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Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization

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

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 19660

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Special Issue Editors

Prof. Dr. Konstantinos Kyprianidis

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Guest Editor

Energy Engineering, Mälardalen University, Future Energy Center, 1, 722 20 Vasteras, Sweden
Interests: energy & environment; process control; system analysis; design optimization; mechanical & gas turbine engineering; aerospace; defence
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Erik Dahlquist

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Guest Editor

Business, society and engineering, Future Energy Center, Malardalen University, Vasteras, Sweden
Interests: process automation; soft-sensors; learning systems; energy efficient buildings; novel process development; pulp and paper; steel
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ambitious goals have been set by the international community to curb carbon emissions by 2030. To achieve these, steps changes are needed in technology across different sectors, from the industry, building and transport sectors to heat and power generation, transmission and distribution. This includes grid stability issues imposed by the increased penetration of renewables, as well as opportunities and challenges from the use of artificial intelligence, digitalization and automation technologies.

The purpose of this Special Issue is to collect research articles dedicated to concepts for emissions-related improvements. A special (but not exclusive) focus is put on the following topics:

Novel technologies and system optimization for improving energy efficiency and waste minimization in the industry, building and transport sectors, as well as heat and power generation, transmission and distribution.
Novel solutions for improving grid stability and renewable energy systems integration.
Applications of artificial intelligence, digitalization and advanced automation and decision support technologies in energy- and resource-intensive systems.
Novel approaches for techno-economic evaluation of emission-reduction technologies in the industry, building and transport sectors.

Prof. Konstantinos Kyprianidis
Prof. Erik Dahlquist
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. Sustainability 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 2400 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
Waste Minimization
Artificial Intelligence
Digitalization
Automation
Industry 4.0
Process Industry
Transport
Techno-Economic Analysis
Building

Published Papers (5 papers)

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Research

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19 pages, 2169 KiB

Open AccessArticle

Study on the Coupled Heat Transfer Model Based on Groundwater Advection and Axial Heat Conduction for the Double U-Tube Vertical Borehole Heat Exchanger

by Linlin Zhang, Zhonghua Shi and Tianhao Yuan

Sustainability 2020, 12(18), 7345; https://doi.org/10.3390/su12187345 - 8 Sep 2020

Cited by 7 | Viewed by 2534

Abstract

In this paper, a dynamic heat transfer model for the vertical double U-tube borehole heat exchanger (BHE) was developed to comprehensively address the coupled heat transfer between the in-tube fluid and the soil with groundwater advection. A new concept of the heat transfer effectiveness was also proposed to evaluate the BHE heat exchange performance together with the index of the heat transfer rate. The moving finite line heat source model was selected for heat transfer outside the borehole and the steady-state model for inside the borehole. The data obtained in an on-site thermal response test were used to validate the physical model of the BHE. Then, the effects of soil type, groundwater advection velocity, inlet water flow rate, and temperature on the outlet water temperature of BHE were explored. Results show that ignoring the effects of groundwater advection in sand gravel may lead to deviation in the heat transfer rate of up to 38.9% of the ground loop design. The groundwater advection fosters the heat transfer of BHE. An increase in advection velocity may also help to shorten the time which takes the surrounding soil to reach a stable temperature. The mass flow rate of the inlet water to the BHE should be more than 0.5 kg·s⁻¹ but should not exceed a certain upper limit under the practical engineering applications with common scale BHE. The efficiency of the heat transfer of the double U-tube BHE was determined jointly by factors such as the soil’s physical properties and the groundwater advection velocity. Full article

(This article belongs to the Special Issue Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization)

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27 pages, 7521 KiB

Open AccessArticle

Methodology for Energy Optimization in Wastewater Treatment Plants. Phase I: Control of the Best Operating Conditions

by Ana Belén Lozano Avilés, Francisco del Cerro Velázquez and Mercedes Llorens Pascual del Riquelme

Sustainability 2019, 11(14), 3919; https://doi.org/10.3390/su11143919 - 18 Jul 2019

