bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Artificial Intelligence for EV Charging and Discharging Scheduling and Dynamic Pricing: A Review
Authors: Chen Qin , Folly Komla Agbenyo
Published: December 2022

The high penetration of electric vehicles (EVs) will burden the existing power delivery infrastructure if their charging and discharging are not adequately coordinated. Dynamic pricing is a special form of demand response that can encourage EV owners to participate in scheduling programs. Therefore, EV charging and discharging scheduling and its dynamic pricing model are important fields of study. Many researchers have focused on artificial intelligence-based EV charging demand forecasting and scheduling models and suggested that artificial intelligence techniques perform better than conventional optimization methods such as linear, exponential, and multinomial logit models. However, only a few research studies focused on EV discharging scheduling (i.e., vehicle-to-grid, V2G) because the concept of EV discharging electricity back to the power grid is relatively new and evolving. Therefore, a review of existing EV charging and discharging-related studies is needed to understand the research gaps and to make some improvements in future studies. This paper reviews EV charging and discharging-related studies and classifies them into forecasting, scheduling, and pricing mechanisms. The paper determines the linkage between forecasting, scheduling, and pricing mechanism and identifies the research gaps in EV discharging scheduling and dynamic pricing models.
Fifth-Generation District Heating and Cooling Networks Based on Shallow Geothermal Energy: A review and Possible Solutions for Mediterranean Europe
Authors: García-Céspedes Jordi , Herms Ignasi , Arnó Georgina , de Felipe José Juan
Published: December 2022

This document presents a comprehensive review of research works, regulatory frameworks, technical solutions, and commercial trends related to the integration of shallow geothermal energy (SGE) technologies in modern 5th-generation district heating and cooling (5GDHC) networks. This literature and market analysis is contextualized by the present geopolitical, environmental, and societal scenario in Europe. In this sense, decarbonization of the heating and cooling sector is a crucial piece in the energy transition puzzle to keep global warming below the critical threshold of 1.5 °C by the next century. Moreover, Ukraine war has added urgency to end up with fossil fuel dependency. The most relevant outcome of this literature review is the synergistic relationship between SGE, 5GDHC networks, and urban environments. SGE is most efficiently deployed in urban environments when it is part of a district heating and cooling network, and the modern concept of 5GDHC is the most suitable scenario for it. Since the potential contribution of SGE to the decarbonization of the heating and cooling supply is mostly untapped across Europe, this synergistic effect represents a possible boost. Hybridization with solar photovoltaics and/or storage makes it even more attractive. Outstanding cases are reviewed, challenges for the future are presented, and tools to overcome social reluctance and/or lack of awareness are described, along with a discussion of the stimuli for the deployment of SGE and 5GDHC networks. A particular focus on Mediterranean countries is presented, where SGE systems and DHC networks of any kind show a particularly low deployment compared to the rest of Europe. To this end, the second part of this work evaluates, justifies, and analyzes the possibilities and potentialities of their application in this zone.
Review of Underground Mining Methods in World-Class Base Metal Deposits: Experiences from Poland and Chile
Authors: Skrzypkowski Krzysztof , Gómez René , Zagórski Krzysztof , Zagórska Anna , Gómez-Espina Roberto
Published: December 2022

There are several massive deposits around the world with different geological characteristics. Thus, different mining methods and strategies are applied based on the particularity of each method and mine experience. Particularly, in this work, we review and summarize the underground exploitation of some world-class base metal deposits based on Poland and Chilean experiences. Here, the main geological and mining parameters of Poland and Chilean mines applied in massive deposits are reported and analyzed. In Poland, mainly room and pillar methods (and variants) have been applied in massive deposits. Here, back-filling is required to maintain the mine’s stability due to the large deposit size and open areas. In Chile, the block caving method is commonly used in massive underground deposits where less development is required. Here, the cave is naturally filled with broken material and a large subsidence zone is generated. In this review, it has been observed that different underground methods and strategies can be effectively used in massive deposits. Some parameters that influenced the method selection are mainly related to rock mechanics, ore recovery and dilution, subsidence zone, extraction rate, and mining experience. Here, key mining variables and parameters such as productivity, support, and equipment, as well as various issues related to the world-class deposit are studied. Additionally, a comparison between both experiences is presented, highlighting the main geological and mining parameters. This study can be used as a reference to evaluate the different option of underground mining methods to be applied in future massive mine projects with similar geological characteristics.
Retrofit Proposals for Energy Efficiency and Thermal Comfort in Historic Public Buildings: The Case of the Engineering Faculty’s Seat of Sapienza University
Authors: Vallati Andrea , Di Matteo Miriam , Fiorini Costanza Vittoria
Published: December 2022

