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The entropy change causing dipolar depolarization is proposed as an origin of electrical power generation in triboelectric generators using polar materials. Rubbing mechanically forces permanent dipoles in materials to become orientationally ordered, establishing a low entropy state with an initial dipolar polarization P 0. In this state, the electric field within the materials is zero, but a nonzero Helmholtz free energy F = F 0 = P 0 2 2 (C s − C ∞) arises from the entropy contribution (C s , static capacitance; C ∞ , capacitance at high frequency). Consequently, this state is energetically unstable and undergoes a spontaneous transition into a disordered high entropy state with F < F 0 , resulting in the establishment of a non-zero electric field. Through this process, the energy bounded in materials as the entropy component of free energy is converted, and the electrical energy becomes F 0 η with η = 1 − C ∞ C s (0 < η < 1). Electrical circuit analysis shows that this energy conversion process can be well represented by introducing a virtual resistance R p = τ C s − C ∞ (τ , dipolar relaxation time). This suggests that the entropy change in finite time τ serves as the origin of electrical power generators. Under the matching condition τ = C s R , the power spectrum at the load is best aligned with that at the generator, maximizing the power transmission. The results presented here serve as a basis for understanding the principle of electric power transmission in triboelectric generators through dipolar depolarization. [ABSTRACT FROM AUTHOR]

In the current study, complementary metasurface units with toroidal geometry were fabricated, using the computer numerical control engraving method. The metasurfaces were engraved in copper-coated, FR-4 plates. The produced metasurfaces were electromagnetically characterized in the microwave regime. Furthermore, they were studied regarding their energy harvesting capability, in the microwave range, where they absorb electromagnetic energy. It was found that toroidal structures harvest energy from the incident microwaves and transform it to electric power, through a simple rectification circuit. Moreover, their energy harvesting efficiency was found to be comparable or even superior to those of others reported so far. Therefore, the hereby obtained experimental results evidently show that engraved toroidal metasurfaces could potentially be used as energy harvesters in the microwave regime. [ABSTRACT FROM AUTHOR]

Global energy shortage puts stringent demand for energy harvesters capable of transforming external green vibration sources into electrical power. Employing a self-biased magnetoelectric (ME) composite of FeCuNbSiB/Ni/PZT (lead zirconate titanate), a prototype of vibration energy harvester is designed and fabricated. The energy harvester has a circular orbit in which a permanent magnetic cylinder reciprocates once an initial kinetic energy is provided. Upon a vibration signal, like handshaking, movement of the permanent magnetic cylinder causes an alternative magnetic field, which was applied on the ME composite. Via magnetic-force-electrical coupling, the ME composite of FeCuNbSiB/Ni/PZT produces output voltage. Finite element simulation is carried out to reveal the underlying mechanism of the harvester. The analysis shows that a maximum output voltage of 7.63 V can be obtained once an original potential energy is applied for the magnet. In particular, the magnet moves back and forth automatically inside the circular orbit with no need to further apply the energy. The effectiveness of the energy output is experimentally verified. When handshaking the energy harvester, a maximum open-circuit voltage of 5.51 V can be generated. The study offers a solution for power supplying some miniaturized or portable devices, such as small hand set and pedometer. [ABSTRACT FROM AUTHOR]

The efficient coordination of the distance and directional overcurrent relays (DOCRs) is jeopardized by the massive deployment of renewable distributed generation (DG) into electrical power networks. The two key aspects influencing the relay coordination are the bidirectional flow of current and increased short-circuit currents due to DG integration. This study investigates the consequences of variable DG penetration on the distance and dual-setting DOCRs (DS-DOCRs) coordination. As a result, common optimal relay settings have been obtained that can be utilized for variable DG penetration levels in modified IEEE-14 bus test system. For the distance relays (DRs), a fixed zone 1 and variable zone 2 operation have been considered. The proposed combined protection scheme is tested on a modified IEEE-14 bus test system using DS-DOCRs and DRs. The relay coordination problem is formulated as a constrained non-linear optimization problem and solved by genetic algorithm (GA) and gray wolf optimization (GWO). In this paper, DS-DOCRs with user-defined relay characteristics have demonstrated superior performance in line protection compared to conventional DOCRs with normal inverse (NI) characteristics. In addition, a comprehensive comparative analysis of optimization algorithms has been performed between GA and GWO algorithms. [ABSTRACT FROM AUTHOR]

In this work, we have developed a functional construction material from a cement material that can scavenge mechanical energy from surrounding environment into electricity. An energy harvesting device called "a triboelectric nanogenerator (TENG)" is fabricated from the cement–reduced graphene oxide (rGO) composite to convert mechanical energy into electrical power. The incorporation of rGO in cement is found to enhance the electrical output of the TENG through space charge polarization, resulting in the increase in triboelectric charge density. The maximum power density achieved from the cement–rGO composite TENG is 1.72 W/m2, which is six times greater than that of the unmodified cement TENG. Additionally, rGO improves the compressive strength of the cement composite by up to 50%. This enhancement is attributed to the large specific surface area of rGO, which creates nucleation sites, resulting in increased crystallization of cement hydration products. The findings of this work highlight the promising prospects for the development of functional construction material for smart energy building with improved mechanical strength. [ABSTRACT FROM AUTHOR]

