The article presents a set of experimental-static models of the properties of fine-grained concretes on a cement−slag binder and quartz sand with the addition of a hardening accelerator made on a 3D printer. The influence of the factors of the composition of the mixture and the effects of their interaction on the studied properties of concrete was established. By analyzing the models, the influence of the factors of mixture composition on the studied properties was ranked. The nature and degree of interrelation of individual properties of concrete are shown. A method for calculating the optimal compositions of concrete for a 3D printer, providing the specified properties at a minimum cost, is proposed.

Cogeneration is preferred mostly in process industries where both thermal and electrical energies are required. Cogeneration plants are more efficient than utilizing the thermal and electrical energies independently. Present government policies in India made renewable energy generation mandatory in order to minimize fossil fuels consumption and to protect the environment. Hence, many cogeneration plants have been integrated with renewable energy generation. However, post-integration effects increase and introduce inefficiencies in the operation of cogeneration systems. In this paper, a case study of an identified typical cogeneration plant where renewable energy is integrated is considered. Post operational effects on the plant due to integration of renewable energy (solar) are studied and by practical experimentation through cost-benefit analysis the break-even point beyond which renewable energy generation introduces inefficiencies is estimated. Next, a systematic methodology is deve... [more]

In recent years, environmental and energy issues relating to global warming have become more serious, and there is a need to shift from conventional power generation, which emits an abundance of carbon dioxide, to renewable energy sources without emissions, such as solar and wind. However, solar power generation, which is one of the renewable energies, changes dynamically, depending on real time weather conditions. Thus, power supplied mainly by solar power generation is often unstable, and an appropriate on-demand energy management for demand-to-supply is required to ensure a stable power supply. Demand-to-supply management methods include inventory management analysis and on-demand inventory management analysis. The cumulative-control method has been used as one of the production management methods to visually manage inventory status in factories and warehouses, while the on-demand cumulative-control method is an extension of inventory management analysis. This study models a demand-... [more]

Tower foundations have been used as grounding electrodes to reduce the area of the grounding devices. However, it is difficult to calculate the grounding resistance due to the complex structure of the reinforced concrete foundation. A method for calculating grounding resistance of reinforced concrete foundations is proposed in this paper. The method equates the complex foundation structure into a cylindrical conductor and then calculates the grounding resistance with the help of the method of moments, which simplifies establishment of the simulation model and reduces the extensive computation. In addition, the applicability of the equal cross-sectional area method and the equal cross-sectional perimeter method is analyzed. It shows that both methods are applicable only when the concrete resistivity is close to the soil resistivity. The equal cross-sectional area method is applicable when the concrete resistivity is within twice the soil resistivity, while the equal cross-sectional peri... [more]

The rotor overtemperature caused by losses is one of the important issues for the high-speed electrical machine. This paper focuses on the rotor loss analysis and CFD-thermal coupling evaluation for 105 kW, 36,000 r/min HSPMSM. Three types of sleeve materials as carbon-fiber, Titanium alloy, and stainless steel are introduced in this paper, researching the effects of sleeve conductivity, thickness and rotational speed on rotor eddy current loss, balancing rotor mechanical strength. The sleeve made of titanium alloy material with a thickness of 3.5 mm is chosen to effectively suppress the rotor eddy current loss in high-speed motors in the paper. The air friction loss becomes significant based on the PM motor at high rotational speed. The roundness error of the rotor sleeve has the important impact on the air friction loss of the rotor and the rotor temperature of the motor, which leads to the over temperature of the rotor. Therefore, based on the CFD fluid model, the influence of round... [more]

The protection of high voltage direct current (HVDC) grids is a challenge considering that the protection system must detect, locate, and interrupt large fault currents in a few milliseconds. Resistive type superconducting fault current limiters (R-SFCL) can help solve that difficult task, reducing the extremely demanding ratings of HVDC circuit breakers. This paper presents different approaches to model R-SFCLs in order to analyze their suitability for assessing the performance of HVDC grid protection, including the step model, the exponential model, the RQ model, and the magneto-thermal model. In the first instance, the R-SFCL models are evaluated in a test grid to analyze their parameterisation and select the most adequate model for the study of HVDC grids. The RQ model is finally chosen for its simplicity but closer behavior to the magneto thermal model in terms of fault resistance dependency and resistance evolution curve. Then, the performance of an RQ type R-SFCL model in conjun... [more]

The electric sector is one of the main emitters of greenhouse gases that lead to exacerbating global warming. There is a lack of consensus in the literature regarding renewable energy (RE) determinants and their impacts on the power sector. Using a panel fully modified OLS model, we examine the effect of research and development, the human development index, technological innovation, and other factors on the share of RE sources in electricity generation in six Association of Southeast Asian Nations (ASEAN) member countries from 2000 to 2018. We find that research and development, the human development index, and technological innovation have different effects on different RE sources. The human development index and research and development, for example, modify the composition of RE by shifting resources from conventional RE sources such as hydropower to newer, more technology-intensive ones such as solar, wind, and bioenergy sources. Our findings show that technological innovation, cap... [more]