Cited by 14 | Viewed by 4840

Abstract

Most purification systems work correctly from the point of view of water quality; purification, like any industrial process, must also be carried out efficiently with a minimization of costs. The overall project examined the potential benefits of using a recommended methodology for process evaluation and energy optimization in the aeration stage of activated sludge in the biological reactor at wastewater treatment plants (WWTP), which accounts for more than 44% of total operating costs. This energy control methodology encompasses the process, the installation and the control system. These three phases are examined in separate articles to make it easier to guide the user in the arduous task of optimizing energy efficiency of the WWTP from start to finish. This article focuses on Phase I of the methodology, the stage in charge of selecting the correct variables to control the best process conditions in the activated sludge system of the WWTP. Operating conditions that are a function of the recommended sludge age are influenced by exogenous factors such as temperature. The implementation of a real-time control system of the selected process variables, adapted to the needs, achieves reductions in the overall energy consumption of the installation, in this phase alone, of more than 15%, by reducing the oxygen requirements of the system and the recirculation ratios. Full article

(This article belongs to the Special Issue Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization)

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Review

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55 pages, 1893 KiB

Open AccessReview

Recent Advances in Boundary Layer Ingestion Technology of Evolving Powertrain Systems

by Dimitra Eirini Diamantidou, Md Lokman Hosain and Konstantinos G. Kyprianidis

Sustainability 2022, 14(3), 1731; https://doi.org/10.3390/su14031731 - 2 Feb 2022

Cited by 10 | Viewed by 2845

Abstract

The increasing environmental concern during the last years is driving the research community towards reducing aviation’s environmental impact. Several strict goals set by various aviation organizations shifted the research focus towards more efficient and environmentally friendly aircraft concepts. Boundary Layer Ingestion (BLI) is currently investigated as a potential technology to achieve different design goals such as energy efficiency improvement and noise emission reductions in the next generation of commercial aircraft. The technology principle is to place the propulsive unit within the boundary layer generated by the airframe body. Although several studies showed its theoretical benefits, a multidisciplinary nature is introduced in the design phase. This imposes new challenges on the current design tools. An increasing number of publications are focusing on assessing this technology while taking into account interlinks between different disciplines. The goal of this work is to review the current state-of-the-art of BLI evaluation studies. Particular focus is given to the underlying assumptions of each work, the methodology employed, and the level of fidelity of the tools used. By organizing the available work in a comprehensive manner, the up-to-date results are interpreted. The current trends and trade-offs emerging from studies are presented. Through reviewing the ongoing published work, the next steps for further development of the methods that will assess this technology are derived. Full article

(This article belongs to the Special Issue Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization)

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26 pages, 1632 KiB

Open AccessEditor’s ChoiceReview

Hydrocracking: A Perspective towards Digitalization

by Esin Iplik, Ioanna Aslanidou and Konstantinos Kyprianidis

Sustainability 2020, 12(17), 7058; https://doi.org/10.3390/su12177058 - 29 Aug 2020

Cited by 13 | Viewed by 5135

Abstract

In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation. Full article

(This article belongs to the Special Issue Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization)

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20 pages, 2549 KiB

Open AccessReview

A Review of Information Fusion Methods for Gas Turbine Diagnostics

by Valentina Zaccaria, Moksadur Rahman, Ioanna Aslanidou and Konstantinos Kyprianidis

Sustainability 2019, 11(22), 6202; https://doi.org/10.3390/su11226202 - 6 Nov 2019

Cited by 24 | Viewed by 3597

Abstract

The correct and early detection of incipient faults or severe degradation phenomena in gas turbine systems is essential for safe and cost-effective operations. A multitude of monitoring and diagnostic systems were developed and tested in the last few decades. The current computational capability of modern digital systems was exploited for both accurate physics-based methods and artificial intelligence or machine learning methods. However, progress is rather limited and none of the methods explored so far seem to be superior to others. One solution to enhance diagnostic systems exploiting the advantages of various techniques is to fuse the information coming from different tools, for example, through statistical methods. Information fusion techniques such as Bayesian networks, fuzzy logic, or probabilistic neural networks can be used to implement a decision support system. This paper presents a comprehensive review of information and decision fusion methods applied to gas turbine diagnostics and the use of probabilistic reasoning to enhance diagnostic accuracy. The different solutions presented in the literature are compared, and major challenges for practical implementation on an industrial gas turbine are discussed. Detecting and isolating faults in a system is a complex problem with many uncertainties, including the integrity of available information. The capability of different information fusion techniques to deal with uncertainty are also compared and discussed. Based on the lessons learned, new perspectives for diagnostics and a decision support system are proposed. Full article

(This article belongs to the Special Issue Assessment of Novel Technologies for Improving Energy Efficiency and Waste Minimization)

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