Due to the ubiquity of textiles in the lives, electronic textiles (E‐textiles) have emerged as a future technology capable of addressing a myriad of challenges from mixed reality interfaces, on‐garment climate control, patient diagnostics, and interactive athletic wear. However, providing sufficient electrical power in a textile form factor has remained elusive. To address this issue, different approaches are discussed, starting with supercapacitors' advantages and limitations and material choices for textile‐based supercapacitors before discussing proper data analysis and design considerations of textile‐based energy storage to power wearable electronics. [ABSTRACT FROM AUTHOR]

Switchgear is a vital component of modern power systems, responsible for regulating the flow of electrical power. Contact issues, irregular loads, and other similar problems can cause switchgear to overheat, leading to unexpected disturbances and potential damage to the power equipment. Thermal imaging shows significant potential and is increasingly employed to detect faults in power equipment. However, the unique characteristics of thermal images often pose challenges to accurate fault detection. This research aims to study the effectiveness of transfer learning architectures for switchgear fault detection. This paper applies eleven transfer learning architectures, including SqueezeNet, GoogLeNet, InceptionV3, DenseNet201, ResNet50, Xception, InceptionResNetV2, ShuffleNet, EfficientNetB0, AlexNet, and VGG19. The results of the testing phase demonstrated that the application of transfer learning by fine-tuning pre-trained convolutional neural network architectures was highly effective in the classification of thermal images captured from switchgear units. The models achieved accuracy rates between 83.87% and 98.38%, and values of F 1 -Scores between 83.11% and 98.34% in the pre-trained architectures. [Display omitted] • Transfer learning is applied to address the unique characteristics of thermal images for switchgear fault detection. • A thermal image dataset is setup and augmented to improve the classification performance. • Establish standard comparisons among eleven transfer learning architectures. • Achieve rapid and precise classification with the proposed transfer learning architectures. [ABSTRACT FROM AUTHOR]

Droplet‐based electricity generators (DEGs) have emerged as innovative devices capable of transducing the kinetic energy of falling water droplets into electrical power, thereby presenting a promising solution for ambient energy harvesting. For effective application, DEGs must exhibit transparency and flexibility to facilitate aesthetic integration and optical/mechanical adaptability for utilization on natural objects and wearable devices. In this study, a hydrogel‐based DEG (Hy‐DEG) designed is proposed to be seamlessly integrated into everyday environments without compromising design or functionality. With the intrinsic characteristics of hydrogel, the Hy‐DEG exhibits superior optical transmittance (≈99%) and stretchability (≈70% of its original length), generating the electrical output performance of ≈45 V of voltage, 15 µA of current, and 42 µW of maximum peak power, with single droplet impact. This capability of the Hy‐DEG can operate electronic devices for environmental monitoring while maintaining seamless integration with commonly encountered surfaces. In this context, this study elucidates the characteristics of hydrogel bestowing novel functionalities upon the DEG, expanding the potential for energy harvesting in residential and commercial contexts. The implications of this research extend beyond conventional energy generation, fostering the development of self‐powered, transparent, and flexible devices. [ABSTRACT FROM AUTHOR]

The study explores a novel method to combat the Light and Elevated Temperature‐Induced Degradation (LeTID) in solar cell modules, which significantly reduces their efficiency and lifespan. This method involves applying alternating current (AC) of various waveforms (triangular, sinusoidal, and square) and frequencies (5 and 100 kHz) to boron‐doped p‐type passivated emitter rear contact (p‐PERC) solar cell modules. This approach effectively lowers the series resistance at the critical junction between the silver (Ag) contact and the silicon emitter layer of the PERC solar cell, thereby reducing charge recombination hindered by high resistance, especially at elevated temperatures. As a result, there is an improved flow of electrical charges, leading to decreased energy loss and increased solar cell efficiency. The study's findings indicate that a slow, smooth sinusoidal AC waveform at 100 kHz is particularly effective, restoring about 100% of the original performance of the panel. Moreover, oscillations at 5 kHz also show considerable efficacy, recovering more than 96% of the performance. The sinusoidal waveform is noted to surpass both triangular and square waveforms in recovery efficiency. This research highlights the use of high‐frequency AC electricity as a viable strategy to extend the lifespan and enhance the performance of solar panels. [ABSTRACT FROM AUTHOR]

Electricity transmission lines constitute a vital element in any electrical power system. Nevertheless, the progressive collapse of these structures caused by accidental events and cascade failure can lead to a wide range of failures, including total collapse. The failure of power transmission line structures due to extreme wind and ice loads poses a substantial challenge for electrical power distribution companies globally. In this study, the progressive collapse behavior of a 230-kV electrical power transmission line in Fars Province, Iran was evaluated utilizing the alternative load path method within a nonlinear dynamic analysis framework. Finite element models of a tangent electricity tower (DC0), a terminal tower (DC90), and the conductors of the transmission line were created and simulated using SAP2000 software. The investigation focused on the impact of removing the legs of the transmission tower, and the simulation analyzed the progressive collapse behavior under various loading conditions, including wind load, snow-induced freezing, and simultaneous wind and ice load. By employing the nonlinear dynamic analysis of the progressive collapse, the stresses developed in the structural elements were evaluated, and the damaged elements were identified. The results demonstrated that following the failure of one leg, the tangent and terminal towers remained stable under gravitational loads. However, under extreme winds at a 90∘ angle, the failure of a leg resulted in significant damage to the towers. Further assessment of the tangent and terminal towers revealed that the terminal tower exhibited higher strength compared to the tangent tower. This was evident in the lower dispersion of displacements and a reduced number of damaged elements observed in the terminal tower when one leg was removed. [ABSTRACT FROM AUTHOR]

Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, China, 2Guangdong Power Grid Co., Ltd., Guangzhou, China, 3China Southern Power Grid Co., Ltd., Guangzhou, China To achieve load management optimization and timely failure warning for power transformers, as well as improve the reliability of the power network, this paper proposes a multiple time scale prediction method for top oil temperature (TOT) based on an adaptive extended Kalman filter (AEKF) algorithm. This method combines the Kalman filter (KF) algorithm and the D. Susa thermal model. The TOT, oil exponent and oil time constant are taken as state variables, while the ambient temperature and load current are used as input variables. The iterative optimization of the oil exponent and oil time constant is realized by comparing the estimated and observed TOT values. Moreover, the proposed method utilizes an adaptive noise estimator to correct the noise statistics parameters, which simplifies the initial noise setting and thus further improves the TOT prediction accuracy. A case study is conducted with two 110 kV transformers. The results show that comparing the thermal equivalent circuit model and the extended KF algorithm, the proposed method has a higher accuracy in the intraday ultra-short-term prediction on a 15-min time scale and day-ahead short-term prediction on a 24-h time scale for the TOT. [ABSTRACT FROM AUTHOR]

The cordierite‐based ceramic catalyst filter (CCF) has attracted considerable attention as a promising future air purification system due to its ability to filtrate particulate matter (PM), as well as decompose volatile organic compounds (VOCs) through ultraviolet (UV)‐activated photocatalytic reactions. Its performance, however, is strictly limited because majority of UV photons are absorbed near the entrance of the high‐aspect‐ratio air‐flow channels, thus, only a limited portion of photocatalysts is activated during the flow of polluted air. In this study, a high‐performance CCF is presented featuring textured waveguides (TWs) aligned with an array of UV light‐emitting diodes (LEDs) emitting at a peak wavelength of 365 nm, which are inserted into an array of high‐aspect‐ratio channels. TWs ensure the delivery of UV photons deep inside channels via total internal reflection and scattering, enabling the activation of majority of photocatalysts, resulting in remarkable improvement in VOCs removal efficiency. The proposed CCF system exhibits much higher formaldehyde (HCHO) removal efficiency by 70% compared to conventional CCF systems even subjected to much lower UV light power densities. It is strongly believed that it is possible to further improve the removal efficiency, while maintaining effective PM filtering and ultralow electrical power consumption, by optimization of the geometry of the CCF system with TWs. [ABSTRACT FROM AUTHOR]

This paper proposes stochastic programming to optimal economic scheduling problems of a sustainable integrated energy system with renewable resources including power, natural gas, and hydrogen carriers. Hydrogen is considered a byproduct of electrical power and natural gas carriers using water electrolysis and steam methane reform process technologies. The main objective is to minimize the operation and emission costs while addressing uncertainties of electric/heating/cooling demands, electricity price, and renewable generation using scenario-based stochastic programming. To achieve a risk-hedging strategy, downside risk constraints are involved to minimize the risky scenarios portfolio. The whole problem is modeled as mixed-integer linear programming in GAMS optimization software. The analysis revealed that the expected operation cost without DRC is $ 577.52 and the expected risk-in-cost value for risky scenarios is $ 470.7. However, a conservative decision for reaching zero risk is costly and increases the expected cost up to $ 2901.1, which is not economically viable. A modest decision-making strategy compromises the cost and risk values where for decreasing the risk-in-cost to $ 288.7 (36.8%), the expected cost increased by to $1010.39 (75.95%). Moreover, the risk-averse decision-maker lowers the power sold to the grid, increases the use of water electrolyzing instead of the SMR process to reduce the environmental charges, and tries to increase flexibility with the help of hydrogen and battery storage. • The operation of a multi-carrier energy system is evaluated by stochastic programming. • The risk of different uncertainties is involved using downside risk constraints. • The risk-neutral and risk-averse strategies are developed by adjusting a risk level. • The hydrogen carrier considered as an intermediate to serve multi-energy demands. • The water electrolyze and steam methane reform technologies produce hydrogen gas. [ABSTRACT FROM AUTHOR]

The surge in global energy demand mandates a significant expansion of electric power substations. Nevertheless, the ecological consequences of electric power substation operation, particularly concerning the electromagnetic field, on soil microbial communities and nitrogen enrichment remain unexplored. In this study, we collected soil samples from six distinct sites at varying distances from an electric power substation in Xintang village, southeastern China, and investigated the impacts of electromagnetic field on the microbial diversity and community structures employing metagenomic sequencing technique. Our results showed discernible dissimilarities in the fungal community across the six distinct sites, each characterized by unique magnetic and electric intensities, whereas comparable variations were not evident within bacterial communities. Correlation analysis revealed a diminished nitrogen fixation capacity at the site nearest to the substation, characterized by low moisture content, elevated pH, and robust magnetic induction intensity and electric field intensity. Conversely, heightened nitrification processes were observed at this location compared to others. These findings were substantiated by the relative abundance of key genes associated with ammonium nitrogen and nitrate nitrogen production. This study provides insights into the relationships between soil microbial communities and the enduring operation of electric power substations, thereby contributing fundamental information essential for the rigorous environmental impact assessments of these facilities. [ABSTRACT FROM AUTHOR]

