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Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020)

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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 18995

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Prof. Dr. Erol Kurt

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Guest Editor

Department of Electrical and Electronic Engineering, Gazi University, Ankara, Turkey
Interests: theoretical and experimental cutting-edge studies; energy systems including wind, solar, geothermal, and hydrogen
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Jose Manuel Lopez-Guede

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Guest Editor

Department of Automation Control, University of the Basque Country, 48940 Biscay, Spain
Interests: LiDAR data processing; image processing; control for autonomous vehicles; computational intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We cordially invite you to participate at the Eighth European Conference on Renewable Energy Systems (ECRES2020). The event is going to be organized in Istanbul, Turkey on 09–11 June 2020 by the local organizer Altınbas University. Several universities and research centers from all over the world support the event technically.

The purpose of the ECRES is to bring together researchers, engineers, and natural scientists from all over the world that are interested in the advancement of all branches of renewable energy systems. Wind, solar, hydrogen, hydro-, geothermal, solar concentrating, fuel cell, energy harvesting, and other energy-related topics are welcome.

We are open to the inclusion of related topics.

Energy materials production and characterization;
Power electronic systems for renewable energy;
Conventional energy systems and recovery;
Engines and their combustion features;
Off-shore and tidal energy systems;
Energy statistics and efficiency;
Energy transmission systems;
Heating/cooling systems;
Energy/exergy analysis;
Energy efficiency;
Wind energy;
Solar concentrating system;
Photo-voltaic and their installation;
Energy harvesters;
Smart grid;
Electrical machines;
Hydro-energy plants;
Bio-mass systems;
Bio-diesel systems;
Combustion;
Nuclear fusion systems;
Hydrogen energy systems;
Fuel-cell systems;
Efficiency in nuclear plants;
Energy education;
Energy informatics.

The papers for this special issue must be initially submitted to ECRES 2020 conference till 15th April 2020 via the link https://cmt3.research.microsoft.com/ECRES2020 and presened there. After approval, the succesfull papers will be directed to the journal.

Prof. Dr. Erol Kurt
Prof. Dr. Jose Manuel Lopez Guede
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.

Published Papers (6 papers)

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Research

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23 pages, 3948 KiB

Open AccessArticle

Novel District Heating Systems: Methods and Simulation Results

by David Huber, Viktoria Illyés, Veronika Turewicz, Gregor Götzl, Andreas Hammer and Karl Ponweiser

Energies 2021, 14(15), 4450; https://doi.org/10.3390/en14154450 - 23 Jul 2021

Cited by 6 | Viewed by 2198

Abstract

Fifth-generation district heating and cooling (5th DHC) systems offer promising approaches to decarbonizing space heating, cooling and domestic hot water supply. By using these systems, clustered buildings combined with industrial waste heat can achieve a net-zero energy balance on a variety of time scales. Thanks to the low exergy approach, these systems are highly efficient. As part of the Smart Anergy Quarter Baden (SANBA) project, the thermal energy grid simulation tool TEGSim has been further developed and used to design an ultra-low-temperature district heating (ULTDH) network with hydraulic and thermal components fitted to the specific regional characteristics of the investigated case. Borehole thermal energy storage (BTES) used as seasonal storage ensures long-term feasibility. The annual discrepancy of input of thermal energy provided by space cooling and output of energy demanded by space heating and domestic hot water is supplied by an external low-grade industrial waste heat source. This paper presents the functionality of the simulation and shows how to interpret the findings concerning the design of all components and their interplay, energy consumption and efficiencies. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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14 pages, 4109 KiB

Open AccessArticle

Applicability Study of a Sunken Vessel as an Artificial Reef in a High Wave Energy Zone

by Hyun-Dong Kim, Kyu-Han Kim, Kyu-Tae Shim and Hyumin Oh

Energies 2021, 14(14), 4374; https://doi.org/10.3390/en14144374 - 20 Jul 2021

Cited by 1 | Viewed by 1684

Abstract

The purpose of this study is to analyze the applicability of a sunken vessel as an artificial reef in a high wave energy area in a shallow water zone. Artificial reefs in general shapes are unlikely to be installed and maintained stably in high-energy wave zones. To solve this problem, a method for using a large 2000-ton class sunken vessel as an artificial reef was proposed in this study. Accordingly, we analyzed the applicability, including stability, of the sunken vessel as an artificial reef on the east coast of South Korea, where high-energy waves and swells are observed frequently. In the analysis process, various methods, such as numerical simulation and a hydraulic model experiment, were utilized. 2D and 3D numerical simulations were conducted to simulate the wave energy in the area where the sunken vessel was installed as an artificial reef to identify wave force applied to the vessel. Moreover, a hydraulic model experiment using a sunken vessel model as an artificial reef was performed to compare the stability and motion properties of the vessel model. The experimental results indicated that the stability and motion properties of the sunken vessel differed depending on the water depth. Additionally, the water depth that ensured the stability of the sunken vessel was identified. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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12 pages, 1819 KiB

