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Renewable Poly-Generation Systems: Revolutionizing Energy Production and Resource Utilization

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 1900

Special Issue Editors


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Guest Editor
Energy Systems and Infrastructure Analysis Division, Argonne National Laboratory, Lemont, IL 60439, USA
Interests: techno-economic analysis; green hydrogen; energy storage systems; solar energy; wind energy

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Guest Editor
Mechanical Power Engineering Department, Faculty of Engineering, Cairo University, Giza 12613, Egypt
Interests: renewable energy; heat transfer; thermodynamics; data analytics; optimization

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Guest Editor
Department of Mechanical and Maintenance Engineering, School of Applied Technical Sciences, German Jordanian University, Amman 11180, Jordan
Interests: prognostics and health management; predictive maintenance; RAMS; artificial intelligence; machine learning; data mining; optimization; mathematical modelling; renewable energy; wind and solar photovoltaic systems; energy forecasting; performance analysis; mechanical engineering
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Mechanical Engineering, School of Engineering, University of Jordan, Amman 11942, Jordan
Interests: combustion and fuels; renewable energy; desalination; waste management systems; optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Maximizing the utilization of renewable energy resources is vital for achieving decarbonization, ensuring energy security, addressing climate change, and meeting growing energy demands in residential, commercial, and industrial sectors. Polygeneration and decentralized energy production stand as pivotal strategies to enhance efficiency, productivity, compactness, and cost-effectiveness across various renewable energy systems. Polygeneration involves generating multiple useful energy forms, encompassing electricity, hot water, distilled water, heating/cooling, and even outputs like hydrogen or pressurized air. These systems can be partially or fully powered by renewable sources such as solar, geothermal, biomass, and wind systems. While the concept is compelling, it introduces complexity, necessitating meticulous design, optimization, control, and management to ensure sustainable development. Further research is essential to advance the potential of polygeneration in renewable energy systems. This Special Issue aims to provide a platform for discussing the advancements and innovations of these systems, regardless of the source or output mix. We welcome contributions showcasing newly conceptualized systems, novel models, optimization approaches, techno-economic analysis, control strategies, and life cycle analyses.

Dr. Loiy Al-Ghussain
Dr. Muhammed A. Hassan
Dr. Sameer Al-Dahidi
Dr. Mohammad Alrbai
Guest Editors

Manuscript Submission Information

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Keywords

  • renewable energy
  • poly-generation
  • multi-generation
  • hybrid system
  • energy storage
  • life cycle assessment
  • green hydrogen

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Published Papers (1 paper)

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Research

22 pages, 8000 KiB  
Article
Energy Management Strategy of Fuel Cell Commercial Vehicles Based on Adaptive Rules
by Shiyou Tao, Zhaohui Peng and Weiguang Zheng
Sustainability 2024, 16(17), 7356; https://doi.org/10.3390/su16177356 - 27 Aug 2024
Cited by 2 | Viewed by 1381
Abstract
Fuel cell vehicles have been widely used in the commercial vehicle field due to their advantages of high efficiency, non-pollution and long range. In order to further improve the fuel economy of fuel cell commercial vehicles under complex working conditions, this paper proposes [...] Read more.
Fuel cell vehicles have been widely used in the commercial vehicle field due to their advantages of high efficiency, non-pollution and long range. In order to further improve the fuel economy of fuel cell commercial vehicles under complex working conditions, this paper proposes an adaptive rule-based energy management strategy for fuel cell commercial vehicles. First, the nine typical working conditions of commercial vehicles are classified into three categories of low speed, medium speed and high speed by principal component analysis and the K-means algorithm. Then, the crawfish optimization algorithm is used to optimize the back propagation neural network recognizer to improve the recognition accuracy and optimize the rule-based energy management strategy under the three working conditions to obtain the optimal threshold. Finally, under WTVC and combined conditions, the optimized recognizer is used to identify the conditions in real time and call the optimal rule threshold, and the sliding average filter is used to filter the fuel cell output power in real time, which finally realizes the adaptive control. The simulation results show that compared with the conventional rule-based energy management strategy, the number of fuel cell start–stops is reduced. The equivalent hydrogen consumption is reduced by 7.04% and 4.76%, respectively. Full article
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