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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (15 December 2022) | Viewed by 8552

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Special Issue Editors

Prof. Dr. Valery Meshaklin

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Guest Editor

Department of Logistics and Economic Informatics, D. Mendeleev University of Chemical Technology of Russia, 125047 Moscow, Russia
Interests: process systems engineering energy and environment; energy chemistry; artificial intelligence; smart energies; sustainable environment
Special Issues, Collections and Topics in MDPI journals

Dr. Petros Groumpos

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Guest Editor

Department of Electrical and Computer Engineering, University of Patras, 26500 Rion, Greece
Interests: intelligent control; fuzzy cognition and control; artificial inteligence; energy efficiency; intelligent buildings; fuzzy cognitive maps
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Dr. Chirag Bhimani

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Guest Editor

1. Technical Expert, Gujarat Cleaner Production Centre (GCPC), Gujarat, India
2. Expert Member BAT (INDIA) at Environment Directorate, Organisation for Economic Co-operation and Development (OECD), Paris, France
Interests: reduction of air pollution; climate change and environmental policy; planning and data analytics

Prof. Dr. Alla Kravets

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Guest Editor

Department of Computer-aided design and search design, Volgograd State Technical University, 400005 Volgograd, Russia
Interests: knowledge-based systems; artificial intelligence; technological trends analysis; prior-art analisys
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Special Issue Information

Dear Colleagues,

Smart energy is one of the most significant scientific and technological trends of our time, uniting the issues of energy efficiency, new energy sources and technologies for their production, intelligent control technologies and big data analysis. Challenges related to the sustainable environment include the research and widespread implementation of breakthrough technologies for smart cities, water and air quality by reducing harmful pollution, achieving the sustainable development of the environment, and the integration of artificial-intelligence-based security systems. Critical review articles, original research and case studies are welcomed in this Special Issue, covering relevant up-to-date topics related to energy and environmental technologies, as well as smart technologies for energy and environment management, including interdisciplinary methodologies. This Special Issue, "Smart Energy and Sustainable Environment", in Energies is dedicated to exchanging ideas in the field of energy and the environment, as well as advancing knowledge among practitioners, scientists, researchers, educators and professionals to develop forward-looking ideas needed to solve problems in the fields of smart energy and sustainable environment.

Topics include but not limited:

Smart Energy Renewable Resources (SE-RR)
Smart Energy Hydrogen Technologies (SE-HT)
Smart Energy Management Systems (SE-MS) (including automatic control and lifecycle management)
Smart Energy Intelligent Technologies (SE-IT)
Smart Energy Cyber-Security (SE-CS)
Smart Cities Engineering & Management (SC-EM)
Smart Cities Sustainable Environment (SC-SE)

Prof. Dr. Valery Meshaklin
Dr. Petros Groumpos
Dr. Chirag Bhimani
Prof. Dr. Alla Kravets
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 2200 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

Smart Energy
Environment
Artificial Intelligence
Management Systems
Renewable Energy
Grid Engineering
Solar Technology
Intelligent technologies
Power Energy
Hydrogen Technology
Sustainable Environment
Climate Change
Quality Management
Pollution Management
Energy Assets Performance Management

Published Papers (10 papers)

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Research

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Open AccessArticle

Generalized Method of Mathematical Prototyping of Energy Processes for Digital Twins Development

Sergey Khalyutin

Igor Starostin

and

Irina Agafonkina

Energies 2023, 16(4), 1933; https://doi.org/10.3390/en16041933 - 15 Feb 2023

Cited by 1 | Viewed by 453

Abstract

The use of digital twins in smart power systems at the stages of the life cycle is promising. The dynamics of such systems (smart energy renewable sources, smart energy hydrogen systems, etc.), are determined mainly by the physical and chemical processes occurring inside the systems. The basis for developing digital twins is reliable mathematical models of the systems. In the present paper, the authors present a method of energy processes mathematical prototyping—an overall approach to modeling processes of various physical and chemical natures based on modern non-equilibrium thermodynamics, mechanics, and electrodynamics. Controlled parameters are connected with measured ones by developing a theoretically correct system of process dynamics equations with accuracy up to the experimentally studied properties of substances and processes. Subsequent transformation into particular mathematical models of a specific class of systems makes this approach widely applicable. The properties of substances and processes are given in the form of functional dependencies on the state of the system up to experimentally determined constant coefficients. The authors consider algorithms for identifying the constant coefficients of the functions of substances and processes properties, which complement the proposed unified approach of designing models of various physical and chemical nature systems. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