The building sector greatly contributes to energy consumption and Greenhouse Gas emissions, relating to the whole building life cycle. Boasting a huge building heritage of historical and architectural value, Europe faces challenging retrofit perspectives, as the potential for high energy efficiency has to be exploited while preserving the buildings’ original characteristics. The present work aims to feature the influence of a passive strategy on a heritage building in a mild climate. As historical its façade cannot be modified, its large glazing areas involve multiple issues, such as an increase in the heating (QH) and cooling (QC) energy demands and the risk of thermal discomfort. Thus, window replacement was proposed for retrofitting. A dynamic simulation model in TRNSYS was validated with experimental data collected by the continuous monitoring of walls of different thicknesses and orientations. Solutions from replacement with Double Glazing Units (DGUs) with improved thermal insulation, to internal shading activation were applied. All configurations were compared in terms of QH, QC, thermal performance of the building and user comfort (Fanger). Low-e DGU enabled the saving of up to 14% of the annual energy demand, and shading also offered good results in summer, reducing QC by 19%. In summer, DGU involved a maximum PPD reduction of 10 units.
SolNet: A Convolutional Neural Network for Detecting Dust on Solar Panels
Authors: Onim Md Saif Hassan , Sakif Zubayar Mahatab Md , Ahnaf Adil , Kabir Ahsan , Azad Abul Kalam , Oo Amanullah Maung Than , Afreen Rafina , Hridy Sumaita Tanjim , Hossain Mahtab , Jabid Taskeed , Ali Md Sawkat
Published: December 2022

Electricity production from photovoltaic (PV) systems has accelerated in the last few decades. Numerous environmental factors, particularly the buildup of dust on PV panels have resulted in a significant loss in PV energy output. To detect the dust and thus reduce power loss, several techniques are being researched, including thermal imaging, image processing, sensors, cameras with IoT, machine learning, and deep learning. In this study, a new dataset of images of dusty and clean panels is introduced and applied to the current state-of-the-art (SOTA) classification algorithms. Afterward, a new convolutional neural network (CNN) architecture, SolNet, is proposed that deals specifically with the detection of solar panel dust accumulation. The performance and results of the proposed SolNet and other SOTA algorithms are compared to validate its efficiency and outcomes where SolNet shows a higher accuracy level of 98.2%. Hence, both the dataset and SolNet can be used as benchmarks for future research endeavors. Furthermore, the classes of the dataset can also be expanded for multiclass classification. At the same time, the SolNet model can be fine-tuned by tweaking the hyperparameters for further improvements.
Risk Assessment of User Aggregators in Demand Bidding Markets
Authors: Tien Ching-Jui , Tu Chia-Sheng , Tsai Ming-Tang
Published: December 2022

This paper mainly discusses the demand bidding and risk management of user aggregators by considering profit and risk. The covariance matrix of demand price was used to analyze the risk model under an uncertain demand price. By considering revenue and cost, the demand bidding strategy of user aggregators was derived to obtain the maximum profit. By using a risk-tolerance parameter β, a new demand bidding model for the user aggregators that takes both risk and profit into consideration was formulated. We simulated the risk posed by fluctuating demand prices for user aggregators using this model. Finally, this paper proposes Feasible Particle Swarm Optimization (FPSO) to solve the demand bidding model of user aggregators. Through the dynamic adjustment of control factor parameters in the FPSO, we changed the behavioral characteristics of various types of particles, improved the search efficiency and stability of particles in high-dimensional space, and sought the optimal solution for the system as a whole. This paper provides a parameter adjustment mechanism, improves the capability of algorithm implementation, and increases the probability of finding the optimal solution. The simulation results suggest that a tradeoff between profit and risk needs to be considered in the search process. By doing so, enterprises’ abilities in terms of operation and management control can be enhanced, and effective demand management can be achieved.
E-Bike Motor Drive: A Review of Configurations and Capabilities
Authors: Contò Chiara , Bianchi Nicola
Published: December 2022

In recent years, the mobility sector is undergoing a revolution, which is resulting also into a worldwide spread of light electric vehicles, such as electric scooters and bicycles. The increasing public concern about environmental problems further feeds this revolution. Electric-bicycles (or e-bikes) are a new trend which fits different riders’ needs. In fact, they offer extended range and ease of use, allowing riders to travel in urban centres, but also to take longer trips. E–bikes are reliable, easy to ride, affordable, and they help people live and travel a little greener, with a great benefit for their health. Many Companies (such as Brose, Bafang, Bosch and Shimano) developed performing e-bike motor drives. However, there is not a detailed general procedure to help the choice and design of electric bikes, in particular concerning the electric machine. This review focuses on the analysis of different motors for e-bike application. First, the e-bike system state of art is presented. The pedal-assist and power-on-demand e-bike system typologies are presented, together with the most popular parallel configuration and the less common series configuration. Further on, the environmental resistances are analysed for a traditional bicycle system and then the force balance is extended to the electric vehicle example. The most common Lithium-ion battery and the battery management system state of art is discussed, presenting design schemes and typical performances. Concerning the electrical machine, some electromagnetic design approaches are described, together with some data on commercial motors. Finite element analysis of a common motor model is carried out and some experimental tests are presented to highlight their capabilities. Different control strategies are compared, including innovative solutions and new trends.
Assessment of the Hot-Cracking Susceptibility of Welded Joints of the 7CrMoVTiB10-10 Bainitic Steel Used in Heat Exchangers
Authors: Adamiec Janusz
Published: December 2022

