bluuebunny/crossref_metadata_2025 huggingface dataset:
Fossil Fuel and Biofuel Boilers in Ukraine: Trends of Changes in Levelized Cost of Heat
Authors: Stanytsina Valentyna , Artemchuk Volodymyr , Bogoslavska Olga , Zaporozhets Artur , Kalinichenko Antonina , Stebila Jan , Havrysh Valerii , Suszanowicz Dariusz
Published: October 2022

An increase in the share of renewables in heat supply systems is a promising direction to reach sustainable development goals and decarbonization. Decision makers should consider various factors, including energy market prices, the availability of biofuels, boiler and auxiliary equipment costs, logistic costs, and the taxation system. In the European Union, the energy crisis causes a rapid increase in fossil fuel prices. Moreover, the use of fossil fuels results in greenhouse gas emissions, which threatens the achievement of sustainable development goals. We studied the influence of the delivery cost and the value of environmental tax rates on the levelized cost of heat. Low-capacity boilers (up to 1 MW) and different fossil and renewable fuels were analyzed. An analysis was carried out on the example of Ukraine. The European trends were factored in. The obtained results showed that biofuel boilers had lower levelized costs of heat than fossil fuel boilers. Delivery costs and environmental taxes have a significant impact on heat energy costs.
An AI-Layered with Multi-Agent Systems Architecture for Prognostics Health Management of Smart Transformers: A Novel Approach for Smart Grid-Ready Energy Management Systems
Authors: Laayati Oussama , El Hadraoui Hicham , El Magharaoui Adila , El-Bazi Nabil , Bouzi Mostafa , Chebak Ahmed , Guerrero Josep M.
Published: October 2022

After the massive integration of distributed energy resources, energy storage systems and the charging stations of electric vehicles, it has become very difficult to implement an efficient grid energy management system regarding the unmanageable behavior of the power flow within the grid, which can cause many critical problems in different grid stages, typically in the substations, such as failures, blackouts, and power transformer explosions. However, the current digital transition toward Energy 4.0 in Smart Grids allows the integration of smart solutions to substations by integrating smart sensors and implementing new control and monitoring techniques. This paper is proposing a hybrid artificial intelligence multilayer for power transformers, integrating different diagnostic algorithms, Health Index, and life-loss estimation approaches. After gathering different datasets, this paper presents an exhaustive algorithm comparative study to select the best fit models. This developed architecture for prognostic (PHM) health management is a hybrid interaction between evolutionary support vector machine, random forest, k-nearest neighbor, and linear regression-based models connected to an online monitoring system of the power transformer; these interactions are calculating the important key performance indicators which are related to alarms and a smart energy management system that gives decisions on the load management, the power factor control, and the maintenance schedule planning.
Nitrogen Migration and Conversion in Chars from Co-Pyrolysis of Lignocellulose Derived Pyrolysis Model Compounds and Urea-Formaldehyde Resin Adhesive
Authors: Guo Mengyao , Yu Shu , Zhang Shu , Wei Juntao , Gao Wenran , Bao Weina , Shi Lei , Zhang Hong , Xu Deliang
Published: October 2022

In thermal conversion utilization, nitrogen-rich biomass such as waste wood-based panels will release a large amount of NOx into the atmosphere, causing serious harm to the surroundings. By means of co-pyrolysis, N in waste wood-based panels can be fixed in chars instead of discharging into the atmosphere in the form of volatile matter, which can reduce NOx emission and lay a foundation for the preparation of nitrogen-rich carbon materials with high added value. As the most commonly used adhesive in the production of wood-based panels, urea-formaldehyde resin adhesive (UF) is the main nitrogen source in waste wood-based panels. Therefore, the purpose of this paper is to explore the effects of glucose, ethyl maltol and 2,5-dimethyl-4-hydroxy-3(2H)-furanone (DMHF) on nitrogen migration and conversion during UF pyrolysis by adjusting the different proportions of model compounds and UF. Thermogravimetric analysis showed that ethyl maltol and DMHF had lower thermal stability and the pyrolysis process was concentrated in the range of 90–168 °C, which does not coincide with the mass loss temperature of UF. UF can promote the pyrolysis of these three model compounds at the initial stage to some extent. The elemental analysis showed that the N retention in co-pyrolysis chars increased in varying degrees with the increase of the addition of model compounds; the nitrogen retention in chars of glucose-UF, ethyl maltol-UF and DMHF-UF increased by 28.47%, 3.48% and 16.45% with the increase of the model compound content from 50% to 90%, respectively. The XPS results showed that the relative content of N-6 in chars increased with the increase of ethyl maltol content, and the relative content of N-5 in chars increased with the increased addition of DMHF. Glucose had little effect on the distribution of N-functional groups in chars.
Application of the Analysis of Variance (ANOVA) in the Interpretation of Power Transformer Faults
Authors: Thango Bonginkosi A.
Published: October 2022