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This work explores the potential of self-powered MEMS devices for application in the preventive conservation of cultural heritage. The main objective is to evaluate the effectiveness of piezoelectric aluminum nitride MEMS (AlN-MEMS) for monitoring vibrations and to investigate its potential for harvesting energy from vibrations, including those induced by visitors. A preliminary laboratory comparison was conducted between AlN-MEMS and the commercial device Tromino®. The study was then extended to the Picture Gallery of Ursino Castle, where joint measurements with the two devices were carried out. The analysis focused on identifying natural frequencies and vibrational energy levels by key metrics, including spectral peaks and the Power Spectral Density (PSD). The results indicated that the response of the AlN-MEMS aligned well with the data collected by the commercial device, especially observing high vibrational energy around 100 Hz. Such results validate the potential of AlN-MEMS for effective vibration measurement and for converting kinetic energy into electrical power, thereby eliminating the need for external power sources. Additionally, the vibrational analysis highlighted specific locations, such as the measurement point Cu4, as exhibiting the highest vibrational energy levels. These points could be used for placing MEMS sensors to ensure efficient vibration monitoring and energy harvesting. [ABSTRACT FROM AUTHOR]

Photovoltaic technology has become one of the major renewable ways to generate electric power. However, the mismatch between the incident solar spectrum and photo-electric response efficiency of solar cells severely constrains their performance. Hence, spectral modification technologies, e.g., up-conversion (UC), down-conversion (DC), and luminescent down-shifting (LDS) technologies have been applied widely in the photovoltaic field to reform the incident spectrum to match the best response band possible. In this paper, we review the latest developments of the three technologies above in terms of material selection, optical characteristics, and photovoltaic performance. It is found that the three most popular materials for conversion are NaYF4: Er3+, Yb3+, and Yb3+. The excitation bands for the three technologies are 800–1550 nm, 250–488 nm, and 250–488 nm, respectively, while the emission bands are 523–669 nm, 520–1031 nm, and 490–1010 nm, respectively. Furthermore, issues hindering the development of spectral modification technologies are pointed out, e.g., low absorption efficiency, poor quantum conversion efficiency, and hurdles in commercialization. Finally, suggestions and solutions to address the above-mentioned issues are provided. [ABSTRACT FROM AUTHOR]

Nowadays, the microgrid system is characterized by a diversification of power factors and a complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting mostly focus on the fault detection and operation optimization of a single power device. However, for increasingly complex microgrid systems, it becomes increasingly challenging to effectively contain faults within a specific spatiotemporal range. This can lead to the spread of power faults, posing great harm to the safety of the microgrid. The topology optimization of the microgrid based on deep reinforcement learning proposed in this paper starts from the overall power grid and aims to minimize the overall failure rate of the microgrid by optimizing the topology of the power grid. This approach can limit internal faults within a small range, greatly improving the safety and reliability of microgrid operation. The method proposed in this paper can optimize the network topology for the single node fault and multi-node fault, reducing the influence range of the node fault by 21% and 58%, respectively. [ABSTRACT FROM AUTHOR]

Electrical vehicles are finding wide acceptance in the Jordanian transportation market; this has caused an accelerating shift in the emissions of greenhouse gases from the direct burning of fossil fuels consumed by the transportation sector towards the power generation sector. On the other hand, as electric vehicles gain more popularity, an extra load is added to the electrical power generation systems, raising essential concerns such as the capability of the power network to support this massive extra load and the increased emission of greenhouse gases caused by power plants. Studies show that Jordan's weather is known for being bright, sunny, and very suitable for the generation of electric power from solar energy sources. Therefore, with an infrastructure that can support convenient off-grid charging, a huge burden will be taken off the national grid and the environment. Therefore, this work proposes a basic design for an off-grid PV-covered carport and presents a study of the economics and effectiveness of using such a system to charge electric vehicles owned by the students and employees of the Applied Science Private University. The study is based on actual solar irradiance data collected on-site during university working hours (8 a.m.–5 p.m.) to allow students and employees to charge their electric vehicles from an off-grid carport system while on campus. Space limitations for carport design, initial design cost, return on investment, and annual electricity consumption are discussed to demonstrate the benefits of such a system for both the consumer (convenience and low charging cost) and the power company provider (less load to maintain). [ABSTRACT FROM AUTHOR]

In a conventional automotive manufacturing plant, the paint shop alone can represent 36% of the total energy consumption, making it the most demanding area in terms of electricity and fossil fuel energy consumption. This study explores the possibility of decentralizing the production of electrical power and heat simultaneously, using an Organic Rankine Cycle (ORC) system integrated with a Parabolic Trough Collector (PTC) in a paint shop. To date, no similar system has been explored or implemented by the automotive industry. To increase the efficiency of the integrated system, wasted heat generated during the paint manufacturing process is recovered and used to pre-heat the organic fluid in the ORC system. A 4E analysis (Energy, Exergy, Economic, and Environmental) is conducted to determine the practical viability of the proposed system. When applied to the southern region of the USA, this system's installed capacity is projected to be 11 times higher than the two unique SORC pieces of equipment currently running in Louisiana and Florida. The goals are to reduce the reliance on external primary energy sources and decrease the carbon emission footprint from production activity. The system is evaluated for a location in Alabama, USA. The designed SORC, using toluene, can produce 712.2 kWel net and 13,132 kg/h of hot water, with an overall energy efficiency of 31.02%; exergy efficiency of 34.23; and ORC efficiency of 27.70%. This leads to an electrical energy saving of 5.9% for the manufacturing plant. The regenerative thermal oxidizer (RTO) heat exchanger, the secondary heat source of the system, has the highest exergy destruction—3583 kW. The system avoids the emission of 4521 tCO2 per year. A payback period of 10.16 years for the proposed system is estimated. Considering a planning horizon of 10 years, the investment in the system is also justified by a benefit–cost analysis. [ABSTRACT FROM AUTHOR]

