This paper analyzes the challenges and requirements of establishing energy data ecosystems (EDEs) as data-driven infrastructures that overcome the limitations of currently fragmented energy applications. It proposes a new data- and knowledge-driven approach for management and processing. This approach aims to extend the analytics services portfolio of various energy stakeholders and achieve two-way flows of electricity and information for optimized generation, distribution, and electricity consumption. The approach is based on semantic technologies to create knowledge-based systems that will aid machines in integrating and processing resources contextually and intelligently. Thus, a paradigm shift in the energy data value chain is proposed towards transparency and the responsible management of data and knowledge exchanged by the various stakeholders of an energy data space. The approach can contribute to innovative energy management and the adoption of new business models in future ene... [more]

The anti-reflection film can effectively reduce the surface reflectivity of solar photovoltaics, increase the transmittance of light, and improve the photoelectric conversion efficiency. The high refractive index coating is an important part of the anti-reflection film. However, the traditional metal oxide coating has poor stability and complicated processes. To address this issue, we prepared two organic high refractive index (HRI) photopolymers by modifying epoxy acrylic acid with 4,4′-thiodibenzenethiol, which can be surface patterned by nanoimprinting to prepare antireflection coatings. As a result, two modified photopolymers with high refractive index (n > 1.63), high optical transmittance (T > 95%), and thermal stability (Tg > 100 °C) are obtained after curing. In particular, the diphenyl sulfide photopolymer modified by ethyl isocyanate acrylate has a refractive index up to 1.667 cured by UV light. Our work confirms that the organic HRI photopolymer can be obtained by introducin... [more]

The development and utilization of marine renewable energy is an important measure for achieving energy conservation, emissions reduction and carbon neutrality. Ocean thermal energy is the most stable energy among all the types of marine renewable energy. This paper built a simulation model of an ocean thermal energy conversion system based on actual device specifications by Aspen and MATLAB and put forward a corresponding control strategy. The opening control signal of the control valve at the turbine inlet was the condenser inlet pressure in this paper, and the frequency control of the working fluid pump depended on the evaporating pressure and flow rate of the working fluid. This paper analyzed the key operating parameter changes of the system under different working conditions. According to the analysis results, the turbogenerator in this system was able to generate 50 kW power for about 8 months per year. The highest net output power of the Organic Rankine Cycle was 47.3 kW; the h... [more]

Floating offshore wind turbines (FOWT) have attracted more and more attention in recent years. However, environmental loads on FOWTs have higher complexity than those on the traditional onshore or fixed-bottom offshore wind turbines. In addition to aerodynamic loads on turbine blades, hydrodynamic loads also act on the support platform. A review on the aerodynamic analysis of blades, hydrodynamic simulation of the supporting platform, and coupled aero- and hydro-dynamic study on FOWTs, is presented in this paper. At present, the primary coupling method is based on the combination of BEM theory and potential flow theory, which can simulate the performance of the FOWT system under normal operating conditions but has certain limitations in solving the complex problem of coupled FOWTs. The more accurate and reliable CFD method used in the research of coupling problems is still in its infancy. In the future, multidisciplinary theories should be used sufficiently to research the coupled dyna... [more]

Effective methods for the design of high-performance electrical machines must use optimization techniques and precise and fast physical models. Convergence, precision and speed of execution are important issues, in addition to the ability to explore the entire domain of solutions. The finite element method (FEM) presents a high accuracy in the results but with high computational costs. Analytical models, on the other hand, solve the problem quickly but compromise the accuracy of the results. This work shows a comparison between an optimization made with an analytical electromagnetic model and a direct optimization with finite element field calculation for the optimal design of a Halbach array permanent magnet synchronous motor (PMSM). In the case of the analytical model, it is necessary to use an iterative method of correcting the model to obtain a valid solution. This method is known as Space Mapping (SM) and the analytical model can be improved with a reduced number of iterations wit... [more]

The aim of this paper is to develop an experimental procedure to measure contact friction between granular particles. The contact friction is a micro-property needed in the micromechanical modeling of a granular medium. The proposed method can measure the interparticle friction of idealized spherical particles using the conventional direct shear apparatus in soil testing. In preparation for the test, the test specimen is made of four steel balls embedded halfway in a sulfaset paste plate positioned in a statically determinant configuration to provide point contacts among the steel balls. The upper half of the shear box contains one steel ball, which is supported by three steel balls in the lower shear box, ensuring contact points at all times during the test. Shear force and shear displacement are measured under a specific normal force during the test. An analytical equation is developed based on the geometrical configuration of the balls to calculate the interparticle friction angle.... [more]