Blockchain, or distributed ledger, is an innovative technology that is emerging in various sectors and industries across the globe. It has attracted the attention of different interest groups such as energy companies, SMEs and start-ups, information technology developers, financial institutions, national authorities, and the university community. Through, for example, the decentralization of authority in transactions, Internet of Things (IoT) implementation, and smart contracting, the improvement of the daily business operations is firmly forecasted. In the energy sector, digitalization is already present in solutions such as smart grids, smart meters, electric vehicles, etc. Moreover, a new concept of the Internet of Energy (IoE) has been introduced in the academic literature. In this article, the level of trust and maturity of Blockchain technology implementation is investigated through the Blockchain Maturity Questionnaire, developed by the authors. The database consists of response... [more]

With the depletion of fossil energy and increasingly serious environmental problems, demand-side resources play an increasingly prominent role in peak shaving and valley filling, energy conservation, and emission reduction. Under the background of further promotion of the “double carbon” goal in China, considering the possible double uncertainty factors in the process of unit and demand response resources participating in the scheduling and the goal of minimum carbon emission, the uncertainty models of unit output and demand-side resource response are respectively constructed based on the sequential stochastic production simulation algorithm and the method of additional random variables. In the model, the influence of random forced outage on unit output and the uncertain influence of response deviation caused by the limitation of demand response resource information processing and response aging characteristics are considered, respectively. By analyzing the power supply and demand, con... [more]

Mapping the subsurface temperatures can efficiently lead to identifying the geothermal distribution heat flow and potential hot spots at different depths. In this paper, an advanced adaptive multitask deep learning procedure for 3D spatial mapping of the subsurface temperature was proposed. As a result, predictive 3D spatial subsurface temperatures at different depths were successfully generated using geolocation of 494 exploratory boreholes data in Catalonia (Spain). To increase the accuracy of the achieved results, hybridization with a new modified firefly algorithm was carried out. Subsequently, uncertainty analysis using a novel automated ensemble deep learning approach for the predicted temperatures and generated spatial 3D maps were executed. Comparing the accuracy performances in terms of correct classification rate (CCR) and the area under the precision−recall curves for validation and whole datasets with at least 4.93% and 2.76% improvement indicated for superiority of the hyb... [more]

Putting glass doors on the display cases of refrigerators is one of the most efficient ways to reduce the energy consumption of supermarkets. However, the glass fogs up when opening the door because of the difference in air temperature inside and outside of the refrigerator, thereby obscuring the view. To defog the glass, anti-sweat heaters (ASHs) are used. In this paper, the power usage of ASHs according to changes in the dew point (DP) inside a supermarket were evaluated for two types of ASH, i.e., the door-frame ASH and the glass ASH. The evaluation was based on measurements of the condensation on the glass doors of vertical display cases, used for the preservation of frozen foodstuffs. A mathematical model of the correlation between the ASH’s power usage and the DP was developed and used for predicting the long-term energy savings. The savings were calculated based on the measured DPs inside the supermarket, which were extrapolated over a longer time period based on their correlati... [more]

Since energy consumption in developing countries has increased significantly, motivating energy-saving habits among citizens is an important issue both from the academic and industrial perspectives. Thus, this study aims to predict consumer purchase intention for energy-efficient household appliances based on an extended model of the Theory of Planned Behavior (TPB). This study incorporated two additional constructs of moral norms and environmental concern in the model of the TPB. A self-administered questionnaire was distributed to 1155 Bangladeshi consumers, and partial least squares structural equation modeling (PLS-SEM) regression was used to test the hypotheses. Results show that attitude, subjective norms, and perceived behavior control significantly influence consumer purchase intention of energy-efficient appliances (EEAs). This study also proved that the extension of moral norms is a significant predictor of consumers’ purchase intention in the classic theory of planned behavi... [more]

This study summarises research progress to identify appropriate quality methodologies for representing, interpreting, and modelling complex contexts such as the Claudian Aqueduct in the Appian Way Archaeological Park. The goal is to intrinsically integrate (embed) geometric survey (Laser scanning and photogrammetric) with the materials and construction techniques (Stratigraphic Units—SU), semantic models in order to support the design with a better understanding of the artefact considered, and also to give indications that can be implemented in the future in a continuous cognitive process. Volume stratigraphic units in the form of architectural drawings, heritage building information modelling (HBIM) and extended reality (XR) environments have been oriented to comparative analyses based on the research case study’s complex morphology. Analysis of geometries’ intersection, construction techniques and materials open up new cognitive scenarios, self-feeding a progressive knowledge and mak... [more]