Bainitic steel containing approx. 2.25% Cr and 0.6 Mo with micro-additions of V, Ti, and B, designated as 7CrMoVTiB10-10 (T/P24), is one of the new construction materials used in new supercritical power units. The weldability of 7CrMoVTiB10-10 is defined as the hot-cracking susceptibility, it should be stated that the hot cracking in the welded joints of 7CrMoVTi10-10 is determined by phenomena occurring in the high-temperature brittleness range (HTBR). In this work, the HTBR is established for both the base material and welding conditions, taking into account the critical temperature-strain intensity (CST) and the critical strain speed (CSS). The HTBR for 7CrMoVTi10-10 is 122 °C wide and covers temperatures from 1394 °C to 1516 °C. Under imposed deformation conditions (typical during welding), the HTBR extends to a width of 293 °C towards lower temperatures, i.e., from 1516 °C to 1223 °C. The CSS = 0.83 1/s, the CST = 0.003 1/°C, and the Rf index = 0.12, which can be adopted as the criteria for the susceptibility of 7CrMoVTiB 10-10 to hot cracking under imposed deformation conditions. The hot cracking in 7CrMoVTiB10-10 occurs as a result of the loss of cohesion by the thin liquid layer crystallising between the growing weld crystals. Such cracks appear when the CSS or the CST is exceeded within the HTBR.
Design and Evaluation of Wireless Power Monitoring IoT System for AC Appliances
Authors: Tsai Huan-Liang , Truong Le Phuong , Hsieh Wei-Hung
Published: December 2022

The paper is aimed to develop a wireless alternating current (AC) power monitoring module which features the advantage of cost-effectiveness and sufficient reliability for the proposed AC power monitoring Internet of Things (IoT) system. The novel wireless AC power monitoring module consists of both ZMPT101B voltage sensor and ACS712-20 current sensor; a 16-bit analog-to-digital (ADC) ADS1114 with I2C interface and WeMos D1 Mini Wi-Fi module were integrated for monitoring refrigerator and air conditioner appliances with the ratings of single-phase 110/220 VAC, respectively. First, both analog readings of V/I sensors for AC appliances are converted into data streams in compliance with I2C (inter-integrated circuit) protocol, and are forwarded to a WeMos D1 Mini Wi-Fi module for the corresponding values of instantaneous electric power and energy, power factor (pf), and frequency well programmed in the built-in ESP8266EX IoT-based microcontroller unit (MCU) based on the well-known AC power fundamentals. All of the important AC power parameters are sent to the ThingSpeak IoT platform through Wi-Fi network. The visualization of voltage, current, electric power and energy, pf, and frequency is illustrated in the ThingSpeak IoT platform. Both close agreement and confidence of the proposed AC power monitoring IoT system for both refrigerator and air conditioner are evaluated with two CM3286-1 AC Power Meters. Taking the commercialized CM3286-1 instrument as reference, the values of mean absolute percentage error (MAPE) for above six electrical parameter readings are all less than 2%. The evaluation results illustrate sufficient closeness of agreement and confidence for the proposed wireless AC power monitoring IoT system for in situ monitoring AC appliances with single-phase 110/220 VAC ratings. Furthermore, the cost of the proposed AC power monitoring module is less than 100 USD, which makes the novel module more cost-effective than commercialized AC power meters which generally cost over 1000 USD. The novelties of the work are the following: (1) the introduction of ADS1114 provides I2C interface directly for Wi-Fi module to reduce the capital cost of the proposed wireless AC power monitoring module; (2) the sufficient confidence of the proposed AC power monitoring IoT system has been validated with closeness of agreement as compared to the commercialized CM3286-1 AC Power Meters. These make the assessment action of environmental, social, and governance (EGS) for stakeholders much more feasible with the advantages of cost-effectiveness and sufficient confidence.
Multivariate Data-Driven Models for Wind Turbine Power Curves including Sub-Component Temperatures
Authors: Astolfi Davide , Pandit Ravi , Lombardi Andrea , Terzi Ludovico
Published: December 2022

The most commonly employed tool for wind turbine performance analysis is the power curve, which is the relation between wind intensity and power. The diffusion of SCADA systems has boosted the adoption of data-driven approaches to power curves. In particular, a recent research line involves multivariate methods, employing further input variables in addition to the wind speed. In this work, an innovative contribution is investigated, which is the inclusion of thirteen sub-component temperatures as possible covariates. This is discussed through a real-world test case, based on data provided by ENGIE Italia. Two models are analyzed: support vector regression with Gaussian kernel and Gaussian process regression. The input variables are individuated through a sequential feature selection algorithm. The sub-component temperatures are abundantly selected as input variables, proving the validity of the idea proposed in this work. The obtained error metrics are lower with respect to benchmark models employing more typical input variables: the resulting mean absolute error is 1.35% of the rated power. The results of the two types of selected regressions are not remarkably different. This supports that the qualifying points are, rather than the model type, the use and the selection of a potentially vast number of input variables.
Integral Thermal Management Studies in Winter Conditions with a Global Model of a Battery-Powered Electric Bus
Authors: Broatch Alberto , Olmeda Pablo , Bares Pau , Aceros Sebastián
Published: December 2022