With the wide application of motors in deep sea exploration, deep-sea motors require a higher power density and a longer lifetime. Motor lifetime mainly depends on the thermo-mechanical stress (TMS) load on its stator insulation. Unlike normal motors, deep-sea motors are usually filled with oil to compensate for the high pressure generated by seawater, which leads to high additional viscous drag loss. This, combined with the high pressure, will greatly change the TMS distribution and further influence motor insulation lifetime. Thus, the insulation degradation analysis of deep-sea oil-filled (DSOF) motors due to TMS has become important. This paper presents a TMS analytical model of DSOF motor insulation, considering the joint effects of high pressure and motor temperature. The CFD method is adopted to perform motor thermal analysis, considering temperature effects on viscous drag loss. The FEA method is adopted for thermo-mechanical analysis and to verify the analytical model accuracy... [more]

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive... [more]

Patients are different regarding their health conditions, illnesses and ailments, and mobility. These and other factors could affect their specific feelings about the thermal environment. Current methods of predicting thermal sensations were developed based on research on a group of healthy people. Therefore, the use of these methods with patients should be verified. This paper aimed to verify selected thermal comfort models in terms of their reliability to predict the average assessment of thermal conditions in the patient rooms and the percentage of dissatisfied patients. Thermal condition analyses were based on microclimate parameter measurements and extensive questionnaires among patients, done in parallel in the hospital’s patient rooms. The research was carried out in 23 hospitals located in the following provinces in Poland: (Warmińsko-Mazurskie, Kujawsko-Pomorskie, Mazowieckie, Wielkopolskie, Łódzkie, Świętokrzyskie, Lubelskie and Dolnośląskie). Overall, 890 patients from 14 di... [more]

As the largest emitter of carbon dioxide all over the world, China requires a rapid breakthrough and large-scale commercial application of carbon capture, utilization and sequestration (CCUS) technology to achieve the 2060 carbon neutrality target. However, the process of CCUS technology commercialization in China is quite slow. Firstly, an obstacle system with 15 factors is established based on a literature review and expert consultation, namely on economic, technical, political, market, and social obstacles. Secondly, taking into account the uncertainty and randomness inherent in subjective judgment, Vague set is introduced for the first time to improve the DEMATEL-ANP (DANP) method in order to analyze comprehensive importance and causal relationship of obstacles. According to the study, in advancing CCUS’s commercialization in China, economic obstacles are simply the tip of the iceberg, with the deeper reasons rooted in political obstacles. Specifically, seven critical obstacles are... [more]

Recent growing energy crisis in Europe, coupled with the rising energy prices worldwide, is a clear indication of the many difficulties awaiting the transition of modern societies away from fossil fuels [...]

With the increasing installed capacity of photovoltaic (PV) power generation, it has become a significant challenge to detect abnormalities and faults of PV modules in a timely manner. Considering that all the fault information of the PV module is contained in the current-voltage (I-V) curve, this pioneering study takes the I-V curve as the input and proposes a PV-fault identification method based on improved deep residual shrinkage networks (DRSN). This method can not only identify single faults (e.g., short-circuit, partial-shading, and abnormal aging), but also effectively identify the simultaneous existence of hybrid faults. Moreover, it can achieve end-to-end fault diagnosis. The diagnostic accuracy of the proposed method on the measured data reaches 97.73%, is better than the convolutional neural network (CNN), the support vector machine (SVM), the deep residual network (ResNet), and the stage-wise additive modeling using multi-class exponential loss function based on the classif... [more]

A huge concern regarding global warming, as well as the depletion of natural fuel resources, has led to a wide search for alternative energy sources. Due to their high reliability and long operation time, thermoelectric generators are of significant interest for waste heat recovery and power generation. The main disadvantage of TEGs is the low efficiency of thermoelectric commercial modules. In this work, a unique design for a multilayer TE unicouple is suggested for an operating temperature range of 50−600 °C. Two types of thermoelectric materials were selected: «low temperature» n-and p-type TE materials (for the operating temperature range of 50−300 °C) based on Bi2Te3 compounds and «middle temperature» (for the operating temperature range of 300−600 °C) n- and p-type TE materials based on the PbTe compound. The hot extrusion technology was applied to fabricate n- and p-type low-temperature TE materials. A unique design of multilayer TEG was experienced to achieve an efficiency of u... [more]

