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Energies
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Modelling, Control and Optimisation of Complex Energy Systems
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Modelling, Control and Optimisation of Complex Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (20 December 2021) | Viewed by 8077

Special Issue Editor

Dr. Hamid Khayyam

E-Mail Website
Guest Editor
Department of Mechanical and Automotive Engineering, School of Engineering, RMIT University, Melbourne, VIC 3083, Australia
Interests: artificial intelligence; machine learning and adaptive intelligent systems; limited and big data modelling; Industry 4.0 and Education 4.0
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy systems are often complex, ambiguous, and nonlinear. These complex energy systems need computation and their processing has led to the use of modelling, control and optimisation techniques. As such, the energy management, energy efficiency, energy services, renewable energy and alternative energy technology management of complex systems are of great importance and are topics of discussion for this Special Issue. The Special Issue aims to be a leading peer-reviewed platform and will survey the state-of-the-art of this field and mathematical modelling, such as deterministic and nondeterministic including machine learning, stochastic; modern control techniques (classical and intelligent) and optimization algorithms (classical and heuristic), which are deployed to achieve complex energy systems. The Special Issue covers research on energy analysis, energy modelling and prediction, integrated energy systems, energy planning, and energy management to improve energy efficiency. Papers are also welcome on other related topics, such as renewable energy, electricity supply and demand, bioenergy, robots, vehicle, energy storage, energy conservation, energy in buildings, industrial and residential within the context of the broader automation control and energy efficiency.

Dr. Hamid Khayyam
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Complex energy systems
  • Modelling, control, optimization
  • Renewable energy
  • Artificial intelligence
  • Machine learning
  • Power and energy systems

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Published Papers (2 papers)

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Research

16 pages, 9688 KiB  
Article
Neuro-Fuzzy System for Energy Management of Conventional Autonomous Vehicles
by Duong Phan, Alireza Bab-Hadiashar, Reza Hoseinnezhad, Reza N. Jazar, Abhijit Date, Ali Jamali, Dinh Ba Pham and Hamid Khayyam
Energies 2020, 13(7), 1745; https://doi.org/10.3390/en13071745 - 5 Apr 2020
Cited by 12 | Viewed by 2990
Abstract
This paper investigates the energy management system (EMS) of a conventional autonomous vehicle, with a view to enhance its powertrain efficiency. The designed EMS includes two neuro-fuzzy (NF) systems to produce the optimal torque of the engine. This control system uses the dynamic [...] Read more.
This paper investigates the energy management system (EMS) of a conventional autonomous vehicle, with a view to enhance its powertrain efficiency. The designed EMS includes two neuro-fuzzy (NF) systems to produce the optimal torque of the engine. This control system uses the dynamic road power demand of the autonomous vehicle as an input, and a PID controller to regulate the air mass flow rate into the cylinder by changing the throttle angle. Two NF systems were trained by the Grid Partition (GP) and the Subtractive Clustering (SC) methods. The simulation results show that the proposed EMS can reduce the fuel consumption of the vehicle by 6.69 and 6.35 l/100 km using the SC and the GP, respectively. In addition, the EMS based on NF trained by GP and NF trained by SC can reduce the fuel consumption of the vehicle by 11.8% and 7.08% compared with the case without the controller, respectively. Full article
(This article belongs to the Special Issue Modelling, Control and Optimisation of Complex Energy Systems)
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15 pages, 6167 KiB  
Article
A Study of Temperature-Dependent Hysteresis Curves for a Magnetocaloric Composite Based on La(Fe, Mn, Si)13-H Type Alloys
by Roman Gozdur, Piotr Gębara and Krzysztof Chwastek
Energies 2020, 13(6), 1491; https://doi.org/10.3390/en13061491 - 21 Mar 2020
Cited by 13 | Viewed by 3785
Abstract
In the present paper, the effect of temperature on the shape of magnetic hysteresis loops for a magnetocaloric composite core was studied. The composite core, based on La(Fe, Mn, Si)13-H, was set up using three component disks with different Curie temperatures. [...] Read more.
In the present paper, the effect of temperature on the shape of magnetic hysteresis loops for a magnetocaloric composite core was studied. The composite core, based on La(Fe, Mn, Si)13-H, was set up using three component disks with different Curie temperatures. The magnetic properties of the components and the outcome composite core were determined using a self-developed measurement setup. For the description of hysteresis loops, the phenomenological T(x) model was used. The presented methodology might be useful for the designers of magnetic active regenerators. Full article
(This article belongs to the Special Issue Modelling, Control and Optimisation of Complex Energy Systems)
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