load flow by backward-forward sweep algorithm to make NR
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Hello every one..
please, i need matlab code to make network reconfiguration using BPSO as optimization method for ieee 33 bus system but i need load flow by BFS algorthim for this code.
I know NR by BPSO found but using mat power to make load flow.
thanks alot.
2 个评论
Omar Shaaban
2024-9-1
Hi did you happen to find the network reconfiguration code? can you please share to: omar.abdalmoneem@gmail.com
ARBAZ
2025-5-9
I also need same code, emy if you managed this please connect with me arbazahmadganie@gmail.com
采纳的回答
Zinea
2024-9-2
Here is the outline of the MATLAB code for NR using BPSO with a simplified BFS-based load flow analysis for the IEEE 33-bus system. The following points are to be considered:
- The voltage magnitudes are initialized to 1 p.u. (per unit) for simplicity.
- The adjacency matrix represents the connectivity of the network, where a ‘1’ indicates a connection between buses (i.e., a closed branch).
- The voltage drop across each branch is calculated using a simplified linear approximation. This is a basic method and should be replaced with a more precise calculation, such as using the power flow equations.
% Initialization
numBuses = 33; % Number of buses
numBranches = 37; % Number of branches
maxIter = 100; % Maximum number of iterations for BPSO
numParticles = 30; % Number of particles in the swarm
% Hypothetical bus data: [busNumber, type, Pd, Qd]
busData = [
1, 1, 0, 0; % Slack bus
2, 2, 0.1, 0.06;
3, 2, 0.09, 0.04;
% Add remaining buses...
];
% Hypothetical branch data: [fromBus, toBus, resistance, reactance]
branchData = [
1, 2, 0.0922, 0.0470;
2, 3, 0.4930, 0.2511;
% Add remaining branches...
];
% Initialize particles
particles = randi([0, 1], numParticles, numBranches);
velocities = zeros(numParticles, numBranches);
pBest = particles;
gBest = particles(1, :);
pBestCost = inf(numParticles, 1);
gBestCost = inf;
% BPSO parameters
w = 0.5; % Inertia weight
c1 = 1.5; % Cognitive coefficient
c2 = 1.5; % Social coefficient
% Optimization Loop
for iter = 1:maxIter
for i = 1:numParticles
% Perform BFS Load Flow Analysis
[V, loss] = bfsLoadFlow(particles(i, :), busData, branchData);
% Evaluate cost function (e.g., power loss)
cost = sum(loss);
% Update personal best
if cost < pBestCost(i)
pBest(i, :) = particles(i, :);
pBestCost(i) = cost;
end
% Update global best
if cost < gBestCost
gBest = particles(i, :);
gBestCost = cost;
end
end
% Update particle velocities and positions
for i = 1:numParticles
velocities(i, :) = w * velocities(i, :) ...
+ c1 * rand * (pBest(i, :) - particles(i, :)) ...
+ c2 * rand * (gBest - particles(i, :));
% Update particles using sigmoid function for binary conversion
sigmoid = 1 ./ (1 + exp(-velocities(i, :)));
particles(i, :) = rand(size(sigmoid)) < sigmoid;
end
% Display iteration information
fprintf('Iteration %d: Best Cost = %.4f\n', iter, gBestCost);
end
% Final Results
fprintf('Optimal Configuration: %s\n', num2str(gBest));
fprintf('Minimum Loss: %.4f\n', gBestCost);
function [V, loss] = bfsLoadFlow(particle, busData, branchData)
% Initialize variables
numBuses = size(busData, 1);
V = ones(numBuses, 1); % Initialize voltage magnitudes to 1 p.u.
loss = zeros(size(branchData, 1), 1); % Power loss for each branch
% Create adjacency matrix for BFS
adjacencyMatrix = zeros(numBuses, numBuses);
for i = 1:size(branchData, 1)
if particle(i) == 1 % If branch is closed
fromBus = branchData(i, 1);
toBus = branchData(i, 2);
adjacencyMatrix(fromBus, toBus) = 1;
adjacencyMatrix(toBus, fromBus) = 1;
end
end
% BFS algorithm
visited = false(numBuses, 1);
queue = [1]; % Start from the slack bus (assumed to be bus 1)
visited(1) = true;
while ~isempty(queue)
currentBus = queue(1);
queue(1) = [];
neighbors = find(adjacencyMatrix(currentBus, :));
for neighbor = neighbors
if ~visited(neighbor)
% Find branch index
branchIndex = find((branchData(:, 1) == currentBus & branchData(:, 2) == neighbor) | ...
(branchData(:, 1) == neighbor & branchData(:, 2) == currentBus));
% Calculate voltage drop and losses
resistance = branchData(branchIndex, 3);
reactance = branchData(branchIndex, 4);
powerDemand = busData(neighbor, 3) + 1i * busData(neighbor, 4);
% Simplified voltage drop calculation (linear approximation)
voltageDrop = (resistance + 1i * reactance) * powerDemand / V(currentBus);
V(neighbor) = V(currentBus) - abs(voltageDrop);
% Calculate power loss in the branch
currentFlow = powerDemand / V(currentBus);
loss(branchIndex) = resistance * abs(currentFlow)^2;
% Mark as visited and add to queue
visited(neighbor) = true;
queue(end + 1) = neighbor;
end
end
end
end
Hope this helps you get started!
2 个评论
ARBAZ
2025-5-9
I also need same code,please send full code Or connect with me arbazahmadganie@gmail.com
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