Electrical power transformers are the most exorbitant and tactically prominent components of the South African electrical power grid. In contrast, they are burdened by internal winding faults predominantly on account of insulation system failure. It is essential that these faults must be swiftly and precisely uncovered and suitable measures should be adopted to separate the faulty unit from the entire system. The frequency response analysis (FRA) is a technique for tracking a transformer’s mechanical integrity. Nevertheless, classifying the category of the fault and its gravity by benchmarking measured FRA responses is still backbreaking and for the most part, anchored in personnel proficiency. This work presents a quantum leap to normalize the FRA interpretation procedure by suggesting an interpretation code criteria based on an empirical survey of transformers ranging from 315 kVA to 40 MVA. The study then proposes an analysis of variance (ANOVA) based interpretation tool for diagnosing the statistical significance of FRA fingerprint and measured profiles. The latter cannot be relied upon by an expert or by the naked eye. Additionally, descriptive FRA frequency sub-region data statistics are proposed to evaluate the shift in both the magnitude and measuring frequency characteristics to formulate the recommended interpretation code criteria. To corroborate the code criteria by incorporating ANOVA and descriptive statistics, the study presents various case studies with unknown FRA profiles for fault diagnosis. The results constitute proof of the reliability of the proposed code criteria and a proposed hybrid of ANOVA and descriptive statistics.
Reliability Analysis and Economic Evaluation of Thermal Reflective Insulators
Authors: Borelli Davide , Cavalletti Alessandro , Cavalletti Paolo , Tagliafico Luca Antonio
Published: October 2022

High-performance thermal insulators allow a dramatic reduction in the thickness of coatings, thanks to their low thermal conductivity. This study provides an overview about thermal insulation materials, with regards to heat reflective insulators in particular. Then, the numerical investigation method adopted to compute the thermal resistance associated with reflective insulators is introduced. This method has been used in turn to check the accuracy of the declared, measured performance of different, heat-reflective materials on the market. Many manufacturers of reflective insulators were available to provide information and a good agreement between the declared and expected thermal resistance has been found. The choice of a non-experimental approach is meant to check the validity of an already performed test on a reflective insulator using a predictive approach instead of standard, additional testing. Then, the insulation of five typical walls at three different sites in Italy has been simulated, showing that most of heat-reflective materials cannot achieve the maximum required transmittance. Interstitial condensation is likely to occur in specific cases, also because of the aluminum layers inside. The economic analyses showed comparable costs for both heat reflective and traditional insulators, and their cost effectiveness needs to be evaluated case by case.
Energy and Exergy Analysis of Vapor Compression Refrigeration System with Low-GWP Refrigerants
Authors: Aized Tauseef , Rashid Muhammad , Riaz Fahid , Hamza Ameer , Nabi Hafiz Zahid , Sultan Muhammad , Ashraf Waqar Muhammad , Krzywanski Jaroslaw
Published: October 2022

In this paper, a first- and second-law analysis of vapor compression refrigeration is presented to estimate and propose the replacement of R134 with working fluids having less global warming potential (GWP) and less exergy destruction and irreversibilities. Six different refrigerants were studied, namely, R717, R1234yf, R290, R134a, R600a, and R152a. A thermodynamic model was designed on Engineering Equation Solver (EES) software, and performance parameters were calculated. The model was deployed on all six refrigerants, while the used output parameters of performance were cooling capacity, coefficient of performance, discharge temperature, total exergy destruction, relative exergy destruction rates of different components, second-law efficiency, and efficiency defect of each component. The performance parameters were estimated at different speeds of the compressor (1000, 2000, and 3000 rpm) and fixed condenser and evaporator temperatures of 50 °C and 5 °C, respectively. The isentropic efficiency of the compressor was the same as the volumetric efficiency, and it was taken as 75%, 65%, and 55% at the compressor speeds of 1000 rpm, 2000 rpm, and 3000 rpm, respectively. A comparison of the performance parameters was presented by importing the results in MATLAB. It was found that the compressor had the highest exergy destruction compared to the other components. It was found that R152 was the refrigerant with zero ozone depletion potential (ODP) and a GWP value of 140 with less exergy destruction and irreversibilities. Moreover, it was easy to use R152a with good thermodynamic characteristics. It is estimated that R152a is a suitable replacement for R134a, as it can be used with few modifications.
Eliciting Stakeholders’ Requirements for Future Energy Systems: A Case Study of Heat Decarbonisation in the UK
Authors: Chiu Lai Fong , Lowe Robert John
Published: October 2022