Atmospheric Ecology Modeling for the Sustainable Development of the Urban Environment

and

Energies 2023, 16(4), 1766; https://doi.org/10.3390/en16041766 - 10 Feb 2023

Cited by 1 | Viewed by 645

Abstract

The article considers the actual problem of the ecology of urban areas associated with air pollution by industrial and energy enterprises. The study is aimed at substantiating the method of forming a plan for atmospheric air pollution observation using mobile laboratories. The quantitative characteristic of sites for different urban development zones is determined as a set of estimates. The air pollution index was chosen as a total sanitary and hygienic criterion for assessing pollution. The implementation of the decision-making problem using the analytic network process method is considered. Parameters of the city and environment that affect the assessment of atmospheric air quality were selected in the course of the study. A network structure of mutual influence of the studied parameters is formed. The architecture of the decision support system based on the proposed method is given. The created software makes it possible to automate the modeling of the distribution of pollutants in the atmosphere. The computational experiment is presented on the example of the Volgograd agglomeration, Russia. The proposed approach can significantly improve the organization of monitoring by mobile laboratories and reduce the cost of obtaining data on urban air pollution without increasing the number of existing observation laboratories, both stationary and mobile. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

Experimental and Mathematical Analysis of the Kinetics of the Low-Waste Process of Butyl Lactate Synthesis

Valeriy P. Meshalkin

Roman A. Kozlovskiy

Mikhail R. Kozlovskiy

Yaroslav A. Ibatov

Mikhail S. Voronov

Ivan A. Kozlovskiy

Tamara B. Chistyakova

and

Antony M. Nzioka

Energies 2023, 16(4), 1746; https://doi.org/10.3390/en16041746 - 09 Feb 2023

Viewed by 464

Abstract

Butyl lactate is a green solvent produced from renewable materials through the reaction of ammonium lactate with n-butanol. It could be a source material for valuable products such as propylene glycol, acrylic acid, its derivatives, and the cyclic monomer of polylactic acid (PLA)—lactate. In this study, we present novel non-catalytic interactions of ammonium lactate and n-butanol carried out in the temperature range of 130–170 °C in a closed system. The study focused on the kinetic modelling of the reaction between ammonium lactate and n-butanol to derive a mathematical model for the reactor unit of butyl lactate synthesis. The aim of this work was to study the kinetics of the interaction between ammonium lactate and n-butanol, as well as to obtain a kinetic model of the process and its parameters. We suggested the chemical transformation routes and determined the kinetic model and parameters that adequately describe the process in a closed system within the studied condition range. The study proposes the first kinetic model that accounts for lactamide formation through two routes. This study showed that the high-temperature non-catalytic interaction of ammonium lactate and n-butanol could be one of the prospective synthesis routes. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

Resource and Energy Saving Control of the Steelmaking Converter Process, Taking into Account Waste Recycling

and

Energies 2023, 16(3), 1302; https://doi.org/10.3390/en16031302 - 26 Jan 2023

Viewed by 677

Abstract

With the development of the energy control system of iron and steel enterprises, the urgency of solving the problem of the resource and energy saving control of steelmaking processes increases, taking into account the reconfiguration of production to a new task, intensification of the processes of recycling of raw materials, as well as reducing the waste intensity of production. The way to solve the problem of resource and energy saving of steelmaking production is the creation of a computer system. It allows one to analyze the state of the refractory converter lining, calculation of the material and thermal balances, the amount of slag-forming materials, the quantitative characteristics of slag corrosion, as well as predict the phase and chemical composition of the slag in order to impart the properties necessary in the production of mineral binders and other building materials. The computer system allows one to identify complex fuzzy relationships between process parameters and issue recommendations on the resource and energy saving control of the converter process, taking into account the waste recycling. The testing of the computer system, according to the industrial data of the enterprises CherMF (PJSC Severstal) and PJSC NLMF, confirmed its operability and the possibility of its use at iron and steel enterprises. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