Rockburst may cause damage to engineering equipment, disrupt construction progress, and endanger human life. To this day, the occurrence of rockburst remains complex and difficult to predict. This study proposes the D-P-Transformer algorithm to address this issue by improving the embedding structure of the Transformer for specific applications to rockburst data. To reduce the computational requirement, sparse self-attention is adopted to replace self-attention. A distilling operation and multiple layer replicas are simultaneously used to enhance the robustness and speed up the algorithm’s process. Taking all relevant rockburst factors into consideration, multiple experiments are conducted on seven large-scale rockburst datasets with different training ratios to verify the reliability of the proposed D-P-Transformer rockburst prediction algorithm. As compared to the original algorithm, the proposed algorithm shows average reductions of 24.45%, 46.56%, 17.32%, and 48.11% in the mean abso... [more]

This paper presents the results of comparative studies on the implementation of machine learning methods in the damage intensity assessment of masonry buildings. The research was performed on existing residential buildings, subjected to negative impacts of the industrial environment induced by coal mining plants during their whole technical life cycle. The research was justified on the grounds of safety of use, as well as potential energy losses and CO2 emissions generated by the inefficient management of building materials resources resulting from poor planning of retrofitting. In this field, the research is in line with the global trends of large-scale retrofitting of existing buildings in European countries due to their thermal insulation parameters and seismic hazard. By combining this with the effects of material degradation throughout the technical lifecycle of buildings, the proposed methods allow for a more efficient approach to maintaining quality management of large groups of... [more]

A heat pump is an energy-effective technique to provide heating for buildings using available heat sources from the environment. Solar irradiation and ambient air are the most accessible heat sources among different heat sources; however, they are unstable for a day or several days. A large volume of the heat storage tank is usually required to provide a stable heating supply. As the most commonly used media for heat storage, water has a limitation on the heat storage temperature, i.e., above 0 °C, limiting its density of energy storage. This paper presents an experiment that evaluated the performance of a developed ice source heat pump used for assisting a solar heating system. The ice source heat pump can extract both sensible heat and the latent heat of water freezing, which doubles the density of energy storage and increase the heating output by 50%. The experiment results showed that the solar heating system tested could supply hot water at the highest temperature of 60 °C (with i... [more]

Utilizing the flexibility of hydropower to integrate more intermittent renewable energy into the power grid requires hydro units to expand the operating range; this duty, however, requires a continuous improvement of their stability during part-load conditions. This study focuses on the stability performance of hydropower generation systems (HGS) during flexible operation. First, a dynamic model of HGS that reflects the characteristics of part-load conditions is established by introducing pressure pulsation in the draft tube. Second, the model of HGS is coupled with a shafting system to investigate the vibration property of the unit. Then, the validity of the coupling model is verified by comparing it with a traditional model and actual data. Finally, some possible ways to mitigate the instability caused by part-load operation are explored. The results show that part-load operation of the system is accompanied by significant dynamic response fluctuations (5%). Moreover, the interaction... [more]

With the rising popularity of unmanned aerial vehicles (UAVs) and increasing variety of their applications, the task of providing reliable and robust control systems becomes significant. An active fault-tolerant control (FTC) scheme requires an effective fault detection and isolation (FDI) algorithm to provide information about the fault’s occurrence and its location. This work aims to present a prototype of a diagnostic system intended to recognize and identify broken blades of rotary wing UAVs. The solution is based on an analysis of acoustic emission recorded with an onboard microphone array paired with a lightweight yet powerful single-board computer. The standalone hardware of the FDI system was utilized to collect a wide and publicly available dataset of recordings in real-world experiments. The detection algorithm itself is a data-driven approach that makes use of an artificial neural network to classify characteristic features of acoustic signals. Fault signature is based on Me... [more]

Bellows are the key structures that compensate for and absorb the temperature-dependent displacement of a gas insulated switchgear (GIS) shell. It is of great engineering value to master the relationship between the temperature-dependent displacement behavior and various influencing factors. Based on the analysis of the influencing factors of the temperature variation displacement compensation ability of the GIS bellows, a bellows model was established. By coupling it with a shell having different degrees of bending through two layout methods, finite element simulation was carried out based on ABAQUS software to obtain the regular relationship between the temperature variation displacement compensation behavior of the bellows and various influencing factors. The results of the case study show that the temperature change displacement compensation ability of the bellows is most significantly affected by their own structural size. Reducing the wall thickness and increasing the wave height... [more]