In order to improve the air-gap magnetic field waveform and reduce the torque ripple of dual three-phase surface-mounted permanent magnet synchronous motors (PMSMs), a new surface-mounted modulated permanent magnet (PM) structure is proposed in this paper. Compared with the existing pole-cutting structure, the modulated magnetic pole does not need to customize the precise machining mold. However, when the modulation pole structure is installed, only the magnetic block-assisted assembly structure is designed to reduce the manufacturing cost. Based on the principle of specific harmonic elimination technology (SHET), the number, size and position angle of the modulated magnetic poles can be calculated, and the elimination or the injection of specific harmonics of the air-gap magnetic field can be realized, which can optimize the performance of the motor. It can be seen that the modulation pole structure based on SHET is also an effective method to improve the sinusoidal waveform of the ai... [more]

In the event of a DC side fault in modular multilevel converters (MMCs), the fault current contributions are initially made by submodule (SM) capacitor discharge, which occurs before the fault is detected, followed by the AC side contribution to the DC side fault. While the AC side currents can be regulated using fault blocking SMs, the initial discharge of the SM capacitors results in high DC fault currents, which can take several milliseconds to be brought under control. This paper presents a method to actively control the rate of rise of the DC fault current by regulating the discharge of SM capacitors and accelerating the suppression of fault current oscillations during fault ride-through (FRT) in a full-bridge (FB)-MMC system. In the proposed method, the discharge direction of the FBSM capacitors is reversed following the detection of a DC side fault, which leads to a reversal in the fault current direction and a fast drop-off towards the zero-crossing. Immediately after the zero-... [more]

Shallow Geothermal Energy (SGE) extracted by Ground Source Heat Pump (GSHP) is a proven clean and profitable technology. Although it is available almost everywhere, its market enjoys different maturity levels along with the other EU Members and even those within the same country. In the Murcia region, in Southern Spain, the presence of GSHP is almost nonexistent. Germany, in contrast, has an extensive tradition of exploiting its SGE resources and is an example of a mature GSHP market. In this work, the technical and non-technical barriers were assessed in both countries to identify the site-specific parameters preventing a better deployment of SGE in Southern Spain. In addition, a SWOT analysis was conducted to highlight the parameters positively and negatively influencing the geothermal resource extraction. Results showed that both study cases showed similar and good technical conditions, such as sufficient resource 80 W/m approx. or a similar impact on the environment mainly due to t... [more]

Accurate online capacity estimation and life prediction of lithium-ion batteries (LIBs) are crucial to large-scale commercial use for electric vehicles. The data-driven method lately has drawn great attention in this field due to efficient machine learning, but it remains an ongoing challenge in the feature extraction related to battery lifespan. Some studies focus on the features only in the battery constant current (CC) charging phase, regardless of the joint impact including the constant voltage (CV) charging phase on the battery aging, which can lead to estimation deviation. In this study, we analyze the features of the CC and CV phases using the optimized incremental capacity (IC) curve, showing the strong relevance between the IC curve in the CC phase as well as charging capacity in the CV phase and battery lifespan. Then, the life prediction model based on automated machine learning (AutoML) is established, which can automatically generate a suitable pipeline with less human int... [more]

The decarbonization of the power system forces the rapid development of electric energy storage (EES). Electricity consumption is the fundamental driving force of carbon emissions in the power system. However, the current EES capacity planning research that considers the load-side carbon emission responsibility is still limited. To fill this research gap, this paper proposes a carbon incentive mechanism while considering load-side carbon emission responsibility. Additionally, a bi-level optimal capacity planning model of the load-side EES based on carbon emission flow (CEF) theory is proposed. The upper level obtained the bus carbon intensities through the optimal economic dispatch and passed them to the lower level. Considering the carbon incentive mechanism, the lower level optimized the EES capacity. Finally, the model was tested by MATLAB/Gurobi in the modified IEEE-39 bus power system. The results show that under the stimulation of the carbon incentive mechanism, the bi-level opti... [more]

Road lighting is essential to ensure the safety and comfort of its users, especially in preventing accidents and aiding visual tasks. The monumental shift from conventional road lighting technology to light-emitting diode (LED) lighting is driven by energy efficiency, associated cost savings, and environmental concerns in the road lighting system. This study aims to investigate the performance of LED in substitution for high-pressure sodium vapour (HPSV) road lighting in Penang Bridge, Malaysia using the Data Envelopment Analysis (DEA), a frontier-based optimisation approach, by modelling energy, cost, and environment together, as none of the previous studies has included energy, cost, and environmental concerns together in one model. The LED renewable energy industry that promotes zero carbon emissions has the potential to establish an affordable, clean, and carbon-free energy system for road lighting, especially in rural areas.