New Method of Degradation Process Identification for Reliability-Centered Maintenance of Energy Equipment

Konstantin Zadiran

and

Maxim Shcherbakov

Energies 2023, 16(2), 575; https://doi.org/10.3390/en16020575 - 04 Jan 2023

Viewed by 742

Abstract

Advancements in energy technologies created a new application for gas turbine generators, which are used to balance load. This usage also brought new challenges for maintenance because of harsh operating conditions that make turbines more susceptible to random failures. At the same time, reliability requirements for energy equipment are high. Reliability-centered maintenance based on forecasting the remaining useful life (RUL) of energy equipment, offers improvements to maintenance scheduling. It requires accurate forecasting methods to be effective. Defining stages in energy equipment operation allows for the improvement of quality of data used for training. At least two stages can be defined: normal operation and degradation process. A new method named Head move—Head move is proposed to robustly identify the degradation process by detecting its starting point. The method is based on two partially overlapping sliding windows moving from the start of operation to the end of life of the energy equipment and Kruskal-Wallis test to compare data within these windows. Using this data separation, a convolutional neural network-based forecasting model is applied for RUL prediction. The results demonstrate that the proposed degradation process identification (DPI) method doubles the accuracy when compared to the same forecasting model but without degradation process identification. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

The Influence of Various Solar Radiations on the Efficiency of a Photovoltaic Solar Module Integrated with a Passive Cooling System

Saeed Rubaiee

and

M. A. Fazal

Energies 2022, 15(24), 9584; https://doi.org/10.3390/en15249584 - 16 Dec 2022

Cited by 2 | Viewed by 882

Abstract

The thermal regulation of a silicon photovoltaic (PV) solar system is essential as the module surface temperature beyond 25 °C deteriorates its Power Conversion Efficiency (PCE). The intensity of solar radiation seems to have a crucial impact on the PCE of a PV solar system. The present study aims to assess the effect of solar radiation variations on the PCEs of PV modules integrated with and without passive cooling systems. The used passive cooling systems are (a) multi-pipe copper frame filled with Phase Change Material (PCM) and (b) multi-pipe copper frame filled with ZnO-doped PCM. The tests were conducted at the University of Jeddah in the month of March at various local times. The results show that the ambient and module surface temperatures are directly dominated by solar radiations. The conventional PV solar system presents a higher module surface temperature as compared to that of a PV system integrated with ZnO/PCM. The enhanced module surface temperature decreases the open circuit voltage (V_oc) and slightly increases the short circuit current (I_sc) indicating its reduced electric efficiency. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

The Software Cache Optimization-Based Method for Decreasing Energy Consumption of Computational Clusters

Alla G. Kravets

and

Vitaly Egunov

Energies 2022, 15(20), 7509; https://doi.org/10.3390/en15207509 - 12 Oct 2022

Cited by 1 | Viewed by 883

Abstract

Reducing the consumption of electricity by computing devices is currently an urgent task. Moreover, if earlier this problem belonged to the competence of hardware developers and the design of more cost-effective equipment, then more recently there has been an increased interest in this issue on the part of software developers. The issues of these studies are extensive. From energy efficiency issues of various programming languages to the development of energy-saving software for smartphones and other gadgets. However, to the best of our knowledge, no study has reported an analysis of the impact of cache optimizations on computing devices’ power consumption. Hence, this paper aims to provide an analysis of such impact on the software energy efficiency using the original software design procedure and computational experiments. The proposed Software Cache Optimization (SCO)-based Methodology was applied to one of the key linear algebra transformations. Experiments were carried out to determine software energy efficiency. RAPL (Running Average Power Limit) was used—an interface developed by Intel, which provides built-in counters of Central Processing Unit (CPU) energy consumption. Measurements have shown that optimized software versions reduce power consumption up to 4 times in relation to the basic transformation scheme. Experimental results confirm the effectiveness of the SCO-based Methodology used to reduce energy consumption and the applicability of this technique for software optimization. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessArticle

