article · Sensors
Proton exchange membrane fuel cells respond slowly to sudden shifts in electrical load during periods of energy deficit. To overcome this limitation, hybrid renewable power systems incorporate solar photovoltaic panels alongside fast-acting energy storage devices such as lithium-ion batteries and supercapacitors. Operating these components effectively requires an energy management strategy that balances load demand, protects device operating boundaries, and minimises expensive fuel usage. An advanced energy management strategy utilising the white shark optimizer algorithm has been developed for such multi-source microgrids. The system allocates power demand across all generation and storage units while targeting hydrogen conservation. Comparative evaluations reveal that this method lowers hydrogen utilization by up to 34.17 per cent and enhances overall system efficiency by up to 9.5 per cent compared to existing state machine and energy maximization control strategies.
Hybrid microgrids combining solar panels, fuel cells, and energy storage provide resilient clean electricity, but operating fuel cells can require significant amounts of expensive hydrogen. Implementing smarter power-dispatch algorithms reduces fuel consumption while ensuring that batteries, fuel cells, and supercapacitors run within safe operating limits, making clean microgrids cheaper and more dependable to run.
The method is relevant to microgrid developers and energy management system software providers working with multi-source renewable installations. By lowering hydrogen fuel consumption and raising efficiency, it can decrease operational expenditures for hybrid clean-power sites. As presented in the abstract, the technology is at the stage of applied algorithm development tested against established control methods, with real-world microgrid deployment still requiring field validation.
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The slow dynamic response of a proton exchange membrane fuel cell (PEMFC) to high load change during deficit periods must be considered. Therefore, integrating the hybrid system with energy storage devices like battery storage and/or a supercapacitor is necessary. To reduce the consumed hydrogen, an energy management strategy (EMS) based on the white shark optimizer (WSO) for photovoltaic/PEMFC/lithium-ion batteries/supercapacitors microgrid has been developed. The EMSs distribute the load demand among the photovoltaic, PEMFC, lithium-ion batteries, and supercapacitors. The design of EMSs must be such that it minimizes the use of hydrogen while simultaneously ensuring that each energy source performs inside its own parameters. The recommended EMS-based-WSO was evaluated in regard to other EMSs regarding hydrogen fuel consumption and effectiveness. The considered EMSs are state machine control strategy (SMCS), classical external energy maximization strategy (EEMS), and optimized EEMS-based particle swarm optimization (PSO). Thanks to the proposed EEMS-based WSO, hydrogen utilization has been reduced by 34.17%, 29.47%, and 2.1%, respectively, compared with SMCS, EEMS, and PSO. In addition, the efficiency increased by 6.05%, 9.5%, and 0.33%, respectively, compared with SMCS, EEMS, and PSO.
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DOI: 10.3390/s23031534
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