The potential of e-bus transportation to improve air quality and reduce noise pollution in cities is significant. In order to improve efficiency and extend the useful life of these vehicles, there is a growing need to investigate improvements for the thermal management system of electric city buses. In electric vehicles, there are several systems whose thermal behaviors need to be regulated, such as batteries, electric machines, power electronics, air conditioning, and cabin. In this study, a 0D/1D model of an electric city bus is developed that integrates all sub-models of the powertrain, auxiliaries, and thermal management system. This model is used to evaluate different configurations and thermal management strategies of the electric urban bus by simulating public transport driving cycles in Valencia, Spain, under winter conditions. First, the original thermal–hydraulic circuit of the bus was modified, resulting in an improvement in the battery energy consumption with savings of 11.4% taking advantage of the heat produced in the electric motors to heat the battery. Then, the original PTC heating system of the bus was compared with a proposed heat pump system in terms of battery power consumption. The heat pump system achieved an energy savings of 3.9% compared to the PTC heating system.
Renewable Energy-Based Energy-Efficient Off-Grid Base Stations for Heterogeneous Network
Authors: Islam Khondoker , Hossain Md. , Ruhul Amin B. , Shafiullah G. , Sohel Ferdous
Published: December 2022

The heterogeneous network (HetNet) is a specified cellular platform to tackle the rapidly growing anticipated data traffic. From a communications perspective, data loads can be mapped to energy loads that are generally placed on the operator networks. Meanwhile, renewable energy-aided networks offer to curtailed fossil fuel consumption, so to reduce the environmental pollution. This paper proposes a renewable energy based power supply architecture for the off-grid HetNet using a novel energy sharing model. Solar photovoltaics (PV) along with sufficient energy storage devices are used for each macro, micro, pico, or femto base station (BS). Additionally, a biomass generator (BG) is used for macro and micro BSs. The collocated macro and micro BSs are connected through end-to-end resistive lines. A novel-weighted proportional-fair resource-scheduling algorithm with sleep mechanisms is proposed for non-real time (NRT) applications by trading-off the power consumption and communication delays. Furthermore, the proposed algorithm with an extended discontinuous reception (eDRX) and power saving mode (PSM) for narrowband internet of things (IoT) applications extends the battery lifetime for IoT devices. HOMER optimization software is used to perform optimal system architecture, economic, and carbon footprint analyses while the Monte-Carlo simulation tool is used for evaluating the throughput and energy efficiency performances. The proposed algorithms are validated through the practical data of the rural areas of Bangladesh from which it is evident that the proposed power supply architecture is energy-efficient, cost-effective, reliable, and eco-friendly.
Effect of the Design Parameters of the Combustion Chamber on the Efficiency of a Thermal Oxidizer
Authors: Cao Quang Hat , Lee Sang-Wook
Published: December 2022

Carbon monoxide is often produced during the incomplete combustion of volatile organic carbon compounds in industry. In the combustion chamber for oxidizing carbon monoxide emissions, a penta-coaxial port device can be used to improve the process of mixing the fuel and oxidizer. In this study, the conjugate heat transfer analysis was conducted by solving both Reynolds-averaged Navier–Stokes equations with the eddy dissipation model and solid heat conduction equation in the wall using Fluent 2019R2 to simulate the reaction flow of a volatile organic carbon compound burner and heat transfer of the stack insulation layer. The mass fractions of the O2, CO2, and CO gases; the temperature; and the velocity distribution in a combustion chamber were computed to investigate how various design parameters of the combustor, including air inlet size and stack height, and air inflow conditions affected the combustion performance. Results show that the size of the air inlet had only a minor effect on combustion efficiency and that the airstream forced by a fan significantly enhanced the combustion performance. In particular, increasing the height of the stack from 2 m to 4 m greatly increased combustion efficiency from 63% to 94%, with a 50% increase in the incoming air flow rate by natural convection, which demonstrates the importance of stack height in combustor design.
A Novel Method for Detection and Location of Series Arc Fault for Non-Intrusive Load Monitoring
Authors: Dowalla Krzysztof , Bilski Piotr , Łukaszewski Robert , Wójcik Augustyn , Kowalik Ryszard
Published: December 2022

