OPTIMAL PLACEMENT OF PHOTOVOLTAIC AND WIND GENERATION UNITS FOR VOLTAGE STABILITY ENHANCEMENT IN POWER SYSTEMS USING THE MAYFLY OPTIMIZATION ALGORITHM

Abstract

This study presents a Mayfly Optimization Algorithm (MOA)-based approach for voltage stability enhancement and optimal integration of renewable energy resources in the IEEE 30-bus transmission system under steady state contingency conditions. The methodology combines Newton-Raphson load flow analysis, Bus Voltage Stability Index (BVSI), and MOA to identify the most vulnerable buses and determine suitable locations for photovoltaic (PV) and wind generator installation. Contingency scenario was created by increasing the reactive load demand across the network, resulting in significant voltage degradation and increased system losses. The MOA based BVSI was then applied to identify critical buses requiring corrective actions. Simulation results revealed that buses 5, 16, and 23 were the weakest buses with the highest fitness values and therefore selected for renewable energy integration. Under contingency conditions, active and reactive power losses increased from 324.31 MW and 228.85 MVAr to 453.06 MW and 329.85 MVAr, respectively. Application of MOA reduced these losses to 338.10 MW and 257.60 MVAr. Further integration of optimally sized PV and wind generators significantly improved voltage profiles and reduced active power losses to 256.40 MW and 283.77 MW, respectively. Comparative analysis showed that the proposed BVSI-MOA approach outperformed the Equilibrium Optimizer (EO) and Line Stability Index (LSI) methods in identifying critical buses and minimizing system losses. The results demonstrate the effectiveness of MOA-based renewable energy integration for improving voltage stability, reducing transmission losses, and enhancing overall power system performance.