High temperatures in photovoltaic (PV) modules lead to the degradation of electrical efficiency. To address the challenge of reducing the temperature of photovoltaic modules and enhancing their electrical power output efficiency, a simple but efficient photovoltaic cooling system based on heat pipes (PV-HP) is introduced in this study. Through experimental and numerical investigations, this study delves into the temperature characteristics and power output performance of the PV-HP system. Orthogonal tests are conducted to discern the influence of different factors on the PV-HP system. The experimental findings indicate that the performance of the PV-HP system is superior to that of the single system without heat pipes. The numerical simulation shows the effects of system structural parameters (number of heat pipes, angle of heat pipe condensation section) on system temperature and power output performance. The numerical simulation results show that increasing the angle of the heat pipe condensation section and the number of heat pipes leads to a significant drop in system temperature and an increase in the efficiency of the photovoltaic cells. [ABSTRACT FROM AUTHOR]

This research proposes the utilization of Peltier modules to convert electrical energy from thermal energy to show its potential as a renewable energy source for residential and commercial application. The study, whose results are presented in this manuscript, was conducted in the city of Monterrey, located in the northeast of Mexico. The energy source was tested and analyzed utilizing a set of statistical metrics and further comparison against experimental test results. The Distrito Tec area in Monterrey city is an academic complex and it was chosen for this study, which consisted of the indirect measurement of the average annual heat energy stored within the buildings' cement structure. The aim was to obtain the annual accumulated electrical power in Wh per year that Peltier modules could provide in Distrito Tec, which is located in a city with solar irradiation levels above the world average. The proposal in this paper could encourage further investigation regarding this energy that is currently waste heat. More specifically, the results of this research highlight the importance of thermoelectric modules and seek to motivate research to improve their properties and make them more efficient and more viable as well. Thermoelectric modules have the potential to be part of the solution to sustainable development as presented in the United Nations SDG-7—ensure access to affordable, reliable, sustainable and modern energy for all. [ABSTRACT FROM AUTHOR]

It is essential to protect control, regulation and data storage units used in automated robotic manufacturing from the consequences of harmful electrical grid harmonics. In this paper, the effectiveness of active/passive harmonic filters built into LED lamps, test benches, and industrial robots was investigated (in the latter two cases, light and heavy load states were applied). Based on network analysis, it was found that the built-in passive harmonic filters of the luminaries were ineffective because the THD of the current was approximately two or three times the permissible value according to the IEEE 519-2022 standard. It was proved that the built-in active harmonic filter of the test bench at a heavy load worked properly, but at a light load it was not effective, while the magnitude of harmonic distortion of the industrial robot exceeded the allowed level (three times the limit at a light load, seven times the limit at a heavy load). Further measurements were also performed at three locations: an engineering room, a gearbox house machine tool, and an office room (where there were no built-in filters). The results proved that in each case, there was a significant exceedance of the limit value. Therefore, protection against harmonics needs to be installed, and then the measurements must be repeated. [ABSTRACT FROM AUTHOR]

Mechanical energy harvesters made from soft and flexible materials can be employed as energy sources for wearable and implantable devices. However, considering how human organs and joints expand and bend in many directions, the energy generated in response to a mechanical stimulus in only one direction limits the applicability of mechanical energy harvesters. Here, we report carbon nanotube (CNT) sheets/an elastomer bilayer harvesting electrode (CBHE) that converts two-axis mechanical stimulation into electrical energy. The novel microwinkled structure of the CBHE successfully demonstrates an electrochemical double-layer (EDL) capacitance change from biaxial mechanical stimulation, thereby generating electrical power (0.11 W kg−1). Additionally, the low modulus (0.16 MPa) and high deformability due to the elastomeric substrate suggest that the CBHE can be applied to the human body. [ABSTRACT FROM AUTHOR]

The demand for electric power has consistently been on the rise, owing to urbanisation and technological improvements. On the generation side, renewable sources have been favoured over their polluting, exhaustible, non‐renewable counterparts. These changes in the power system have necessitated a system for maintaining the supply‐demand balance, to maintain system stability. A complex power system is also more prone to blackouts and grid failure. Islanding helps in provision of supply to consumers in a microgrid, reducing the possibility of a blackout. Depending on the power demand and generation, loads need to be shed or restored to mitigate power imbalances. A wide area distribution management system (WADMS) is proposed to dynamically shed and restore loads in the islanded mode, with the aid of micro phasor measurement units (µPMUs). A priority and consumer‐based load shedding and restoration (PCLS) algorithm is proposed in the WADMS that preferentially sheds or restores loads based on their assigned load priority indices and number of consumers. The algorithm has been tested on a modified IEEE 13 bus system, incorporated with a solar photovoltaic (PV) system, diesel generators (DGs) and an energy storage system (ESS) in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