Since there are no legally defined testing requirements for mobile positive pressure fans, they may be tested based on methods that do not correspond to their actual operating conditions. Adequate assessment of the technical and operating conditions for this type of equipment is particularly important for equipment used in rescue operations. Such units should be characterized by efficient and reliable operation. This article investigates the influence of measurement methods of the volumetric airflow rate on the performance of a power unit. The article shows that the applied measurement method, whether it is PN-EN ISO 5801 (test conditions in a pipe duct—Method A) or other methods, i.e., ANSI/AMCA 240-15 and testing of the characteristics of the velocity profile (tests in open flow—Method B), can cause differences in the power demand of fans of from 3.2% to 4.5%. The differences in the requirements of propulsion power translate into fuel consumption and emissions of harmful exhaust gase... [more]

In the hot-spot fault of photovoltaic modules, there is a low resistance hot-spot fault caused by crystal defects, such as internal crack and PN junction failure. When the faulty area is partially shaded, it will produce severe temperature rise, accelerate the aging of battery unit, and even cause fire, which will affect the safe operation of the photovoltaic system. In this paper, the low resistance hot-spot fault endangering the safe operation of photovoltaic modules is taken as the research object; the shunt effect of equivalent low resistance caused by crystal defects under local shadow occlusion is explained by using the reverse characteristic of PN junctions of battery units, and its failure mechanism is analyzed. The three working states of the power generation system and the formation conditions of hot-spots in the process of power generation are analyzed in detail. By building a simulation model, the heating power distribution characteristics of hot-spots under different exter... [more]

In the EU countries, almost 50% of the produced energy is used in residential buildings. More than 25% of this energy is used to produce domestic hot water, of which almost 80% is used to heat water in domestic hot water circulation systems. This is due to high expectations on the part of residents based on their comfort, in particular regarding the supply of heat for heating and domestic hot water. In the course of their long-term research conducted on real systems, the authors confirmed that the operation of domestic hot water distribution systems causes significant costs, mainly due to heat losses. Therefore, typical variants of energy optimization of such systems were analyzed. Tests have shown that selected solutions, such as the use of control automation, are not sufficient, and recommended additional thermal insulation may not be applicable due to technical reasons. With an aim of finding a solution to the problem, the publication analyzes operational data from an existing heat... [more]

As telecommunications are becoming increasingly important for modern systems, ensuring secure data transmission is getting more and more critical. Specialised numerous devices that form smart grids are a potential attack vector and therefore is a challenge for cybersecurity. It requires the continuous development of methods to counteract this risk. This paper presents a heuristic approach to detecting threats in network traffic using statistical analysis of packet flows. The important advantage of this method is ability of intrusion detection also in encrypted transmissions. Flow information is processing by neural networks to detect malicious traffic. The architectures of subsequent versions of the artificial neural networks were generated based on the results obtained by previous iterations by searching the hyperparameter space, resulting in more refined models. Finally, the networks prepared in this way exhibited high performance while maintaining a small size—thereby making them an... [more]

As one of the countries with the most rapid development of new energy, China has been committed to exploring countermeasures to the challenges of new energy consumption. After more than ten years of consideration and consultation, the “renewable portfolio standard“(RPS) for “renewable energy power consumption responsibility weighting” has landed in China. However, in the official affirmation issued by the National Energy Administration, theoretical support for the basis of the initial quota allocation is still lacking. In this study, we examine the efficiency of the weight allocation scheme for renewable energy power consumption responsibilities, which was announced by the National Energy Administration in 2018 and which is based on the BCC-DEA efficiency model. The results indicate that most provinces have low allocation efficiency under this allocation scheme. Therefore, we propose an optimal allocation scheme for a renewable energy consumption quota, based on the ZSG-DEA model. With... [more]

Subchannel codes have been widely used for thermal-hydraulics analyses in nuclear reactors. This paper details the development of a novel subchannel code within the Idaho National Laboratory’s (INL) Multi-physics Object Oriented Simulation Environment (MOOSE). MOOSE is a parallel computational framework targeted at the solution of systems of coupled, nonlinear partial differential equations, that often arise in the simulation of nuclear processes. As such, it includes codes/modules able to solve the multiple linear and nonlinear physics that describe a nuclear reactor, under normal operation conditions or accidents. This includes thermal-hydraulics, fuel performance, and neutronics codes, between others. A MOOSE-based subchannel code is a new addition to the fleet of INL-developed codes, based on the MOOSE framework. In this work, we present the derivation of the subchannel equations for a single-phase fluid, we proceed with the description of the algorithm that is used to solve these... [more]