It is a truism that whole energy system models underpin the development of policies for energy system decarbonisation. However, recent reviews have thrown doubt on the appropriateness of such models for addressing the multiple goals for future energy systems, in the face of emergent real-world complexity and the evolution of stakeholder’s priorities. Without an understanding of the changing priorities of policy makers and expectations of stakeholders for future systems, system objectives and constraints are likely to be ill-defined, and there is a risk that models may be inadvertently instrumentalised. Adopting a system architecture perspective, the authors have undertaken a three-year programme of research to explore strategies for decarbonising heat in the UK, with interaction with and elicitation of needs from stakeholders at its heart. This paper presents the procedure, methods, and results of an exercise in which experts from stakeholder organisations across the energy system were interviewed. Analysis of interview data reveals two broad approaches to heat decarbonisation which can be defined as either adaptive or transformative. Specific insights gained from these interviews enabled our modelling teams to refocus their work for exploration with a wider circle of stakeholders. Results suggests that this iterative approach to formalising model-policy interaction could improve the transparency and legitimacy of modelling and enhance its impact on policy making.
Stationary Gas Dynamics and Heat Transfer of Turbulent Flows in Straight Pipes at Different Turbulence Intensity
Authors: Plotnikov Leonid , Grigoriev Nikita , Osipov Leonid , Slednev Vladimir , Shurupov Vladislav
Published: October 2022

The gas-dynamic and heat-exchange behaviours of air flows in gas-dynamic systems have a significant impact on the efficiency and environmental performance of most technical equipment (heat engines, power plants, heat exchangers, etc.). Therefore, it is a relevant task to obtain reliable experimental data and physical laws on the influence of cross-sectional shape and initial turbulence intensity on gas dynamics and the level of heat transfer. In this study, data were experimentally obtained on the instantaneous values of the local velocity and local heat transfer coefficients of stationary air flows in straight pipes with circular, square, and triangular cross-sections at different initial values of the turbulence intensity. The measurements were carried out with a constant temperature hot-wire anemometer, thermocouples, and pressure sensors. Based on the research results, data on the turbulence intensity and averaged local heat transfer along the length of pipes with different cross-sections were summarised. It has been established that turbulence intensity in a square pipe is up to 40% higher than in a round channel; in a triangular channel, on the contrary, it is up to 28% lower. After the air flow’s initial turbulence, the relaxation of the flow in square and triangular pipes occurs faster than in a round channel. It is found that the initial intensity of turbulence leads to an increase in the averaged local heat transfer, which is typical of all investigated pipe configurations and initial conditions.
A Spiking Neural Network Based Wind Power Forecasting Model for Neuromorphic Devices
Authors: González Sopeña Juan Manuel , Pakrashi Vikram , Ghosh Bidisha
Published: October 2022

Many authors have reported the use of deep learning techniques to model wind power forecasts. For shorter-term prediction horizons, the training and deployment of such models is hindered by their computational cost. Neuromorphic computing provides a new paradigm to overcome this barrier through the development of devices suited for applications where latency and low-energy consumption play a key role, as is the case in real-time short-term wind power forecasting. The use of biologically inspired algorithms adapted to the architecture of neuromorphic devices, such as spiking neural networks, is essential to maximize their potential. In this paper, we propose a short-term wind power forecasting model based on spiking neural networks adapted to the computational abilities of Loihi, a neuromorphic device developed by Intel. A case study is presented with real wind power generation data from Ireland to evaluate the ability of the proposed approach, reaching a normalised mean absolute error of 2.84 percent for one-step-ahead wind power forecasts. The study illustrates the plausibility of the development of neuromorphic devices aligned with the specific demands of the wind energy sector.
Priorities in Bioeconomy Strategies: A Systematic Literature Review
Authors: Papadopoulou Christina-Ioanna , Loizou Efstratios , Chatzitheodoridis Fotios
Published: October 2022

Bioeconomy is an emerging concept and no commonly accepted definition has been given so far. Bioeconomy strategies attempt to cover every aspect of this emerging concept from a different perspective, depending on the country, region, or organisation issuing them. For these reasons, each strategy has its own priority fields depending on the economic, geomorphological, social, ecological, and technological conditions of each country. In this review, an attempt is made to study the priority fields of bioeconomy strategies through a systematic review of the literature. PRISMA analysis was used to review the literature on the priority fields of bioeconomy strategies. The review examined the issue in the rich academic literature of two databases, Scopus and AgEcon. Using a repeatable search process to identify relevant studies in the literature, only 68 publications met the eligibility criteria that were included in the review. The results show that there are trends in the priority fields of bioeconomy strategies in the years 2013–2022. Moreover, the economic and technological development of the respective countries foreshadows their priorities. A successful transition to a bioeconomic model requires the participation of society as a whole, because a sustainable society as a whole requires sustainable and environmentally friendly solutions. The study concludes that governance with global coordination and stakeholder training is needed for successful implementation of bioeconomy strategies.
Measuring and Predicting the In-Ground Temperature Profile for Geothermal Energy Systems in the Desert of Arid Regions
Authors: Abdel-Ghany Ahmed M. , Al-Helal Ibrahim M. , Alsadon Abdullah , Ibrahim Abdullah , Shady Mohamed
Published: October 2022