Satellites engaged in observation missions often face severe pointing constraints, which can limit the ability of their solar panels optimize the generation of electrical power during payload operations. Some approaches to maximize power generation involve either using orientable solar panels, or performing orbital maneuvers to point fixed or deployable (non-orientable) solar panels towards the Sun, which can compromise the payload's ability to meet its pointing requirements. In this study, an alternative approach that enables high-consuming remote sensing payloads to operate for extended periods without requiring orientable solar panels is presented. The satellite under consideration is equipped with fixed or deployable (non-orientable) solar panels mounted on up to three different perpendicular faces. The on-board payload is required to remain within a fixed angle from a target direction, which can be either nadir or a specific geographical position. To derive an optimal tracking law, the projected solar array area at each instant is maximized, resulting in optimal electrical power generation. This methodology allows the satellite to maintain its pointing constraints and efficiently operate high-consuming payloads for longer periods. The proposed tracking law is validated using an actual mission scenario, comparing the power generation achieved by the proposed method against other techniques. The approach presented in this paper shows improved performance, enabling satellites equipped with non-orientable solar panels to fulfill their observation requirements while optimizing electrical power generation. This work offers significant benefits for satellite operators, reducing the need for costly orientable solar panels and enhancing the overall efficiency of satellite missions. • Guidance law for optimal power generation while complying with payload pointing constraints. • Simple and easy formulation, suitable for real-time systems. • Methodology validated and compared against other attitude strategies. • Integration and simulation of the guidance law into a control scheme. [ABSTRACT FROM AUTHOR]

• A novel variable stiffness valve based on PEEK and stainless steel was proposed. • Stress-strain behavior and operational characteristics of novel valve were studied. • Impacts of novel valve on compressor performance and noise experimentally. • Compressor performance improved by 2.6 % and noise reduced by 3–5 dB. Improving valve design is crucial for enhancing the performance of rolling piston type rotary compressor. A novel variable stiffness valve based on PEEK and stainless steel was proposed. The stress-strain behavior of the novel valve was studied, and its operational characteristics, including opening and closing angles and over-compression losses, were analyzed in a compressor. It is shown that opening and closing angle of the new-designed valve were advanced compared to that of the original cylinder by about 2∼3°, leading to a general reduction in over-compression losses, with a maximum decrease of 4.15 W. The impacts of new-designed valve on compressor performance were experimentally investigated. The cooling capacity and coefficient of performance of compressors equipped with new-designed compared to original valve were improved by 1.1–1.7 % and 1.1–2.6 %, respectively. In addition, the input electrical power required for the new valve was observed to be 0.9–1.3 % lower. The incorporation of high-damping material in the new valve design significantly reduced compressor noise by 3–5 dB at the critical frequency bands of 630–1250 Hz. These findings offer valuable insights for enhancing the energy efficiency and noise reduction in rolling piston type rotary compressors. [ABSTRACT FROM AUTHOR]

When a series arc fault (SAF) occurs in one branch of a low-voltage alternating current power distribution system with complex connections and many types of loads, the load branches interact with one another, and thus, detection becomes more difficult. To avoid the occurrence of electrical fire, an SAF detection method based on a residual deformable convolutional network (RDCN) is proposed. First, an arc fault data acquisition experimental platform for low-voltage complex branches is built to measure trunk current signals during normal operation and SAF occurrence. Second, 1D current signals are mapped to 2D space as input to the model, more comprehensively responding to the amplitude and variation of the signals. Deformable convolutional networks are used to extract spatial distribution information from feature maps to avoid the limitation posed by the fixed shape of convolutional kernels and improve spatial differentiation among different data. Considering the ability to focus better on fault information, channel attention is introduced to strengthen the correlation among feature channels. Then, the experimental platform data verify that the method can effectively distinguish whether SAF occurs and the type of load where the fault occurs, with the highest accuracy of up to 98.98% and 98.84%, respectively, and an average test time of 1.8 s in determining whether a fault occurs in a six-branch circuit. Finally, compared with existing network models, RDCN has a shorter running time while obtaining a higher accuracy rate. [ABSTRACT FROM AUTHOR]

The electric power industry is a high-risk industry with frequent accidents. To ensure the life safety of employees and reduce the probability of accidents, it is necessary to utilize certain technical means to identify the main causative factors in electric fatal accident reports. This research proposes an accident causation identification method that combines text categorization and catastrophe association analysis. First, an improved text feature extraction method (TF-IDF-GloVe-LDA) is proposed by fusing term frequency-inverse document frequency (TF-IDF), global vectors for word representation (GloVe), and latent dirichlet allocation (LDA) algorithms. Then, an SVM classifier was used to categorize the 473 accident report texts into five categories, ACCIDENT, PROCESS, CAUSE, PROBLEM, and RESPONSE, based on the extracted text feature vectors. Second, for the 461 CAUSEs categorized from the accident report texts, the TF-IDF algorithm is utilized to mine them to obtain 62 accident causative factors. Using the word cloud map and semantic network, a visualization analysis is performed to reveal the intrinsic connection between causative factors. The human factor analysis and classification system (HFACS) is combined to construct a framework and a Boolean dataset for electric power fatal accident causative factors. Finally, the catastrophe progression method is utilized to improve the FP-growth algorithm and propose a catastrophe association analysis method. It is utilized to mine the Boolean dataset to obtain 28 association rules and construct the accident causal network. The main causative factors were ultimately identified by analyzing the critical causal chains within the network and examining the frequency and sensitivity of each node. The findings of this study indicate that a lack of effective management, supervision, and training serves as the fundamental cause of fatal accidents in the electric power industry when compared to equipment and environmental factors. This paper offered a fresh perspective on identifying primary accident causative factors in non-standardized text and exploring their intricate mechanisms of interaction, which holds significant implications for the pre-control management of accidents in the power industry. [ABSTRACT FROM AUTHOR]