Series arc faults cause the majority of household fires involving electrical failures or malfunctions. Low-fault current amplitude is the reason for the difficulties faced in implementing effective arc detection systems. The paper presents a novel arc detection and faulty line identification method. It can be easily used in the low-voltage Alternate Current (AC) household network for arc detection in the Non-Intrusive Load Monitoring (NILM). Unlike existing methods, the proposed approach exploits both current and voltage signal time domain analysis. Experiments have been conducted with up to six devices operating simultaneously in the same circuit with an arc fault generator based on the IEC 62606:2013 standard. Sixteen time-domain features were used to maximize the arc-fault detection accuracy for particular appliances. Performance of the random forest classifier for arc fault detection was evaluated for 28 sets of features with five different sampling rates. For the single period analysis arc, detection accuracy was 98.38%, with F-score of 0.9870, while in terms of the IEC 62606:2013 standard, it was 99.07%, with F-score of 0.9925. Location of a series arc fault (line selection) was realized by identifying devices powered by the faulty line. The line selection was based on the Mean Values of Changes feature vector (MVC50), calculated for absolute values of differences between adjacent current signal periods during the arc fault. The fault location accuracy was 93.20% for all cases and 98.20% for cases where the arc fault affected a single device.
The Importance of City Logistics for Urban Tourism Development: Searching for a New Research Field
Authors: Hącia Ewa , Wagner Natalia , Łapko Aleksandra
Published: December 2022

This paper presents the results of a study on city logistics in the urban tourist area as a research field. Both disciplines are developing intensively, and the research results have many implications for business practices, in particular for alternative fuel for transport, energy savings, waste management, and creating new business models that meet the challenges of modern society. In the era of decarbonisation, city logistics and tourism must define new rules for coexistence. The identified dominant subfields (tourism, logistics, urban transport, urban development and planning, new technologies, and sustainable development) and the links between them have pointed to some research gaps and suggested a direction for further research. The research procedure applied, adapted to the overall goal of the study, consists of an analysis of publications in the Scopus database (February 2022). A keyword co-occurrence network for the research field of city logistics in the urban tourist area is constructed with the use of the VOSviewer software. It follows from the analysis that the research area combining city logistics and city tourism remains relatively unexplored. Forming only a small part of research into city logistics, it has unexplored research potential. The research area under analysis is interdisciplinary in nature.
Use of Archival Aerial Photos and Images Acquired Using UAV to Reconstruct the Changes of Annual Load of the Suburban Landfill: Case Study of Promnik, Poland
Authors: Hajdukiewicz Maciej
Published: December 2022

The aim of this study is to evaluate the rate of the changes of the annual volume of the municipal waste deposited in the landfill in Promnik, Poland in the period 2003–2020, and to assess the applicability of archival aerial photos for this kind of survey. The landfill analyzed in this article is the main recipient of garbage from the city of Kielce, with a population of 200,000. That assessment is crucial for municipal waste management planning, bio-gases management, expected use time and reclamation of landfill area. Important issues to consider are how the new legal regulations, in effect from 2012, affected the amount of the municipal waste and the rate of landfill growth. Measurement of the volume changes was conducted using a photogrammetric method on the archival aerial photos from 2003 to 2015 and aerial photos acquired using an unmanned air vehicle in 2020. Reference material was digital elevation model (DEM) of this area, derived from aerial laser scanning performed in 2014. Chamber works on the images were conducted using PCI Orthoengine and Agisoft Metashape software. DEMs of the landfill area were generated, and the volume changes of the dump canopy have been determined between 2003, 2014, 2015 and 2020. Height changes were measured along cross-sections and in probe of 150 random points. A significant decrease in the annual load of the municipal waste after 2014 has been found, from over 70,000 m3 to 50,000 m3, which proves the effectiveness of the regulations introduced in 2012. Bio-gas productivity potential of the bio-active municipal waste layer was also assessed.
Review of Efficiency Improvement Technologies of Wind Diesel Hybrid Systems for Decreasing Fuel Consumption
Authors: Sosnina Elena , Dar’enkov Andrey , Kurkin Andrey , Lipuzhin Ivan , Mamonov Andrey
Published: December 2022

The article contains current information on the development of energy-efficient technologies of wind–diesel hybrid systems (WDHS) for decreasing organic fuel consumption. As a result of the review, three research directions are identified: WDHS design optimization, the main equipment and control system improvements. A comparison of their effectiveness is presented. The methods of selecting WDHS configuration, equipment capacities and location, the optimization algorithms and objective functions used are described and WDHS project feasibility calculation results are presented. The methods to improve energy efficiency of WDHS major units’ (diesel generator (DG) and wind turbine (WT)) are considered. The methods to decrease diesel fuel consumption using special devices and energy storage system are presented. Special attention is paid to WDHS operating modes’ control methods and strategies, as well as to algorithms providing the efficient system operation. As a result, recommendations for the design of both isolated and on-grid WDHS are formulated.
Review of the Li-Ion Battery, Thermal Management, and AI-Based Battery Management System for EV Application
Authors: Ghalkhani Maryam , Habibi Saeid
Published: December 2022