Instead of fossil fuels, clean renewable energy resources are being used to meet space heating and cooling needs, to reduce global warming and air pollution worldwide. In the desert of the Arabian Peninsula, extensive solar irradiance and drastic variations in air temperatures (daily and/or seasonally) are common; thus, geothermal energy resources are a promising solution that is nearly independent of weather fluctuations. Due to a lack of information about in-ground temperature profiles in these regions, the use of geothermal energy resources for domestic applications is very limited. Therefore, this study aimed to measure the in-ground temperature (Tg) up to 3.5 m in depth for one year. Due to the difficulty of digging in the ground (i.e., gravelly sand; rocky, dry soil), numerical equations were adopted and used to simulate the in-ground temperature (Tg) for a depth > 3 m. These equations were validated by comparing the measured and simulated values of Tg for depths ≤ 3 m under extreme weather conditions. The validation yielded a mean absolute error (EMA) of ≤ 1.2 °C and a root mean square error (ERMS) of ≤ 1.42 °C. The measurements showed that at 3 m depth, the in-ground temperature was 32 °C in summer and 29 °C in winter. The simulation showed that values of Tg increased with depth in winter and decreased in summer and became constant as 30 °C at 13 m depth throughout the year (i.e., the undisturbed ground temperature (UGT)). This temperature would provide considerable heating and cooling capacity if an earth-to-air heat exchanger were implemented in arid regions where ambient temperatures exceed 47 °C on summer days and drop below 10 °C on winter nights. The theoretical prediction of Tg using the proposed equations is a useful tool for designers who use geothermal effects for indoor space cooling and heating in the desert of arid regions.
Toward Circular Supply Chains for Flat Glass: Challenges of Transforming to More Energy-Efficient Solutions
Authors: Forslund Helena , Björklund Maria
Published: October 2022

Even if flat glass is 100% recyclable, only 1% is currently handled in circular or closed-loop supply chains (CLSCs) in Sweden. This has an unnecessary environmental impact, indicating not only the potential for more energy-efficient solutions but also the challenges that need to be understood. The purpose of this article is to increase the knowledge of challenges in applying different types of more or less energy-efficient CLSCs for flat glass. Through a literature review, an overview of CLSC types, together with challenges in different areas, is provided. The CLSC types and challenges are corroborated in a flat glass context, including focus groups and expert interviews. Four CLSC types—two CLSCs based on remanufacturing, one on reconditioning, and one on reuse—are identified. A framework provides implications for both literature and practice. It contains 19 challenges—such as lack of large-scale actors, lack of material knowledge, lack of knowledge of customers’ behavior, lack of promotion of flat glass CLSCs at many levels in society—in terms of both legislation and cost—and lack of business models—structured in four areas—material characteristics and quality, inefficient logistics systems, demand and supply, and means of control and costs. The least-applied CLSC includes almost every challenge and has a large upscaling potential, indicating the necessity of mitigating challenges. The framework identifies challenges not included in earlier flat glass literature. CLSC types are related to different challenge set-ups and different energy efficiency potentials, leading to expanded CLSC knowledge. One additional implication is that practitioners can identify potential CLSC types and understand their challenges from the perspective of several stakeholders. The participatory research methodology fills a methodological research gap within CLSC literature and provides important insights.
Hierarchical Distributed Coordinated Control for Battery Energy Storage Systems Participating in Frequency Regulation
Authors: Yu Bingqing , Lv Qingquan , Zhang Zhenzhen , Dong Haiying
Published: October 2022

At present, battery energy storage systems (BESS) have become an important resource for improving the frequency control performance of power grids under the situation of high penetration rates of new energy. Aiming at the problem that the existing control strategy is not sufficient for allocating the frequency regulation power instructions, a hierarchical distributed coordinated control strategy for BESS to participate in the automatic generation control (AGC) of a regional power grid is proposed. At the upper layer, the state of charge (SOC) of BESS and the technical characteristics of different frequency regulation power sources are comprehensively considered to complete the coordinated distribution of frequency regulation commands between BESS and traditional generators; at the lower layer, for the purpose of optimizing the economic operation of the regional power grid, the distributed consistency algorithm is used to control the distributed BESS in order to realize the fine management of power output of BESS. The simulation results indicate that this control strategy can give full play to the technical characteristics of different frequency power sources and improve the frequency regulation of the power grid. The excessive power consumption of BESS is successfully avoided, and the continuous operation of BESS is realized.
Experimental and Numerical Study on the Elimination of Severe Slugging by Riser Outlet Choking
Authors: Li Nailiang , Chen Bin , Du Xueping , Han Dongtai
Published: October 2022

