ArticleScientific reports2024
Advanced efficient energy management strategy based on state machine control for multi-sources PV-PEMFC-batteries system.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 38 citations in OpenAlex.
- Adaptive Control-based frequency control strategy for PV/ DEG/ battery power system during islanding conditions.Scientific reports · 2025Article
- CNN-LSTM optimized with SWATS for accurate state-of-charge estimation in lithium-ion batteries considering internal resistance.Scientific reports · 2025Article
- A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems.Scientific reports · 2024Article
- Enhancing renewable energy utilization and energy management strategies for new energy yachts.Heliyon · 2024Article
- An ultra-high gain boost converter with low switching stress for integrated multi-energy storage systems.Scientific reports · 2024Article
- Enhancing residential energy access with optimized stand-alone hybrid solar-diesel-battery systems in Buea, Cameroon.Scientific reports · 2024Article
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Authors and funding
5 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article offers a PV-PEMFC-batteries energy management strategy (EMS) that aims to meet the following goals: keep the DC link steady at the standard value, increase battery lifespan, and meet power demand. The suggested multi-source renewable system (MSRS) is made to meet load demand while using extra power to fill batteries. The major energy source for the MSRS is photovoltaic, and fuzzy logic MPPT is used to guarantee that the PV operates at optimal efficiency under a variety of irradiation conditions. The suggested state machine control consists of 15 steps. It prioritizes the proton exchange membrane fuel cell (PEMFC) as a secondary source for charging the battery when power is abundant and the state of charge (SOC) is low. The MSRS is made feasible by meticulously coordinating control and power management. The MSRS is made achievable by carefully orchestrated control and electricity management. The efficacy of the proposed system was evaluated under different solar irradiance and load conditions. The study demonstrates that implementing the SMC led to an average improvement of 2.3% in the overall efficiency of the system when compared to conventional control techniques. The maximum efficiency was observed when the system was operating under high load conditions, specifically when the state of charge (SOC) was greater than the maximum state of charge (SOCmax). The average efficiency achieved under these conditions was 97.2%. In addition, the MSRS successfully maintained power supply to the load for long durations, achieving an average sustained power of 96.5% over a period of 7.5 s. The validity of the modeling and management techniques mentioned in this study are confirmed by simulation results utilizing the MATLAB/Simulink (version: 2016, link: https://in.mathworks.com/products/simulink.html ) software tools. These findings show that the proposed SMC is effective at managing energy resources in MSRS, resulting in improved system efficiency and reliability.
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