A Hybrid Zebra Optimization Sine Cosine Algorithm for Economic Operation of Power Systems Based on Optimal Power Generation to Control Congestion in Transmission Lines

Effective Congestion Management (CM) plays a vital role in ensuring reliable system operation and control. The primary objective of CM is to relieve transmission line overloads while satisfying all operational constraints at the minimum possible cost. This study introduces a hybrid Zebra Optimization Algorithm–Sine Cosine Algorithm (ZOA–SCA) for an efficient generation rescheduling strategy aimed at minimizing congestion-related expenses. The hybrid framework integrates key mechanisms of the SCA into the ZOA process to strengthen both its exploration and exploitation capabilities, thereby enabling robust global search performance and effective optimization of rescheduled generation levels. The effectiveness of the ZOA-SCA was tested on the 23 benchmark functions. The proposed approach was validated on IEEE 30-bus and IEEE 118-bus benchmark systems under congested system conditions. Its effectiveness was assessed through comparative analysis with several state-of-the-art optimization techniques. Simulation results indicate that the ZOA-SCA consistently achieves superior performance by avoiding premature convergence and exhibiting favorable convergence behavior.