Severe slugging is an unstable multiphase flow pattern occurs in a pipeline riser with low gas and liquid flowrates. It is highly undesired in practical operation because of the pressure and mass flow oscillations induced. Riser outlet choking has shown effectiveness in eliminating or reducing the severity of the slugging. This work presents an experimental and numerical study on the elimination of severe riser-induced slug by means of riser outlet choking. The test loop consists of a horizontal pipeline with 50 mm i.d. and 15 m in length, followed by a downward inclined section and a vertical riser of 2 m. It was found that by choking the flow at riser outlet, flow pattern in the riser changes from severe slugging first into slug flow and then into bubbly flow. The recognition of the flow regimes was basically according to the trends of the riser base pressure. The flow patterns were characterized in terms of pressure at riser base, as well as liquid holdup at riser top. A numerical model was developed accordingly using OLGA to investigate the dynamic behavior in the process of riser outlet choking.
A Review on the Molecular Modeling of Argyrodite Electrolytes for All-Solid-State Lithium Batteries
Authors: Ayoola Oluwasegun M. , Buldum Alper , Farhad Siamak , Ojo Sammy A.
Published: October 2022

Solid-state argyrodite electrolytes are promising candidate materials to produce safe all-solid-state lithium batteries (ASSLBs) due to their high ionic conductivity. These batteries can be used to power electric vehicles and portable consumer electronics which need high power density. Atomic-scale modeling with ab initio calculations became an invaluable tool to better understand the intrinsic properties and stability of these materials. It is also used to create new structures to tailor their properties. This review article presents some of the recent theoretical investigations based on atomic-scale modeling to study argyrodite electrolytes for ASSLBs. A comparison of the effectiveness of argyrodite materials used for ASSLBs and the underlying advantages and disadvantages of the argyrodite materials are also presented in this article.
Planning, Operation, and Design of Market-Based Virtual Power Plant Considering Uncertainty
Authors: Ullah Zahid , Arshad  , Hassanin Hany , Cugley James , Alawi Mohammed Al
Published: October 2022

The power systems of today seem inseparable from clean energy sources such as wind turbines (WTs) and photovoltaics (PVs). However, due to their uncertain nature, operational challenges are expected when WT and PV energy is added to the electricity network. It is necessary to introduce new technologies to compensate for the intermittent nature of renewable energy sources (RESs). Therefore, rationally implementing a demand response (DR) program with energy storage systems (ESSs) in a virtual power plant (VPP) environment is recommended as a way forward to minimize the volatile nature of RESs and improve power system reliability. Our proposed approach aims to maximize social welfare (SW) (i.e., maximization of consumer benefits while minimizing energy costs). Our method assesses the impact of the DR program on SW maximization. Two scenarios are examined, one with and one without a DR program. Stochastic programming theory is used to address the optimization problem. The uncertain behavior of WTs, PVs, and load demand is modeled using a scenario-based approach. The correctness of the proposed approach is demonstrated on a 16-bus UK generic distribution system. Our results show that SW and active power dispatch capacity of WT, PV, and ESS are fairly increased using the proposed approach.
Power System Division—Certain Issues Associated with Shaping Commutation Strategies in Power Substations
Authors: Skuza Aleksandra , Ziemianek Stanisław , Suproniuk Marek
Published: October 2022

The article addresses some of the problems associated with the process of shaping commutation strategies in power substations. The issues of modelling the commutation processes of switching devices within a substation and a sample system, as well as mathematical models for creating switching steps within a substation were reviewed. Examples of optimisation methods to be possibly applied in the creation of algorithms for the division of a system into subsystems as a result of a threat of losing its integrity were discussed. The aim of this article is to present the results of preliminary research on the topic described. Its content includes the main methods to achieve the final research results. It is therefore an article marking the path of the research work carried out. The article shows that it is possible, with simple substation measures, to adapt a large power system in such a way that eventual subdivision into sub-systems can be realised by system operation planners before uncontrolled division as a result of a fault occurs. To illustrate the intent of the pathway, a New England test system modified version was used, using an example where the binodalisation process and one possible division of this system into subsystems was explained.
Review on the Hydrogen Dispersion and the Burning Behavior of Fuel Cell Electric Vehicles
Authors: Lan Hao , Wang Guiyun , Zhao Kun , He Yuntang , Zheng Tianlei
Published: October 2022