As electric vehicle (EV) adoption increases, transportation services will shift dependence from liquid fuel infrastructure to electric power infrastructure. Since transportation plays a major role in disaster response and recovery, this shift in dependence has important implications for coupling electrical grids and transport resilience. The implications for the electrical grid for southwestern British Columbia, Canada are examined, motivated by this region's high EV adoption rate and the potential for a catastrophic magnitude 9.5 earthquake. A comparison of the resilience of the electrical infrastructure compared to the fuel infrastructure is provided and approaches for increasing resilience in the region for EV power supply are discussed. This paper compiles lessons learned from past large earthquakes in Chile, Japan, and New Zealand with consideration given to successes and failures. While this paper was written with a focus on southwestern British Columbia, many of the suggestions for increasing power system resilience could be applied in other seismically active locations during the transition to EVs. This paper also considers integrated disaster resilience planning for the changing transport landscape from fuel vehicles to EVs. [ABSTRACT FROM AUTHOR]

It is shown that the transformation of the energy sector based on the construction of new architectures of energy systems requires a joint consideration of three layers of two-way energy information exchange: economic, informationmanagement, and physical (energy), and the functioning of modern electric power systems requires the application of process monitoring with enhanced functionality. For such intelligent monitoring, defined as Smart-monitoring, the first and second level monitoring procedures are characterized, in particular, taking into account measurement with a change in signal type, operation with information with syntactic, semantic and pragmatic adequacy, diagnosis with identification and forecasting. It is shown that Smart-monitoring in electric power at the level of medium and low voltages (distribution and consumption systems) should be formed as a technological platform for diagnosis, audit, control, dispatching, energy management of electric power systems, formation of modern energy markets. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerators (TENGs) have emerged as a promising technology to harvest electrical energy from natural motions such as human movement, wind, and water flow. Although TENGs show significant potential in small-scale applications, developing large-scale TENGs capable of generating high power remains a significant challenge. Several factors that can affect the performance of large-scale TENGs are being investigated to overcome this challenge, including the size and configuration of dielectric materials. This study optimizes dielectrics regarding surface area, thickness, and multicell configuration to improve harvested electrical power density in large-scale TENGs. In the studies, glass fiber was used as the positive dielectric, and multipurpose white silicone was used as the negative dielectric because of their high tribo-potential, durability, and easy accessibility. In the size optimization phase, dielectric thicknesses and surface areas that provide the maximum power density were determined. Subsequently, horizontal and vertical multicell configurations were examined to efficiently integrate size-optimized dielectrics. The results reveal that large-scale TENGs with vertical multicell configurations can achieve high and usable energy density for electronics. The findings provide valuable insight into the development of large-scale TENGs with advanced power generation capabilities. [ABSTRACT FROM AUTHOR]

Copper-clad steel wire is widely used in electric power, railroads, automobiles, and other fields. However, how to balance production efficiency and wire quality is still a challenging task. In this paper, a continuous cladding composite casting method for copper-clad steel wire is proposed based on the hot-dip plating process, which adopts a removable graphite crucible and S-shaped wiring to control the thickness and eccentricity of the cladding metal, and at the same time adopts connecting the electrical resistance furnace with a water-cooled crystallizer to achieve rapid solidification, which in turn strengthens the mechanical properties of the copper-clad wire and thus realizes the rapid and continuous preparation of copper-clad steel wires with good quality. In this study, the optimum process parameters, including drawing speed and pure copper melt temperature, were provided to reveal the mechanism of metallurgical bonding at the solid–liquid composite interface. The circumferential uniformity, mechanical properties, and electrical conductivity of the prepared copper-clad steel wires were tested. The growth mechanism of the copper-coated structure and the mechanism of rapid solidification to strengthen the mechanical properties are described. The results have been plotted in graphs to describe the properties and characteristics of the materials. [ABSTRACT FROM AUTHOR]

Purpose. To obtain analytical dependencies for the precise calculation of the stator current of a frequency-regulated three-phase shortcircuited induction motor and to estimate the components of its main electrical power losses, which are spent on the transportation magnetic power losses (to the magnetization circuit) and additional power losses (through the motor air gap), as well as with using the obtained refined dependencies to research the electromagnetic processes and energy modes of the frequency-regulated induction motor when its speed and load change. Methodology. The method of generalized vectors is used for the refined calculation of the electromagnetic processes and energy modes of the frequency-regulated induction motor. Results. Based on the catalog data and parameters of the induction motor’s equivalent replacement circuit, also the specified values of its useful rotational torque and speed, refined analytical dependencies were obtained for the calculation of the main electromagnetic power losses of the frequency-regulated induction motor, which take into account the influence of all types of power losses, which present in it, as well as – power losses spent on transporting magnetic losses (to the magnetization circuit) and additional losses (through the air gap of the motor). With the help of the obtained dependencies, the energy modes (including main power consumption and electromagnetic power losses, efficiency factor, power factor) of the frequency-regulated induction motor in the driving and generator modes of its operation in relation to the first (at speeds not higher than the nominal) and the second (at speeds above the nominal) speed control zones for the operating ranges of the motor useful rotational torque and speed changes were calculated. Originality. A refined analytical calculation dependence has been obtained for determining the active projection of the generalized stator current vector of a frequency-regulated induction motor, which takes into account the presence of additional power losses and the component of electrical losses caused by the transportation of additional power losses through the air gap of the motor; an analytical dependence is also proposed for determining the increment of the mentioned active projection, which is due to the transportation of magnetic power losses to the motor magnetization circuit. Practical value. Analytical calculation dependencies are proposed for the quantitative assessment of errors (as a percentage of mentioned values) in steady-state modes for determining the main electromagnetic power losses of the frequency-regulated induction motor, caused by the absence (in comparison with relevant studies from known publications) of taking into account additional and magnetic power losses, as well as – the influence of electrical component losses caused by the transportation of the mentioned power losses through the air gap or to the magnetization circuit of the motor, respectively. References 16, tables 5, figures 2. [ABSTRACT FROM AUTHOR]

