Sparse matrix based power flow solver for real-time simulation of power system

Analyzing a massive number of Power Flow (PF) equations even on almost identical or similar network topology is a highly time-consuming process for large-scale power systems. The major computation time is hoarded by the iterative linear solving process to solve nonlinear equations until convergence is achieved. This is a paramount concern for any PF analysis methods. This thesis presents a sparse matrix-based power flow solver that is fast enough to be implemented in the real-time analysis of largescale power systems. It uses KLU, a sparse matrix solver, for PF analysis. It also implements parallel processing of CPU and GPU which enables the simultaneous computation of multiple blocks in the algorithm leading to faster execution. It runs 1000 times and 200 times faster than newton raphson method for DC and AC power system respectively. On average, it is around 10 times faster than MATPOWER for both AC and DC power system.