The development of a hydrogen energy-based society is becoming the solution for more and more countries. Fuel cell electric vehicles are the best carriers for developing a hydrogen energy-based society. The current research on hydrogen leakage and the diffusion of fuel cell electric vehicles has been sufficient. However, the study of hydrogen safety has not reduced the safety concerns for society and government management departments, concerning the large-scale promotion of fuel cell electric vehicles. Hydrogen safety is both a technical and psychological issue. This paper aims to provide a comprehensive overview of fuel cell electric vehicles’ hydrogen dispersion and the burning behavior and introduce the relevant work of international standardization and global technical regulations. The CFD simulations in tunnels, underground car parks, and multistory car parks show that the hydrogen escape performance is excellent. At the same time, the research verifies that the flow, the direction of leakage, and the vehicle itself are the most critical factors affecting hydrogen distribution. The impact of the leakage location and leakage pore size is much smaller. The relevant studies also show that the risk is still controllable even if the hydrogen leakage rate is increased ten times the limit of GTR 13 to 1000 NL/min and then ignited. Multi-vehicle combustion tests of fuel cell electric vehicles showed that adjacent vehicles were not ignited by the hydrogen. This shows that as long as the appropriate measures are taken, the risk of a hydrogen leak or the combustion of fuel cell electric vehicles is controllable. The introduction of relevant standards and regulations also indirectly proves this point. This paper will provide product design guidelines for R&D personnel, offer the latest knowledge and guidance to the regulatory agencies, and increase the public’s acceptance of fuel cell electric vehicles.
Boiling Heat Transfer Enhancement on Biphilic Surfaces
Authors: Chinnov Evgeny A. , Khmel Sergey Ya. , Vladimirov Victor Yu. , Safonov Aleksey I. , Semionov Vitaliy V. , Emelyanenko Kirill A. , Emelyanenko Alexandre M. , Boinovich Ludmila B.
Published: October 2022

Flat surfaces with different patterns of hydrophobic spots were employed for experimental investigation of boiling heat transfer. In one case, hydrophobic spots were created on a smooth copper surface and on a surface coated with arrays of micrococoons from silicon oxide nanowires by vapor deposition of a fluoropolymer. In the second case, a hydrophobic coating was deposited on heater surfaces with cavity microstructures formed by laser ablation and chemisorption of fluorinated methoxysilane. Water under saturation conditions at atmospheric pressure was used as the working liquid. The temperature of the heating surface was varied from 100 to 125 °C, and the maximum value of the heat flux was 160 W/cm2. Boiling heat transfer on the test biphilic surfaces was significantly (up to 600%) higher than on non-biphilic surfaces. Surface texture, the shape of hydrophobic regions, and the method of their creation tested in this study did not show a significant effect on heat transfer. The boiling heat transfer rate was found to depend on the size of hydrophobic spots, the distance between them, and hence the number of spots. The highest heat transfer efficiency was detected for the surface with the largest number of hydrophobic spots. After long-term experiments (up to 3 years), the heat transfer coefficient on the obtained surfaces remained higher than on the smooth copper surface. Biphilic surfaces with arrays of cavities formed by laser ablation turned out to be the most stable during prolonged contact with boiling water.
Improved Fixed-Frequency SOGI Based Single-Phase PLL
Authors: Stojic Djordje , Tarczewski Tomasz , Niewiara Lukasz J. , Grzesiak Lech M.
Published: October 2022

In this paper, an improved single-phase second order generalized integrator (SOGI) fixed-frequency phase-locked loop (FFPLL) is presented. The proposed improvement comprises the modification of the PLL input signal estimated phase angle correction factor, which is in this paper calculated and implemented with the exactly accurate value, while in the existing literature the approximated correction value is employed. Also, in this paper, the FFPLL with DC offset is presented, together with the corresponding estimated angle correction technique. Furthermore, the PLL with the positive sequence separation is outlined, based on the new FFPLL structure. The proposed technique is analyzed and verified by simulation and experimental runs, which proved the accuracy and efficiency of the proposed PLL technique. Furthermore, a corresponding PLL parameter values tuning procedure is presented that illustrates the dynamic performance improvements that SOGI based FFPLL introduces when compared with SOGI based PLL. Consequently, FFPLL combined with the proposed new estimated angle correction factor represents a significant improvement when compared to the conventional SOGI based PLL.
The Disturbance Detection in the Outlet Temperature of a Coal Dust–Air Mixture on the Basis of the Statistical Model
Authors: Łabęda-Grudziak Zofia M.
Published: October 2022

The reliability of a coal mill's operation is strongly connected with optimizing the combustion process. Monitoring the temperature of a dust–air mixture significantly increases the coal mill's operational efficiency and safety. Reliable and accurate information about disturbances can help with optimization actions. The article describes the application of an additive regression model and data mining techniques for the identification of the temperature model of a dust–air mixture at the outlet of a coal mill. This is a new approach to the problem of power unit modeling, which extends the possibilities of multivariate and nonlinear estimation by using the backfitting algorithm with flexible nonparametric smoothing techniques. The designed model was used to construct a disturbance detection system in the position of hot and cold air dampers. In order to achieve the robust properties of the detection systems, statistical measures of the differences between the real and modeled temperature signal of dust–air mixtures were used. The research has been conducted on the basis of the real measuring data registered in the Polish power unit with a capacity of 200 MW. The obtained high-quality model identification confirms the correctness of the presented method. The model is characterized by high sensitivity to any disturbances in the cold and hot air damper position. The results show that the suggested method improves the usability of the statistical modeling, which creates good prospects for future applications of additive models in the issues of diagnosing faults and cyber-attacks in power systems.
A Real-Time Digital Twin and Neural Net Cluster-Based Framework for Faults Identification in Power Converters of Microgrids, Self Organized Map Neural Network
Authors: Lopez Juan R. , de Jesus Camacho Jose , Ponce Pedro , MacCleery Brian , Molina Arturo
Published: October 2022