: This paper presents an aspect of asset tracking and storage conditions. This paper aims to fill the gap in the development of Industry 4.0 in terms of fully digital asset tracking to be implemented by medium and large-size manufacturing and logistics facilities. The article presents an innovative technology for the remote monitoring of chemical raw materials, including fertilizers, during their storage and transport from the place of manufacture to the local distributor or recipient.: The method assumes the monitoring and identification of special transport bags, so-called “big-bags,” through embedded RFID tags or LEB labels and monitoring the key parameters of their content, i.e., temperature, humidity, insolation, and pressure, using a measuring micro-station that is placed in the transported raw material.: The automation of inference based on the collected information about the phenomenon in question (the distribution of parameters: pressure, temperature, and humidity), and expert... [more]

Increasing wind generation insertion levels on electrical grids through power converters may cause instabilities in the AC grid due to the intermittent wind nature. Integrating a Battery Electric Energy Storage System (BESS) in wind generation can smooth the power injection at the Common Coupling Point (PCC), contributing to the power system voltage and frequency stability. In this article, it is proposed to analyze the operation of a lithium-ion battery technology based 1 MW/1.29 MWh BESS connected in parallel with wind generation with a capacity of 50.4 MW. The main characteristics investigated are power smoothing and power factor correction. Experimental results show that BESS contributes to smoothing the active power and correcting the power factor of wind generation, improving the quality of electrical energy at the PCC.

As the population continues to rise, the demand for resources and environmentally friendly management of produced wastes has shown a significant increase in concern. To decrease the impact of these wastes on the environment, it is important to utilize the wastes in producing and/or recovering usable products to provide for the sustainable management of resources. One non-renewable and rapidly diminishing resource is phosphorus, which is used in several products, the most important being its use in manufacturing chemical fertilizer. With the increase in demand but reduction in availability of naturally occurring mineral phosphorus, it is important to investigate other sources of phosphorus. Phosphorus is most commonly recovered through struvite (magnesium ammonium phosphate) precipitation. The recovery of phosphorus from various wastewater has been well established and documented with recovery rates mostly above 90%. However, one of the major drawbacks of the recovery is the high cost o... [more]

Bidirectional DC−DC converters are key devices in the DC distribution system and the energy storage system (ESS). It is important to consider the safety of the elements in the converter for rapid conversion of the power direction. Damages may occur to the power-related components in the circuit if the direction of the inductor current or the capacitor voltage changes instantaneously. To make the power flow change smoothly and quickly, this research proposed a bidirectional DC−DC converter with rapid energy transition technology implemented in the circuit architecture. The rapid energy bidirectional transition technology added a resonance path based on the LC resonant circuit, allowing rapid energy conversion through the resonance path. Therefore, the energy in the energy storage element could be quickly converted without causing circuit surges. Analyses of the converter operating in the step-up mode, the step-down mode, and the transition operation mode are presented. The proposed circ... [more]

In this study, three-dimensional thermal simulations for a 54 V Lithium-ion battery pack composed of 18 LiFePO4 pouch battery cells connected in series were conducted using a multi-scale electrochemical-thermal-fluid model. An equivalent circuit model (ECM) is used as a subscale electrochemical model at each cell node of the battery, which is then combined with the macro-scale thermal and fluid equations to construct a model of the battery and battery pack. With the model, the cooling effects of indirect cooling and direct cooling battery thermal management systems (BTMS) on the battery pack under rapid discharging conditions are explored. It is found that when the battery pack is discharged at 2C, indirect cooling of the bottom plate can effectively dissipate heat and control the temperature of the battery pack. Under the 10C discharging condition, the maximum temperature of the battery pack will exceed 100 °C, and the temperature uniformity will be very poor when using indirect cooli... [more]

The electric vehicle (EV) cluster charging strategy is a key factor affecting the grid load shifting in vehicle-to-grid (V2G) mode. The conflict between variable tariffs and electric-powered energy demand at different times of the day directly affects the charging cost, and in the worst case, can even lead to the collapse of the whole grid. In this paper, we propose a multi-agent reinforcement learning and long-short memory network (LSTM)-based online charging strategy for community home EV clusters to solve the grid load problem and minimize the charging cost while ensuring benign EV cluster charging loads. In this paper, the accurate prediction of grid prices is achieved through LSTM networks, and the optimal charging strategy is derived from the MADDPG multi-agent reinforcement learning algorithm. The simulation results show that, compared with the DNQ algorithm, the EV cluster online charging strategy algorithm can effectively reduce the overall charging cost by about 5.8% by dynam... [more]