Introduction. Solar photovoltaic (PV) has recently become very important especially in electrical power applications for countries with high luminosity because it is an effectively unlimited available energy resource. Depending on solar radiation and temperature, the PV generator has a non-linear characteristic with a maximum power point (MPP). The novelty is the efficiency improvement of a PV energy module, it is necessary to track the MPP of the PV array regardless of temperature or irradiation circumstances. Purpose. This paper presents the modeling and the digitally simulation under MATLAB/Simulink of a Fuzzy Logic Controller based on Voltage Perturbation Algorithm (FLC-VPA) applied to PV battery charging system, which consists of PV module, DC-DC boost converter, MPP tracking (MPPT) unit and battery storage. Methods. The DSP1104 is then used to experimentally implement this MPPT algorithm for real-time driving. The obtained results show the high precision of the proposed FLC-VPA MPPT around the optimal point compared to the conventional VPA under stable and changing meteorological conditions. Practical value. The experimental results approve the effectiveness and validity of the proposed total control system in the PV system. References 30, tables 3, figures 17. [ABSTRACT FROM AUTHOR]

Purpose: Sawdust, a by-product of wood workplaces, poses environmental contamination and reduces workspace efficiency. This research aimed at recycling sawdust from rain tree by incorporating its extracts into gelatin films to create active films with antifungal properties against Aspergillus flavus. Research method: Sawdust was extracted by microwave with various solvents and electrical powers. The extract (0, 0.25, 0.5, 1, and 2%) were then tested for A. flavus inhibition. The extract was also incorporated with gelatin for making wrapped films and tested for inhibition potential on garlic inoculated with A. flavus. Findings: The optimal microwave extraction condition utilized a solvent mixture comprising distilled water and 95% ethanol in a 1:1 v/v ratio, applying 100 watts of electrical power for 30 seconds, repeated 5 times. This method yielded 23.26 mg/g of tannin. Furthermore, the 2% concentration of the extract significantly inhibited both mycelium growth and spore germination of A. flavus (P<0.05) when tested on a petri dish. Additionally, incorporating 2% of the crude extract into gelatin film resulted in the most favorable outcome. This treatment demonstrated the capability to prolong the shelf life of wounded-inoculated garlic for more than 12 days. Research limitations: No limitations were found. Originality/Value: Sawdust originating from a rain tree can be recycled biodegrable actine gelatin films against A. flavus, a field-bomepathogen in garlic. [ABSTRACT FROM AUTHOR]

The reliable operation of electrical power transmission systems is crucial for ensuring consumer's stable and uninterrupted electricity supply. Faults in electrical power transmission systems can lead to significant disruptions, economic losses, and potential safety hazards. A protective approach is essential for transmission lines to guard against faults caused by natural disturbances, short circuits, and open circuit issues. This study employs an advanced artificial neural network methodology for fault detection and classification, specifically distinguishing between single-phase fault and fault between all three phases and three-phase symmetrical fault. For fault data creation and analysis, we utilized a collection of line currents and voltages for different fault conditions, modelled in the MATLAB environment. Different fault scenarios with varied parameters are simulated to assess the applied method's detection ability. We analyzed the signal data time series analysis based on phase line current and phase line voltage. We employed SMOTE-based data oversampling to balance the dataset. Subsequently, we developed four advanced machine-learning models and one deep-learning model using signal data from line currents and voltage faults. We have proposed an optimized novel glassbox Explainable Boosting (EB) approach for fault detection. The proposed EB method incorporates the strengths of boosting and interpretable tree models. Simulation results affirm the high-efficiency scores of 99% in detecting and categorizing faults on transmission lines compared to traditional fault detection state-of-the-art methods. We conducted hyperparameter optimization and k-fold validations to enhance fault detection performance and validate our approach. We evaluated the computational complexity of fault detection models and augmented it with eXplainable Artificial Intelligence (XAI) analysis to illuminate the decision-making process of the proposed model for fault detection. Our proposed research presents a scalable and adaptable method for advancing smart grid technology, paving the way for more secure and efficient electrical power transmission systems. [ABSTRACT FROM AUTHOR]

Thermoelectric effects refer to the voltage generation from temperature gradients in condensed matter. Although various power generators are made from them, all the known effects, such as Seebeck effect, require macroscopic temperature gradients; since the sign of the generated voltage is reversed by reversing the temperature gradient, the net voltage disappears when the temperature distribution fluctuates temporarily or spatially with a macroscopic temperature gradient of zero. It is impossible to utilize such temperature fluctuations in the conventional thermoelectric effects, a situation which limits their application. Here we report the observation of a second-order nonlinear thermoelectric effect; we develop a method to measure nonlinear thermoelectricity and observe that a superconducting MoGe film on Y3Fe5O12 generates a voltage proportional to the square of the applied temperature gradient. The nonlinear thermoelectric generation demonstrated here provides a way for making power generators that produce electric power from temperature fluctuations. A second-order nonlinear thermoelectric effect can be used for making power generators using temperature fluctuations. Here, the authors report that a MoGe film on Y3Fe5O12 generates a voltage proportional to the square of the temperature gradient. [ABSTRACT FROM AUTHOR]