In developing distribution networks, the deployment of alternative generation sources is heavily motivated by the growing energy demand, as by environmental and political motives. Consequently, microgrids are implemented to coordinate the operation of these energy generation assets. Microgrids are systems that rely on power conversion technologies based on high-frequency switching devices to generate a stable distribution network. However, disrupting scenarios can occur in deployed systems, causing faults at the sub-component and the system level of microgrids where its identification is an economical and technological challenge. This paradigm can be addressed by having a digital twin of the low-level components to monitor and analyze their response and identify faults to take preventive or corrective actions. Nonetheless, accurate execution of digital twins of low-level components in traditional simulation systems is a difficult task to achieve due to the fast dynamics of the power converter devices, leading to inaccurate results and false identification of system faults. Therefore, this work proposes a fault identification framework for low-level components that includes the combination of Real-Time systems with the Digital Twin concept to guarantee the dynamic consistency of the low-level components. The proposed framework includes an offline trained Self Organized Map Neural Network in a hexagonal topology to identify such faults within a Real-Time system. As a case study, the proposed framework is applied to a three-phase two-level inverter connected to its digital model in a Real-Time simulator for open circuit faults identification.
Keynote Review of Latest Advances in Thermoelectric Generation Materials, Devices, and Technologies 2022
Authors: Hendricks Terry , Caillat Thierry , Mori Takao
Published: October 2022

The last decade created tremendous advances in new and unique thermoelectric generation materials, devices, fabrication techniques, and technologies via various global research and development. This article seeks to elucidate and highlight some of these advances to lay foundations for future research work and advances. New advanced methods and demonstrations in TE device and material measurement, materials fabrication and composition advances, and device design and fabrication will be discussed. Other articles in this Special Issue present additional new research into materials fabrication and composition advances, including multi-dimensional additive manufacturing and advanced silicon germanium technologies. This article will discuss the most recent results and findings in thermoelectric system economics, including highlighting and quantifying the interrelationships between thermoelectric (TE) material costs, TE manufacturing costs and most importantly, often times dominating, the heat exchanger costs in overall TE system costs. We now have a methodology for quantifying the competing TE system cost-performance effects and impacts. Recent findings show that heat exchanger costs usually dominate overall TE system cost-performance tradeoffs, and it is extremely difficult to escape this condition in TE system design. In regard to material performance, novel or improved enhancement principles are being effectively implemented. Furthermore, in addition to further advancements in properties and module developments of relatively established champion materials such as skutterudites, several high performance ZT ≈≥ 2 new material systems such as GeTe, Mg3(Sb,Bi)2 have also been relatively recently unearthed and module applications also being considered. These recent advancements will also be covered in this review.
TSO/DSO Coordination for RES Integration: A Systematic Literature Review
Authors: Alazemi Talal , Darwish Mohamed , Radi Mohammed
Published: October 2022

The increasing penetration of large-scale Renewable Energy Sources (RESs) has raised several challenges for power grid operation. Power management solutions supporting the integration of RESs, such as those based on energy storage technologies, are generally costly. Alternatively, promoting a more proactive role of the Distribution System Operator (DSO) to successfully manage RESs’ uncertainty, and take advantage of their flexible resources for the provision of ancillary services, can avoid installing expensive devices in the network and reduce costs. In this line, improved coordination between Transmission System Operators (TSOs) and DSOs is highly desirable. In this paper, the feasibility of solving different aspects of the integration of RESs through an improved TSO/DSO coordination is evaluated. In particular, a Systematic Literature Review (SLR) is conducted to study the most relevant TSO/DSO coordination approaches, exclusively focused on integrating distributed RESs, currently available in the literature. Their main operational, managerial, economic, and computational challenges, advantages, and disadvantages are discussed in detail to identify the most promising research trends and the most concerning research gaps to pave the way for future research toward developing a solid TSO/DSO coordination mechanism for integrating RESs efficiently. The main results of the SLR show a clear trend in implementing decentralized TSO/DSO coordination models since they provide efficient facilitation of RESs’ services, while reducing computational burden and communication complexity and, consequently, reducing operative costs. In addition, while different aspects of the TSO/DSO coordination implementation, such as reactive power and voltage regulation, operational cost minimization, operational planning, and congestion management, have been thoroughly addressed in the literature, further research is needed regarding data exchange mechanisms and RESs’ uncertainty modeling and prediction. In this line, the development of standardized communication solutions, based on the Common Grid Model Exchange Standard (CGMES) of the International Electrotechnical Commission (IEC), has shown promising interoperability results, whereas the use of learning-based approaches to predict RESs’ uncertain behavior and distribution networks’ responses, using only historical data, which relieves the need for access to commercially sensitive and proprietary network data, has also shown itself to be a promising research direction.
Socioeconomic Paradigms and the Perception of System Risks: A Study of Attitudes towards Nuclear Power among Polish Business Students
Authors: Platje Johannes (Joost) , Will Markus , Paradowska Monika , van Dam Ynte K.
Published: October 2022

