Power System Load Flow Calculation in MATLAB using PQ Decomposition Method

Resource Overview

Implementation of PQ decomposition method for load flow analysis with three test cases included. Users can perform additional calculations by modifying the input data files. The implementation demonstrates how to structure power system data and apply iterative solving techniques.

Detailed Documentation

This article presents a comprehensive implementation of the PQ decomposition method for power system load flow calculations, accompanied by three practical test cases to help readers better understand the application of this methodology. Before performing calculations for additional test cases, users need to modify the input data files to specify system parameters, bus data, and line information. The PQ decomposition method offers improved computational efficiency for certain types of power system problems by decoupling the active and reactive power equations. This approach separates the problem into smaller subproblems: the P-θ subproblem (active power and voltage angle) and the Q-V subproblem (reactive power and voltage magnitude). For each subproblem, the implementation uses iterative solving techniques with appropriate convergence criteria. Key implementation aspects include: - Structured input file format containing bus data (type, voltage, power injections) - Branch data matrix with line parameters and transformer specifications - Jacobian matrix construction for the decoupled equations - Iterative solution algorithm with convergence checking - Output formatting for bus voltages, power flows, and losses The MATLAB implementation demonstrates how to initialize system parameters, build the admittance matrix, and solve the power flow equations using successive iterations. The code structure allows for easy modification of system configurations and analysis of different operating conditions. Through this PQ decomposition approach, users can gain deeper insights into power system behavior and develop more effective solutions for load flow analysis.