With the large-scale commercialization and growing market share of electric vehicles (EVs), many studies have been dedicated to battery systems design and development. Their focus has been on higher energy efficiency, improved thermal performance and optimized multi-material battery enclosure designs. The integration of simulation-based design optimization of the battery pack and Battery Management System (BMS) is evolving and has expanded to include novelties such as artificial intelligence/machine learning (AI/ML) to improve efficiencies in design, manufacturing, and operations for their application in electric vehicles and energy storage systems. Specific to BMS, these advanced concepts enable a more accurate prediction of battery performance such as its State of Health (SOH), State of Charge (SOC), and State of Power (SOP). This study presents a comprehensive review of the latest developments and technologies in battery design, thermal management, and the application of AI in Battery Management Systems (BMS) for Electric Vehicles (EV).
Buffer Tank Discharge Strategies in the Case of a Centrifugal Water Chiller
Authors: Kostyák Attila , Béres Csaba , Szekeres Szabolcs , Csáky Imre
Published: December 2022

In this article, energy optimization of the cooling system of IKEA Budaörs is carried out. The cooling system is served by a centrifugal water chiller and includes a large-volume cooling buffer tank. The facility operates the hydraulic system of the buffer storage tank only during the transitional period. The main goal is to reduce energy consumption by changing the operating strategy of the existing system. To test the operating strategies, the operation and the thermal load of the shopping center during the summer season had to be simulated to find the best operation strategy. A hybrid method (real data and calculated values) was used in the simulation. The three operating scenarios examined show that the annual energy consumption and the number of operating hours of the chiller can be reduced by using the buffer tank with the right strategy. In the examined scenarios, a 30% energy improvement was achieved. The possibility of using a buffer tank is significantly limited by the fact that the heat exchangers were sized for low forward water temperatures. By re-sizing the heat exchangers, the utilization of the buffer tank could be considerably improved in conditions close to peak heat load.
Intelligent Probability Estimation of Quenches Caused by Weak Points in High-Temperature Superconducting Tapes
Authors: Sadeghi Alireza , Xu Zhihui , Song Wenjuan , Yazdani-Asrami Mohammad
Published: December 2022

Fluctuations in the critical current along the length of high-temperature superconducting (HTS) tapes manufactured in the form of coated conductors is a common manufacturing phenomenon. These fluctuations originate in the generation of weak points through the length of HTS tapes that may cause quenching later. By means of the propagation of quenches in HTS tapes, the reliability, stability, and the performance of the device and the system that contain HTS tapes could be seriously degraded. In this study, an artificial intelligence technique based on artificial neural networks (ANN) was proposed to estimate the probability of quenches in HTS tapes caused by weak points. For this purpose, six different HTS tapes were considered with different widths, total thicknesses, and thicknesses of sub-layers. Then, for each one of these tapes, different operating conditions were considered, where the operating temperature changed from 40 K to 80 K, in 1 K steps. Under each operating temperature, different operating currents were considered from 50% to 100% of tape critical current. All of these resulted in more than 5000 different data points. Then, for each of these data points, analytical modelling was performed to provide initial inputs and outputs for the ANN model. It should be noted that the performed simulations were conducted based on an analytical method that was experimentally validated in the literature. After that, a sensitivity analysis was conducted to select the hyperparameters and structure of the ANN-based model. The last step was to take advantage of the trained model, as a function in the MATLAB software package to estimate the probability of quenches in different case studies. The significant feature of the proposed model is the capability for estimating the probability of quenches under different operating temperatures and currents for different types of HTS tapes.
On the Simulations of Thermal Liquid Foams Using Lattice Boltzmann Method
Authors: Mobarak Mohammad , Gatternig Bernhard , Delgado Antonio
Published: December 2022

Liquid foams exist in a wide variety of chemical and industrial processes, and they can contaminate the end-product and cause time and economical losses. Understanding and simulating foam is not a straightforward task, due to the highly dispersed time and length scales where the physical phenomena occur. Surfactants’ or proteins’ length scales are far beyond the capability of macroscopic and even mesoscopic numerical fluid solvers, yet the macroscales are still required to be resolved. Meanwhile, the lattice Boltzmann method (LBM) has gained much attention and success as a mesoscopic approach which can deal with complex multiphase multicomponent systems. The aim of this study is to implement LBM to simulate liquid foams while considering the accompanying thermal effects. A coupled multiphase multicomponent thermal flow model and its selected add-ons from the literature are tuned and explained, limitations and future suggestions are fairly discussed. Validations and a final study case are shown as an example for the proposed model and its applicability in thermal liquid foams. Finally, a delicate treatment to back couple the effect of temperature on the surface tension is proposed, hence considering one aspect of the Marangoni effect. Initial results show promising behavior, which can be material for future investigations.
Distribution System Reconfiguration with Soft Open Point for Power Loss Reduction in Distribution Systems Based on Hybrid Water Cycle Algorithm
Authors: Alwash Shamam , Ibrahim Sarmad , Abed Azher M.
Published: December 2022

