Hybrid Emperor Penguin Salp Swarm Optimized Probabilistic Neural Network Controller for Maximum Power Tracking From HRES
| International Journal of Electrical and Electronics Engineering |
| © 2025 by SSRG - IJEEE Journal |
| Volume 12 Issue 7 |
| Year of Publication : 2025 |
| Authors : C. Jeeva, Ambarisha Mishra |
10.14445/23488379/IJEEE-V12I7P112
How to Cite?
C. Jeeva, Ambarisha Mishra, "Hybrid Emperor Penguin Salp Swarm Optimized Probabilistic Neural Network Controller for Maximum Power Tracking From HRES," SSRG International Journal of Electrical and Electronics Engineering, vol. 12, no. 7, pp. 1-5, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I7P112
Abstract:
Energy harvesting using solar and wind energy is a major requirement in many applications. Also, to expand the efficacy of power generated from renewable sources, Maximum Power Point Tracking (MPPT) is crucial. Traditional MPPT controllers suffer from high error rates, slow convergence, and increased computational complexity, limiting their effectiveness. Thus, to solve these issues, an optimized Probabilistic Neural Network (PNN) controller to control the duty cycle of the boost converter has been designed. To improve performance, the proposed controller is optimized using a novel Hybrid Emperor Penguin–Salp Swarm Optimization Algorithm (HESS-SSA), which efficiently fine-tunes the neural network parameters. The proposed controller can optimize the duty cycle of the boost converter to maximize power extraction. Power extraction and duty cycle selection by HESS-SSA is compared with existing cuckoo search, Group Teaching Optimization Algorithm (GTOA), Dragonfly Optimization Algorithm (DOA), Particle Swarm Optimization (PSO) and PSO-Gravitational Search Algorithm (PSO-GSA). Proposed controller outperforms traditional optimization methods, as shown by simulation results, achieving a greater power output of 4538.89W with enhanced convergence speed and decreased error. The improved MPPT approach guarantees increased system efficiency and stability, which makes it a viable option for integrating renewable energy into independent power systems and smart grids.
Keywords:
Hybrid renewable energy sources, Boost converter, Duty cycle, Emperor Penguin Optimization (EPO), Salp Swarm Optimization.
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