Multifractal Analysis of the Mechanical PropOKerties of the Texture of Biopolymer-Inorganic Composites of Chitosan-Silicon Dioxide

and

Energies 2022, 15(19), 7147; https://doi.org/10.3390/en15197147 - 28 Sep 2022

Viewed by 603

Abstract

An original multifractal algorithm is proposed for calculating the fractal characteristics of the cluster texture of biopolymer-inorganic (BIN) composites from microphotographic images (MPIs) of their texture, which allows one to determine the quantitative dependence of the mechanical properties of biopolymer–inorganic composites on the characteristics of their cluster texture. As a result of the studies conducted on the MPI texture of the “chitosan-silicon dioxide” BIN composites using a multifractal algorithm, it was found that such important indicators as strength and plasticity can be quantitatively described using generalized fractal pixel dimensions of MPI samples of the BIN composite. It was established that when the amount of silicon dioxide in the samples of the BIN composite changes, the mechanical characteristics of the BIN composites, such as strength and plasticity, can be quantitatively described using generalized fractal pixel dimensions of the MPIs of the BIN composite samples. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessFeature PaperArticle

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Nguyen Thanh Viet

and

Alla G. Kravets

Energies 2022, 15(18), 6613; https://doi.org/10.3390/en15186613 - 09 Sep 2022

Cited by 6 | Viewed by 1033

Abstract

The development of emerging technologies not only has recently affected current industrial production but also has generated promising manufacturing opportunities that impact significantly on social and economic factors. Exploring upcoming renovation tendencies of technologies prematurely is essential for governments, research and development institutes, and industrial companies in managing strategies to achieve dominant advantages in business competitiveness. Additionally, the prospective changes, the scientific research directions, and the focus of technologies are crucial factors in predicting promising technologies. On the other hand, Industry 4.0 revolutionizes standards and models by accompanying significant technology developments in numerous sectors, including the sector of Smart energy. Moreover, asset performance management is always a prominent topic that has attained prevalence over the last decade because numerous challenges force all industrial companies to optimize their asset usability. However, to the best of our knowledge, no study reported an analysis of technology trends of asset performance management in the Smart energy sector by using proper data mining methods. Hence, this paper aims to fill in this gap and provide an analysis of technology trends of asset performance management in the Smart energy sector by structuring and exploring research subjects, considering problems, and solving methods with numerous experiments on scientific papers and patent data. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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Open AccessReview

Key Performance Indicators for Smart Energy Systems in Sustainable Universities

Claudiu Vasile Kifor

Alexandru Olteanu

and

Mihai Zerbes

Energies 2023, 16(3), 1246; https://doi.org/10.3390/en16031246 - 23 Jan 2023

Cited by 1 | Viewed by 951

Abstract

Sustainable campus management includes energy-saving measures and waste reduction and has become important to many universities, being part of the institution’s societal responsibility. Smart energy systems (SESs), as part of campus energy management, can bring many benefits, including increased efficiency, reduced energy consumption, reduced emissions, increased reliability, and real-time control, and facilitate the integration of the renewable energy systems (RES). Despite the growing interest in energy efficiency and for the initiatives and projects to implement SESs, there are no universally accepted standards for assessing the performance of SESs, with most techniques being dedicated to subsystems. A KPI (key performance indicator) framework for evaluating the SESs’ performance from university campuses is proposed, starting from the current findings and priorities from the scientific literature, energy standards, legislation, and university rankings. The framework can support the implementation, operation, and evaluation of the SESs from university campuses, based on SES requirements and the stakeholders’ goals. Unlike previously developed solutions, the framework is focused not only on the technical side of SESs but also on the role that education, research, and innovation should have in sustainable development, making universities key contributors to achieving these goals. Full article

(This article belongs to the Special Issue Smart Energy and Sustainable Environment)

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