In this paper, the role of soft open point (SOP) is investigated with and without system re-configuration (SR) in reducing overall system power losses and improving voltage profile, as well as the effect of increasing the number of SOPs connected to distribution systems under different scenarios using a proposed hybrid water cycle algorithm (HWCA). The HWCA is formulated to enhance the water cycle algorithm (WCA) search performance based on the genetic algorithm (GA) for a complex nonlinear problem with discrete and continuous variables represented in this paper by SOP installation and SR. The WCA is one of the most effective optimization algorithms, however, it may have difficulty striking a balance between exploration and exploitation due to the nature of the proposed nonlinear optimization problem, which mostly causes slow convergence and poor robustness. Consequently, the HWCA proposed in this paper is an efficient solution to improve the balance between exploration and exploitation, which in turn leads to improving the WCA’s overall performance without the possibility of getting trapped in local minima. Several cases are studied and conducted on an IEEE 33-node and the IEEE 69-node to investigate the real benefit gained from using SOPs alone or simultaneously with the SR. Based on the obtained results, the proposed HWCA succeeds in enhancing the performance of the proposed test systems considerably in terms of loss reduction (e.g., 31.1–63.3% for IEEE 33-node and 55.7–82.1% for IEEE 69-node compared to the base case) and voltage profile when compared to the base case while maintaining acceptable voltage magnitudes in most cases. Furthermore, the superiority of the proposed method based on the HWCA is validated when compared with the GA and WCA separately for both test systems. The obtained results show the outperformance of the proposed HWCA in attaining the best optimal solution with the least number of iterations.
Biodegradation Kinetics of Organic Matter in Water from Sludge Dewatering after Autothermal Thermophilic Aerobic Digestion
Authors: Biedka Paweł
Published: December 2022

The study presents the research results on the rejected water generated in dewatering sludge stabilised in Autothermal Thermophilic Aerobic Digestion (ATAD) technology. The research was carried out in three municipal wastewater treatment plants (WWTPs), with a capacity of 1500 to 3260 m3 d−1 and a sludge node capacity of 835 to 2000 kg DM d−1. The mean content of Kjeldahl nitrogen (TKN) in the rejected water samples taken from each object ranged from 485 to 1573 mg N L−1, ammonium nitrogen 318 to 736 mg N L−1, and the average concentration of total phosphorus ranged from 96 to 281 mg P L−1. The average content of organic matter expressed as five-day biological oxygen demand (BOD5) ranged from 205 to 730 mg O2 L−1, while chemical oxygen demand (COD) ranged from 767 to 4884 mg O2 L−1. The study determined the kinetics of the biochemical decomposition of organic matter, assuming that it follows the first-order equation. The average reaction rate constant k in subsequent treatment plants was estimated at 0.424, 0.513 and 0.782 d−1. The R2 coefficient determining the model’s adjustment to empirical values was not lower than 0.952. The organic matter biodegradability index average values ranged from 0.17 to 0.26.
TOC/Conductivity: Surrogate Measurements Potentially Guiding Greater Utilization of Treated Produced Water
Authors: Hildenbrand Zacariah L. , Sanchez-Rosario Ramon , Klima Alexis , Liden Tiffany , Schug Kevin A.
Published: December 2022

Hydraulic fracturing utilizes pressurized liquid typically consisting of water, proppants, and a multitude of chemical additives, in order to fracture petroliferous strata to extract natural gas and oil. In this process, a vast amount of wastewater is produced. This water is heavily contaminated, which renders it unusable outside of direct reuse, without extensive treatment being performed. Typically, various sophisticated analytical techniques are involved in the characterization of both waste and treated waters, increasing the cost and the complexity of the management efforts. The article discusses the constituents found in oilfield wastewater, the methods used to identify and quantify these constituents, and the present management methods. Additionally, we introduce total organic carbon and conductivity analyses as surrogate measurements of overall water quality. Total organic carbon and conductivity are established bulk measurements, which can be used to facilitate rapid decisions regarding the treatment and greater utilization of flowback and produced oilfield wastes. The application of the proposed surrogates could be used to streamline the current myriad of complex and expensive measurements. This would improve operational efficiency with respect to wastewater management in the energy sector.
Effect of Eccentric Tension on the Response of Wrinkle Defects in Carbon Fiber-Reinforced Composite Laminates
Authors: Ma Li , Ying Kaidi , Wen Ange , Guo Jing , Zheng Jinyang
Published: December 2022

Composite pressure vessels (CPVs) have become the main equipment for hydrogen storage; however, the effect of defect in the laminates of CPVs is difficult to detect. In this paper, composite specimens containing wrinkle defects were investigated, and a heterogeneity model of a wrinkle defect is proposed. A three-dimensional finite element code was developed to predict the behavior of carbon fiber-reinforced composite laminates with wrinkle defects. The effect of the geometric asymmetry of clamping was distinguished from the whole response. It was found that wrinkle defects are sensitive to tension but completely insensitive to torsion and that the distortion of out-of-plane displacement is strongly dependent upon wrinkle defects. An optical–mechanical method based on fringe projection was presented to measure the response of wrinkle defects, which shows an outstanding performance on wrinkle location and deformation visualization.
An Experimental and Numerical Study on Charged 21700 Lithium-Ion Battery Cells under Dynamic and High Mechanical Loads
Authors: Bulla Marian , Schmandt Christopher , Kolling Stefan , Kisters Thomas , Sahraei Elham
Published: December 2022

