Enhancing the Hybrid Microgrid Performance with Jellyfish Optimization for Efficient MPPT and THD Estimation by the Unscented Kalman Filter

Power management in advanced grid systems requires the seamless integration of diverse renewable energy sources. This study investigates the optimization of a grid-connected system comprising a photovoltaic (PV) solar panel, energy storage system, fuel cell (FC), and diesel generator (DG) using the bioinspired metaheuristic technique called jellyfish optimization (JF). The objective is to maximize power generation from the PV system under normal and partial shading conditions. The performance of JF is compared against particle swarm optimization (PSO) using various parameters. As India heavily relies on solar PV, the results highlight JF’s exceptional effectiveness in extracting maximum power during partial shading scenarios. Inspired by the active and passive motions of jellyfish in the ocean, the JF algorithm is utilized. To further optimize the power output, the system is integrated with an efficient battery management system, PEM fuel cell stacking, and diesel generators. The system’s performance is analyzed using fast Fourier transform (FFT) to evaluate harmonic distortions, which consistently meet the limits specified in IEEE STD 1547-2018. Furthermore, unscented Kalman filter-based analysis is employed to assess total harmonic distortion (THD) and power rating for the grid system across various renewable energy scenarios. The contribution of the jellyfish optimization (JF) algorithm lies in its ability to efficiently and effectively maximize power generation from the PV system, regardless of normal or partial shading conditions. JF, a bioinspired metaheuristic optimization technique, successfully emulates the collective behavior of jellyfish in the ocean to identify optimal solutions. In this study, JF outperforms particle swarm optimization (PSO) in terms of power generation under partial shading conditions. Notably, JF exhibits remarkable capability in exploring the search space and discovering the global optimum, even when the system operates under challenging conditions. Overall, this study demonstrates the tremendous potential of JF in maximizing power generation in grid-connected systems with renewable energy sources while also highlighting the benefits of integrating additional components to further enhance the system performance

Comprehensive overview of optimizing PV-DG allocation in power system and solar energy resource potential assessments

Distributed Generation based on Photovoltaic (PV-DG) injected in the power system is considered a highly promising solution due to the advantage of clean energy use. However, the investigation of the optimal PV-DG allocation (site and size) is a significant task for power system requirements and assessment of PV potentials. Recent research works on PV-DG allocation are reviewed from two viewpoints; (1) DG, optimization algorithms and objectives and (2) methodologies of PV potential assessments. Due to the review of recent research works, the research gaps are identified and new methodology will be proposed. The authors strongly believe that this work can be helpful to mitigate power system challenges. Besides, it helps to maximize the PV harness within the power system in particular developing countries. © 2019 The AuthorsArizona Research Institute for Solar Energy, AzRISEAt the beginning, the author is grateful from YTB (Yurtd??? T?rkler ve Akraba Topluluklar Ba?kanl???) to provide the chance for conducting this study in Turkey. He would also like to thank each of Solar Energy Institute (G?ne? Enerjisi Enstit?s?) in Ege University for providing all necessary needs to complete this work, my supervisor for his tangible guiding and motivating during this academic research and my parents for spiritual support