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Prof. Dr. Przemysław Orłowski

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Department of Automatic Control and Robotics, Faculty of Electrical Engineering, West Pomeranian University of Technology in Szczecin, 71-154 Szczecin, Poland
Interests: control systems; energy efficiency; optimization; robust control; sustainable control; inventory control; system modelling; artificial neural networks; hybrid systems; Model Predictive Control; microgrids; smart grid

Prof. Dr. Andrzej Bartoszewicz

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Guest Editor

Institute of Automatic Control, Lodz University of Technology, 90-924 Lodz, Poland
Interests: discrete time sliding mode control; control of logistic systems; control of data transmission networks

Dr. Przemysław Ignaciuk

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Faculty of Technical Physics, Computer Science and Applied Mathematics, Lodz University of Technology, 90-924 Lodz, Poland
Interests: networked systems; logistic systems; inventory control; robust control; optimal control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With high prices and a scarcity of stable sources, maximizing production and distribution efficiency has become a critical factor in creating modern and sustainable energy and transportation systems. The concepts of green management and control should be applied at all levels and phases of the distribution process, starting from suppliers, through conversion and storage, to delivery. Both theoretical studies and practical application examples are welcome.

This Special Issue invites high-quality papers covering a wide range of topics related to:

Energy efficiency;
Energy optimization;
Sustainable management;
Sustainable control systems;
Optimal control and scheduling;
Energy aware transportation systems;
Sustainable logistics;
Green networking;
Carbon footprint inequality;
Smart cities;
Internet of Things;
Cyber-physical systems;
Artificial intelligence methods;
Big data.

Prof. Dr. Przemysław Orłowski
Prof. Dr. Andrzej Bartoszewicz
Dr. Przemysław Ignaciuk
Guest Editors

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

energy efficiency
energy optimization
sustainable management
sustainable control system
optimal control and scheduling
artificial intelligence and evolutionary computation
energy aware logistics networks
green logistics networks
sustainable logistics
perishable inventory management
smart technologies
cyber-physical systems
genetic algorithm
particle swarm optimization
Nelder–Mead algorithm
multi-objective genetic algorithm
energy storage and saving
energy management
smart grids
energy sustainability
energy modeling
neural network

Published Papers (2 papers)

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Research

22 pages, 6582 KiB

Open AccessArticle

Neural Network Control of Perishable Inventory with Fixed Shelf Life Products and Fuzzy Order Refinement under Time-Varying Uncertain Demand

by Ewelina Chołodowicz and Przemysław Orłowski

Energies 2024, 17(4), 849; https://doi.org/10.3390/en17040849 - 11 Feb 2024

Viewed by 595

Abstract

Many control algorithms have been applied to manage the flow of products in supply chains. However, in the era of thriving globalization, even a small disruption can be fatal for some companies. On the other hand, the rising environmental impact of a rapid industry is imposing limitations on energy usage and waste generation. Therefore, taking into account the mentioned perspectives, there is a need to explore the research directions that concern product perishability together with different demand patterns and their uncertain character. This study aims to propose a robust control approach that combines neural networks and optimal controller tuning with the use of both different demand patterns and fuzzy logic. Firstly, the demand forecast is generated, following which the parameters of the neural controller are optimized, taking into account the different demand patterns and uncertainty. As part of the verification of the designated controller, the sensitivity to parameter changes has been determined using the OAT method. It turns out that the proposed approach can provide significant waste reductions compared to the well-known POUT method while maintaining low stocks, a high fill rate, and providing lower sensitivity for parameter changes in most considered cases. The effectiveness of this approach is verified by using a dataset from a worldwide retailer. The simulation results show that the proposed approach can effectively improve the control of uncertain perishable inventories. Full article

(This article belongs to the Special Issue Optimization and Control for Sustainable Green Energy and Transportation Systems: Latest Advances and Prospects)

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16 pages, 2095 KiB

Open AccessArticle

Optimal Control of Cascade Hydro Plants as a Prosumer-Oriented Distributed Energy Depot

by Przemysław Ignaciuk and Michał Morawski

Energies 2024, 17(2), 469; https://doi.org/10.3390/en17020469 - 18 Jan 2024

Viewed by 584

Abstract

For political and economic reasons, renewable sources of energy have gained much importance in establishing a sustainable energy economy. By their very nature, however, their benefits depend on changeable weather conditions, and are unrelated to the generation and consumption patterns in industrial or home environments. This generation–dissipation disparity induces price fluctuations and threatens the stability of the supply system, yet can be alleviated by installing energy depots. While the classic methods of energy storage are hardly cost-effective, they may be supplemented, or replaced, by a distributed system of small-scale hydropower plants with ponds used as energy reservoirs. In this paper, following a rigorous mathematical argument, a dynamic model of a multi-cascade of hydropower plants is constructed, and a cost-optimal controller, with formally proven properties, is designed. On the one hand, it allows for an increase in the owners’ revenue by as much as 30% (compared to a free-flow state); on the other hand, it reduces the load fluctuation imposed on the grid and the legacy supply system. Moreover, the risk of floods and droughts downstream resulting from inappropriate use of the plants is averted. Full article

(This article belongs to the Special Issue Optimization and Control for Sustainable Green Energy and Transportation Systems: Latest Advances and Prospects)

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