Enhancing Power Production: A Novel Hydrogen‐Based Scheme With Comprehensive Analysis and <scp>AI</scp>‐Optimized Criteria

ABSTRACT Despite being a cutting‐edge technology, the proton exchange membrane fuel cell (PEMFC) generates a lot of heat as it works, which makes it wasteful with energy. In order to enhance energy efficiency via waste heat recovery, we provide and analyze a novel integrated energy system that utilizes PEMFC and ORC technology. There are a lot of ways to put the waste heat from fuel cells (FCs) to good use, but the most efficient one is the organic Rankine cycle (ORC) with the right working fluid. This research aims to find the optimal way to use the waste heat of the FC by testing several working fluids. The optimal solution is derived using a genetic algorithm by monitoring the objective functions that characterize the system's overall performance as they vary across different system parameters. The results show that the proposed efficient integration achieves high energy and exergy efficiency levels and achieves rates of total cost and environmental impact that are within acceptable limits. Since the fuel usage element's content significantly affects the system indicators in several ways, the results also demonstrate that it is quite relevant. Since the exergo‐environmental metric and the exergy efficiency meter are always moving in different directions, choosing a design condition that meets several requirements is crucial. According to the results, fuel cells had the highest irreversibility rate at 12.2, making them the most energy‐conserving piece of machinery.

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Publication Details

Journal
Energy Storage
Published
2024-08-01
DOI
https://doi.org/10.1002/est2.70013
Citations
4
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
0.68
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article

Enhancing Power Production: A Novel Hydrogen‐Based Scheme With Comprehensive Analysis and AI‐Optimized Criteria

Ehsan Gholamian, Vahid Mohammadzadeh, Zoheir Saboohi, Fathollah Ommi
4 citations
Energy Storage
Hybrid Renewable Energy Systems
0.68
article

Enhancing Power Production: A Novel Hydrogen‐Based Scheme With Comprehensive Analysis and AI‐Optimized Criteria

Ehsan Gholamian, Vahid Mohammadzadeh, Zoheir Saboohi, Fathollah Ommi
article en
4 citations

Abstract

ABSTRACT Despite being a cutting‐edge technology, the proton exchange membrane fuel cell (PEMFC) generates a lot of heat as it works, which makes it wasteful with energy. In order to enhance energy efficiency via waste heat recovery, we provide and analyze a novel integrated energy system that utilizes PEMFC and ORC technology. There are a lot of ways to put the waste heat from fuel cells (FCs) to good use, but the most efficient one is the organic Rankine cycle (ORC) with the right working fluid. This research aims to find the optimal way to use the waste heat of the FC by testing several working fluids. The optimal solution is derived using a genetic algorithm by monitoring the objective functions that characterize the system's overall performance as they vary across different system parameters. The results show that the proposed efficient integration achieves high energy and exergy efficiency levels and achieves rates of total cost and environmental impact that are within acceptable limits. Since the fuel usage element's content significantly affects the system indicators in several ways, the results also demonstrate that it is quite relevant. Since the exergo‐environmental metric and the exergy efficiency meter are always moving in different directions, choosing a design condition that meets several requirements is crucial. According to the results, fuel cells had the highest irreversibility rate at 12.2, making them the most energy‐conserving piece of machinery.

Energy StorageVol. 6(5)
Tarbiat Modares University (IR), University of Tabriz (IR), Ministry of Science, Research and Technology (IR)
Affordable and clean energy
Openalex Percentile: Top 27%
Hybrid Renewable Energy Systems
0.68
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Enhancing Power Production: A Novel Hydrogen‐Based Scheme With Comprehensive Analysis and <scp>AI</scp>‐Optimized Criteria — Ehsan Gholamian, Vahid Mohammadzadeh, et al. · Energy Storage (2024) | TGRS Research Map | TGRS