Adaptive Load Sharing Strategy for Multi-Source Renewable Energy Systems

This research optimizes solar, fuel cell, and battery systems for near-fault current, efficiency, and low-transient charging and discharging to extend battery life. Replicating these energy sources on the grid requires MATLAB Simulink assessment and coordination. Goals include assessing PV, Fuel cell, and battery dependability, maintaining load demand, and controlling power generation to reduce battery stress. Battery power management can improve fuel cell longevity and efficiency, and optimizing peak loads can reduce big spikes. Connecting the PV, fuel cell, and battery systems in MATLAB Simulink will simulate load demand and share electricity proportionally. To balance power output, load fulfilment ratios will be based on source capacity and efficiency. This is 2kW from the photovoltaic system, 6kW from the fuel cell system, and 10 kWh from the battery storage system to supply 100 kW. It charges in 1.5–2 seconds and starts working in 0.5–1.5 seconds with PV and fuel cells. In an ideal world, the energy management system would use PV and fuel cells and the batteries first. By synchronizing PVs, fuel cells, and batteries, efficiency and battery life will improve. Thus, optimization and monitoring will focus on battery burden control, transient charging and discharging control, and system efficiency to extend battery life. Battery will also determine fuel cell power responses. This project uses MATLAB Simulink to analyses power source capacities, synchronize power production, and share load to create a dependable and accurate hybrid power system.

Authors

Publication Details

Journal
Modern Applied Science
Published
2025-10-14
DOI
https://doi.org/10.5539/mas.v19n2p48
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Load Sharing Strategy for Multi-Source Renewable Energy Systems

Chin Kim Gan, Hairol Nizam Mohd Shah, Mohd Shahrieel Mohd Aras, Zairi Ismael Rizman et al.
Modern Applied Science
Smart Grid Energy Management
article

Adaptive Load Sharing Strategy for Multi-Source Renewable Energy Systems

Chin Kim Gan, Hairol Nizam Mohd Shah, Mohd Shahrieel Mohd Aras, Zairi Ismael Rizman, Alias Khamis, N. Nasir
article en

Abstract

This research optimizes solar, fuel cell, and battery systems for near-fault current, efficiency, and low-transient charging and discharging to extend battery life. Replicating these energy sources on the grid requires MATLAB Simulink assessment and coordination. Goals include assessing PV, Fuel cell, and battery dependability, maintaining load demand, and controlling power generation to reduce battery stress. Battery power management can improve fuel cell longevity and efficiency, and optimizing peak loads can reduce big spikes. Connecting the PV, fuel cell, and battery systems in MATLAB Simulink will simulate load demand and share electricity proportionally. To balance power output, load fulfilment ratios will be based on source capacity and efficiency. This is 2kW from the photovoltaic system, 6kW from the fuel cell system, and 10 kWh from the battery storage system to supply 100 kW. It charges in 1.5–2 seconds and starts working in 0.5–1.5 seconds with PV and fuel cells. In an ideal world, the energy management system would use PV and fuel cells and the batteries first. By synchronizing PVs, fuel cells, and batteries, efficiency and battery life will improve. Thus, optimization and monitoring will focus on battery burden control, transient charging and discharging control, and system efficiency to extend battery life. Battery will also determine fuel cell power responses. This project uses MATLAB Simulink to analyses power source capacities, synchronize power production, and share load to create a dependable and accurate hybrid power system.

Modern Applied ScienceVol. 19(2)
Openalex Percentile: Top 71%
Smart Grid Energy Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Adaptive Load Sharing Strategy for Multi-Source Renewable Energy Systems — Chin Kim Gan, Hairol Nizam Mohd Shah, et al. · Modern Applied Science (2025) | TGRS Research Map | TGRS