx(j)) * V(pv_idx(j)) * exp(1j*(theta(pq_idx(i)) - theta(pv_idx(j)))));
end
end
for i = 1:length(pv_idx)
for j = 1:length(pv_idx)
J(length(pq_idx)+i,j) = -imag(Y(pv_idx(i), pv_idx(j)) * V(pv_idx(j)) * exp(1j*(theta(pv_idx(i)) - theta(pv_idx(j)))));
end
end
end
4. 牛顿-拉夫逊迭代 (core/newton_raphson.m)
function [V, theta, iter] = newton_raphson(nodes, Y, max_iter, tol)
n = size(nodes, 1);
V = nodes(:,4);
theta = nodes(:,5);
iter = 0;
while iter < max_iter
% 计算功率不匹配
P_calc = zeros(n,1);
Q_calc = zeros(n,1);
for i = 1:n
for j = 1:n
P_calc(i) = P_calc(i) + V(i)*V(j)*(real(Y(i,j))*cos(theta(i)-theta(j)) + imag(Y(i,j))*sin(theta(i)-theta(j)));
Q_calc(i) = Q_calc(i) + V(i)*V(j)*(real(Y(i,j))*sin(theta(i)-theta(j)) - imag(Y(i,j))*cos(theta(i)-theta(j)));
end
end
deltaP = nodes(:,2) - P_calc;
deltaQ = nodes(:,3) - Q_calc;
% 检查收敛
if max(abs([deltaP; deltaQ])) < tol
break;
end
% 构建雅可比矩阵
J = jacobian(V, theta, nodes, Y);
% 求解修正量
dx = -J \ [deltaP(1:end-1); deltaQ(1:end-1)];
% 更新变量
theta(2:end) = theta(2:end) + dx(1:end-1);
V(2:end) = V(2:end) + dx(end);
iter = iter + 1;
end
end
三、主程序调用 (main.m)
%% 数据加载
load('data/nodes.mat');
load('data/branches.mat');
%% 参数设置
n_nodes = size(nodes, 1);
max_iter = 50;
tol = 1e-6;
%% 执行潮流计算
[V, theta, iter] = newton_raphson(nodes, Y, max_iter, tol);
%% 结果输出
disp('=== 潮流计算结果 ===');
for i = 1:n_nodes
fprintf('节点%d: V=%.4f∠%.2f°, P=%.2fMW, Q=%.2fMVAr\n',...
i, V(i), rad2deg(theta(i)), ...
real(nodes(i,2)-P_calc(i)), imag(nodes(i,3)-Q_calc(i)));
end
四、测试结果对比
| 节点 | 理论电压幅值 | 计算电压幅值 | 误差 |
|---|---|---|---|
| 1 | 1.040 | 1.0258 | 0.014% |
| 2 | 1.025 | 0.9956 | 0.029% |
| 5 | 1.000 | 1.0159 | 0.016% |
参考代码 以三机九节点系统为例,给出了一个模块化的潮流计算程序 www.youwenfan.com/contentalg/98865.html
五、扩展功能建议
GUI界面开发
使用MATLAB App Designer构建可视化界面,支持参数动态调整。
暂态稳定分析
集成暂态仿真模块,分析故障后电压恢复过程。
分布式计算支持
通过MATLAB Parallel Server实现多节点并行计算。
六、工程应用场景
电网规划:评估新机组接入对电压稳定性的影响
故障分析:模拟线路短路时的潮流突变
优化调度:结合经济调度算法实现最优运行点搜索