The need for higher capacity battery cells has increased significantly during the past years. Therefore, the subject of this study is to investigate the behavior of high performance 21700 Lithium-Ion cylindric battery cells under several abuse conditions, represented by high mechanical loads with different velocities and states of charge (SoC), and to develop a finite element analysis (FEA) model, using the OpenRadioss’ explicit solver capabilities. The present study is focused on the investigation of the behavior of these cells under high mechanical loads with different loading velocities and different states of charge. The aim of the study is to provide a tool to predict the point of an internal short circuit in FEA, with a very good approximation. Experiments were completed using a hydraulic flat-compression test, set up at four different states of charge, 40%, 60%, 80% and 100%, and three different loading velocities of 10 mms−1, 100 mms−1 and 1000 mms−1. A homogenized FEA model is developed to predict the internal damage of the separator, which can lead to a short circuit with a possible thermal runaway under abusive load conditions. The present model, in combination with well identified material and fracture parameters, succeeded in the prediction of the mechanical behavior at various states of charge and mechanical loading conditions; it can also be used for further crashworthiness analysis within a full-car FEA model. This accurate cell model will be the first building block to optimize the protective structures of batteries in electric vehicles, and reduce their weight through a deeper understanding of their overall behavior during the different crash cases.
Social, Economic, and Environmental Effects of Electricity and Heat Generation in Yenisei Siberia: Is there an Alternative to Coal?
Authors: Syrtsova Ekaterina , Pyzhev Anton , Zander Evgeniya
Published: December 2022

The energy sector is one of the most important pollutants in the atmosphere and causes significant emissions of greenhouse gases. In Russia, coal is the main contributor to the fossil fuel consumption of thermal power plants and boilers, thus affecting atmospheric air pollution by releasing particulate matter and nitrogen oxides, which are strongly associated with a negative impact on human health. This problem is especially acute for the resource regions of Yenisei, Siberia, a 2.5+ mln sq km macro-region in the very heart of Russia. In this paper, we analyze the impact of the structure of electricity and heat generation on emissions of pollutants and climate-active gases in Yenisei, Siberia, and give an overview of their social, ecological, and economic effects. More than 75% of electricity in Yenisei, Siberia, is produced by hydroelectric power plants that do not pollute the atmosphere. The rest of the electricity is generated in the cogeneration mode by thermal power plants, which are cores of the heat supply designs of cities. The share of individual coal-powered heat sources is still high. A detailed analysis of existing equipment and technologies at existing thermal power plants is needed to select options for their modernization to reduce emissions while keeping coal in use. Our calculations for the biggest cities of Krasnoyarsk Krai show that investments in the transition to heating with pellets will require RUB 184.7 million for Nazarovo and RUB 313.9 million for Kansk. At the same time, switching to electric heating is more than twice as expensive: RUB 498.6 million for Nazarovo and RUB 847.5 million for Kansk. The additional costs will range from RUB 21 to RUB 45.4 thousand per household per year for the pellet variant and from RUB 56.8 to RUB 122.5 thousand per year for electric heating, which could triple the annual heating costs. Thus, these options are unlikely to be implemented without direct state support. We argue that creating an attractive living environment in Yenisei, Siberia, must begin with intensive public investment in mitigating the environmental externalities caused by coal emissions.
Mixed-Integer Distributed Ant Colony Optimization of Dump Load Allocation with Improved Islanded Microgrid Load Flow
Authors: Kreishan Maen Z. , Zobaa Ahmed F.
Published: December 2022

Dump load (DL) utilization at low demand hours in highly penetrated islanded microgrid is of great importance to offer voltage and frequency regulation. Additionally, load flow (LF) convergence is vital to optimize the working states of the DL allocation problem. Hence, more analysis is necessary to highlight the significance of DL in power regulation while observing the influence of LF on solution accuracy. This article proposes two LF techniques derived from backward/forward sweep (BFS), viz., general BFS (GBFS) and improved special BFS (SBFS-II). The latter is based on global voltage shared between generating units, while the former has a more general approach by considering generating bus’s local voltage. The optimal sizing and sitting of DL with optimum droop sets are determined using the mixed-integer distributed ant colony optimization (MIDACO) with the two new LF methods. The optimization problem was formulated to minimize voltage and frequency deviations as well as power losses. The problem was validated on IEEE 69- and 118-bus systems and compared with established metaheuristics. Results show that DL allocation using MIDACO with SBFS-II and GBFS has improved the solution speed and accuracy, respectively. Furthermore, the enhanced voltage and frequency results highlight DL as an efficient power management solution.