Optimal Power Flow Analysis of Uyo Zone 002 IBB Distribution Feeder Line System Network Using Conventional Analytical Techniques

Abstract

The Optimal Power Flow (OPF) analysis is crucial for ensuring the efficient operation of power systems by optimising the generation and transmission of power while satisfying various operational constraints. This paper compares three different analytical methods, Gauss-Seidel, Newton-Raphson, and Fast Decoupled, to simulate and compute the OPT in Uyo Zone 002 IBB distribution feeder lines system network using the ETAP software. The study aimed to determine the most suitable method for achieving optimal regional power flow. Using the Gauss Siedel method, the load flow was analysed for a 44-bus system wh in bus 1, 2, and 4's transmission lines operate on 132,000 kVA lines. The power generated in bus two was observed at 0.014MW while Mvar was -0.076. The load flow in the buses varied between -0.007 and 0.014 MW, while the Mvar was between -0.03 and 0.076. The voltage magnitudes (% Mag) ranged between 100.000 and 100.497. Using the Newton-Raphsons method, the load flow was analysed for a 44-bus system where all the transmission lines on all the buses operate at 11 kVA. The voltage magnitude on buses 10 and 12 were 98.744% and 76.014%, respectively, while other buses worked at 100.497. Using the Fast Decoupled method, the 11kV transmission line accommodated all the buses and their voltages and power generation. The loads flowing through all the buses in the system had the same parametric values except for Umoh Obot Street s/s Bus 16, whose voltage magnitude dropped to 76.014% with Ang of -45.2%. Only the % Mag for UMOH OBOT S/S Bus 16 was 76.014%, and the rest were 100.497. The study results indicate that the three methods were quite effective in terms of convergence speed and accuracy. However, the Newton-Raphson method was able to quickly converge to a solution that satisfies all operational constraints while minimising generation costs. In contrast, the Gauss-Seidel method exhibited slower convergence and may require more iterations to reach a feasible solution. The fast decoupled method, although computationally efficient, may sacrifice accuracy for speed in certain scenarios.