Optimal Sustainable Energy Management for Isolated Microgrid: A Hybrid Jellyfish Search-Golden Jackal Optimization Approach

Dilip Kumar; Yogesh Chauhan; Ajay Pandey; Ankit Srivastava; Raghavendra Vijayaraghavan; Elavarasan Rajvikram Madurai; G Shafiullah

doi:10.3390/su17114801

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Optimal Sustainable Energy Management for Isolated Microgrid: A Hybrid Jellyfish Search-Golden Jackal Optimization Approach

Journal article

Open access

Peer reviewed

Optimal Sustainable Energy Management for Isolated Microgrid: A Hybrid Jellyfish Search-Golden Jackal Optimization Approach

Dilip Kumar, Yogesh Chauhan, Ajay Pandey, Ankit Srivastava, Raghavendra Vijayaraghavan, Elavarasan Rajvikram Madurai and G Shafiullah

Sustainability, Vol.17(11), 4801

2025

DOI: https://doi.org/10.3390/su17114801

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Abstract

Algorithms

Alternative energy

Back up systems

Efficiency

Energy management

Energy storage

Mathematical models

Optimization techniques

Renewable resources

Turbines

This study presents an advanced hybrid energy management system (EMS) designed for isolated microgrids, aiming to optimize the integration of renewable energy sources with backup systems to enhance energy efficiency and ensure a stable power supply. The proposed EMS incorporates solar photovoltaic (PV) and wind turbine (WT) generation systems, coupled with a battery energy storage system (BESS) for energy storage and management and a microturbine (MT) as a backup solution during low generation or peak demand periods. Maximum power point tracking (MPPT) is implemented for the PV and WT systems, with additional control mechanisms such as pitch angle, tip speed ratio (TSR) for wind power, and a proportional-integral (PI) controller for battery and microturbine management. To optimize EMS operations, a novel hybrid optimization algorithm, the JSO-GJO (Jellyfish Search and Golden Jackal hybrid Optimization), is applied and benchmarked against Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO), Artificial Bee Colony (ABC), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA). Comparative analysis indicates that the JSO-GJO algorithm achieves the highest energy efficiency of 99.20%, minimizes power losses to 0.116 kW, maximizes annual energy production at 421,847.82 kWh, and reduces total annual costs to USD 50,617,477.51. These findings demonstrate the superiority of the JSO-GJO algorithm, establishing it as a highly effective solution for optimizing hybrid isolated EMS in renewable energy applications.

Details

Title: Optimal Sustainable Energy Management for Isolated Microgrid: A Hybrid Jellyfish Search-Golden Jackal Optimization Approach
Authors/Creators: Dilip Kumar - Dr. Ram Manohar Lohia Avadh University
Yogesh Chauhan - Indira Gandhi Institute of Technology
Ajay Pandey - Indira Gandhi Institute of Technology
Ankit Srivastava - Dr. Ram Manohar Lohia Avadh University
Raghavendra Vijayaraghavan
Elavarasan Rajvikram Madurai
G Shafiullah - Murdoch University, Centre for Water, Energy and Waste
Publication Details: Sustainability, Vol.17(11), 4801
Publisher: MDPI AG; BASEL
Number of pages: 40
Identifiers: 991005788083007891
Murdoch Affiliation: School of Engineering and Energy; Centre for Water, Energy and Waste
Language: English
Resource Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.18 Power Systems & Electric Vehicles; 4.18.575 Photovoltaic Systems
Web Of Science research areas: Environmental Sciences; Environmental Studies; Green & Sustainable Science & Technology
ESI research areas: Environment/Ecology