Optimal Harmonic Estimation in Renewable Integrated Power System Using Grasshopper Optimisation Algorithm and Recursive Least Square Approach

Harmonic estimation in renewable integrated power systems is crucial for maintaining power quality and ensuring the reliability of the grid. This paper presents an innovative approach for optimal harmonic estimation by combining the Grasshopper Optimization Algorithm (GOA) with the Recursive Least Square (RLS) method. RLS is used for estimation of amplitude of harmonics, whereas phase is estimated by GOA. The performance of GOA-RLS is investigated in detail for estimation of power system signals using test signals buried with noise. The integration of GOA, a nature-inspired optimization technique, with RLS, a statistical method, provides a robust framework for accurately identifying harmonics in power systems. The proposed method is tested on a simulated renewable integrated power system, demonstrating superior performance in terms of accuracy, convergence speed. The results highlight the potential of this hybrid approach in enhancing the operational efficiency and stability of modern power grids with high penetration of renewable energy sources.