MATLAB Implementation of Forward-Backward Sweep Algorithm for Power Flow Analysis

The forward-backward sweep algorithm is a classic and efficient method for power flow calculation in distribution networks, particularly suitable for radial network structures. This algorithm iteratively computes node voltages and power distributions, characterized by fast computation speed and good convergence properties.

In MATLAB implementation, the core approach involves two key stages: forward sweep and backward sweep. During the forward sweep stage, the algorithm starts from the root node and progresses along feeders to calculate power flows through branches, incorporating line impedance and node load effects using matrix operations and impedance calculations. The backward sweep phase begins from terminal nodes, utilizing known power distributions to recursively compute node voltages in reverse direction while updating voltage magnitudes and phase angles through iterative voltage updates.

The complete algorithm implementation typically requires setting convergence criteria, such as maintaining voltage deviations between consecutive iterations below a specified threshold. For the specific structure of distribution networks, MATLAB can employ sparse matrix techniques and optimized indexing to enhance computational efficiency through functions like sparse() and backslash operators. Regarding convergence, the forward-backward sweep method demonstrates stable convergence in most distribution network scenarios, with iteration counts showing linear relationship to network size.

During implementation, special attention must be given to handling models of special equipment like distributed generators and voltage regulators, which can be implemented through custom function modules that affect algorithm convergence speed and final results. For weakly meshed networks or heavy-load conditions, improvement measures such as introducing relaxation factors may be necessary through convergence control parameters to ensure stable convergence.