Due to anticipated energy shortages and the need to achieve climate goals, there is an urgent requirement for transition towards a green, resilient system of energy provision. This transition is hampered because important players in energy markets (governments and oligopolies), while supporting large-scale solutions, avoid or block systemic changes. This rejection of systemic change is strengthened by the dominant social paradigm, which ignores systemic vulnerabilities, treating resources as solutions and the environment as a sink. In its turn, the dominant social paradigm is contested by the new ecological paradigm and by attitudes towards sustainable business practices. Understanding this framework may be relevant for identifying decision-makers’ perception of system risk, and thus for supporting a transition towards a more decentralized and resilient energy supply. In this context, this paper presents an empirical study among Polish students of a business university (N = 393), trying to discover the relationship between the social paradigms, perceptions of environmental resources and sinks, and systemic risk in large-scale energy production (i.e., nuclear power plants). Although the explained variance is limited, results show that various elements of the dominant social paradigm are related to problem denial. Technological optimism and belief in markets are predictors of optimism about resource shortages and neglect of system risk. This optimism is counteracted by political liberalism, and respondent attitudes towards sustainable business practices. Belief in market forces has an ambivalent effect, tempering technological optimism regarding nuclear energy but also political acknowledgement of the limited resources and sink capacities of the environment. Although the influence of the dominant social paradigm on energy transition can be identified, the results may indicate a decline in belief in market forces and liberal democracy, implying a rethinking of the dominant social paradigm may be needed. The existing relationship between these aspects warrants a critical review and discussion of the central role of the dominant paradigm in current management training. The results indicate that a lack of political liberalism and a negative attitude towards sustainable business practices amplify system risks in, e.g., large-scale nuclear energy projects.
Impact of Financial Inclusion on the Efficiency of Carbon Emissions: Evidence from 30 Provinces in China
Authors: Zhang Xu , Sun Huaping , Wang Taohong
Published: October 2022

Carbon emissions have become a serious environmental problem worldwide, with the greenhouse effect and global temperature increase being the main areas of concern. Financial inclusion is a means to increase the welfare of citizens and promote sustainable development. Development of financial inclusion may have a big impact on carbon emissions. This study uses data from 2011 to 2019 to do panel Tobit regression and check the effect of financial inclusion on the efficiency of carbon emissions, which is calculated by the super-efficiency Slacks-Based Measure (SBM) -data envelopment analysis (DEA) method. The results show that financial inclusion decreases the efficiency of carbon emissions. Moreover, financial inclusion could reduce the efficiency of carbon emissions by increasing the proportion of tertiary industries. Moreover, the effect varies in each region. Thus, following these conclusions, we propose several related policy implications. The government should strengthen the supervision of money due to financial inclusion and ensure that the investment should be put into environmental projects. In addition, it needs to pay attention to carbon emissions generated in the process of industrial upgrading. More access to renewable energy is an effective measure to solve the problem of higher carbon dioxide emissions.
Applying Intelligent Multi-Agents to Reduce False Alarms in Wind Turbine Monitoring Systems
Authors: Teixeira Weldon Carlos Elias , Sanz-Bobi Miguel Ángel , Oliveira Roberto Célio Limão de
Published: October 2022

This study proposes a method for improving the capability of a data-driven multi-agent system (MAS) to perform condition monitoring and fault detection in industrial processes. To mitigate the false fault-detection alarms, a co-operation strategy among software agents is proposed because it performs better than the individual agents. Few steps transform this method into a valuable procedure for improving diagnostic certainty. First, a failure mode and effects analysis are performed to select physical monitoring signals of the industrial process that allow agents to collaborate via shared signals. Next, several artificial neural network (ANN) models are generated based on the normal behavior operation conditions of various industrial subsystems equipped with monitoring sensors. Thereafter, the agents use the ANN-based expected behavior models to prevent false alarms by continuously monitoring the measurement samples of physical signals that deviate from normal behavior. Finally, this method is applied to a wind turbine. The system and tests use actual data from a wind farm in Spain. The results show that the collaboration among agents facilitates the effective detection of faults and can significantly reduce false alarms, indicating a notable advancement in the industrial maintenance and monitoring strategy.