Open AccessArticle

GLSDC Based Parameter Estimation Algorithm for a PMSM Model

by Artun Sel, Bilgehan Sel and Cosku Kasnakoglu

Energies 2021, 14(3), 611; https://doi.org/10.3390/en14030611 - 26 Jan 2021

Cited by 5 | Viewed by 1782

Abstract

In this study, a GLSDC (Gaussian Least Squares Differential Correction) based parameter estimation algorithm is used to identify a PMSM (Permanent Magnet Synchronous Motor) model. In this method, a nonlinear model is assumed to be the correct representation of the underlying state dynamics and the output signals are assumed to be measured in a noisy environment. Using noisy input and output signals, parameters that constitute the coefficients of the nonlinear state and input signal terms are to be estimated using the state transition matrix which is computed by the numerical means that are detailed. Since a GLSDC algorithm requires correct initial state value, this term is also estimated in addition to the unknown coefficients whose bounds are assumed to be known, which is mostly the case in the industrial applications. The batch input and output signals are used to iteratively estimate the parameter set before and after the convergence, and to recover the filtered state trajectories. A couple of different scenarios are tested by means of numerical simulations and the results are addressed. Different methods are discussed to compute better initial estimate values, to shorten the convergence time. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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15 pages, 6357 KiB

Open AccessArticle

Cell-Set Modelling for a Microtab Implementation on a DU91W(2)250 Airfoil

by Alejandro Ballesteros-Coll, Unai Fernandez-Gamiz, Iñigo Aramendia, Ekaitz Zulueta and José Antonio Ramos-Hernanz

Energies 2020, 13(24), 6723; https://doi.org/10.3390/en13246723 - 20 Dec 2020

Cited by 3 | Viewed by 1901

Abstract

Microtabs (MTs) are a regularly used flow control device in terms of wind turbine optimization. The present study introduces the application of the novel cell-set model for an MT implementation on a DU91W(2)250 airfoil. The cell-set model is based on the reusability of a mesh to add new geometries on the domain; the matching geometry is located where the user requires, and a set of cells is constructed around the mentioned geometry. Subsequently, wall boundaries are assigned to the generated region. Computational simulations were carried out for fully mesh and cell-set models: MT lengths were set at 1.0%, 1.5% and 2.0% of the airfoil chord length (c) and the MTs were placed at 93% and 95% of c from the leading edge of the airfoil. Resulting data showed that the MT behavior was similar for both models with regard to aerodynamic performance curve representations. A global relative error of 3.784% was obtained for the cell-set model and a maximum relative error of 7.332% was determined. Qualitatively, both models generated significantly similar flow stream velocity wakes on the trailing edge area of the airfoil. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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12 pages, 16186 KiB

Open AccessArticle

Image-Based River Water Level Estimation for Redundancy Information Using Deep Neural Network

by Gabriela Rocha de Oliveira Fleury, Douglas Vieira do Nascimento, Arlindo Rodrigues Galvão Filho, Filipe de Souza Lima Ribeiro, Rafael Viana de Carvalho and Clarimar José Coelho

Energies 2020, 13(24), 6706; https://doi.org/10.3390/en13246706 - 18 Dec 2020

Cited by 4 | Viewed by 1966

Abstract

Monitoring and management of water levels has become an essential task in obtaining hydroelectric power. Activities such as water resources planning, supply basin management and flood forecasting are mediated and defined through its monitoring. Measurements, performed by sensors installed on the river facilities, are used for precisely information about water level estimations. Since weather conditions influence the results obtained by these sensors, it is necessary to have redundant approaches in order to maintain the high accuracy of the measured values. Staff gauge monitored by conventional cameras is a common redundancy method to keep track of the measurements. However, this method has low accuracy and is not reliable once it is monitored by human eyes. This work proposes to automate this process by using image processing methods of the staff gauge to measure and deep neural network to estimate the water level. To that end, three models of neural networks were compared: the residual networks (ResNet50), a MobileNetV2 and a proposed model of convolutional neural network (CNN). The results showed that ResNet50 and MobileNetV2 present inferior results compared to the proposed CNN. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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Review

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20 pages, 3008 KiB

Open AccessEditor’s ChoiceReview

Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization

by Iñigo Aramendia, Unai Fernandez-Gamiz, Adrian Martinez-San-Vicente, Ekaitz Zulueta and Jose Manuel Lopez-Guede

Energies 2021, 14(1), 176; https://doi.org/10.3390/en14010176 - 31 Dec 2020

Cited by 47 | Viewed by 8094

Abstract

Large-scale energy storage systems (ESS) are nowadays growing in popularity due to the increase in the energy production by renewable energy sources, which in general have a random intermittent nature. Currently, several redox flow batteries have been presented as an alternative of the classical ESS; the scalability, design flexibility and long life cycle of the vanadium redox flow battery (VRFB) have made it to stand out. In a VRFB cell, which consists of two electrodes and an ion exchange membrane, the electrolyte flows through the electrodes where the electrochemical reactions take place. Computational Fluid Dynamics (CFD) simulations are a very powerful tool to develop feasible numerical models to enhance the performance and lifetime of VRFBs. This review aims to present and discuss the numerical models developed in this field and, particularly, to analyze different types of flow fields and patterns that can be found in the literature. The numerical studies presented in this review are a helpful tool to evaluate several key parameters important to optimize the energy systems based on redox flow technologies. Full article

(This article belongs to the Special Issue Selected Papers from Eight European Conference on Renewable Energy Systems (ECRES2020))

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