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The supply of electric power is vital for the daily lives of people, industrial production, and business services. At present, although enough electric power can be supplied to meet the power demand, there are still some challenges, especially in terms of long-distance power transmissions and long-term power storage. Consequently, if the power production capacity exceeds the immediate consumption requirements, i.e., the produced electric power cannot be consumed in a short period, and much electric power could be wasted. Evidently, to minimize the wastage of electric power, it is necessary to properly plan power production by accurately forecasting the future power load. Therefore, a preferable power load forecasting algorithm is crucial for the planning of power production. This paper proposes a novel deep learning model for the purpose of power load forecasting, termed the SSA-CNN-LSTM-ATT model, which combines the CNN-LSTM model with SSA optimization and attention mechanisms. In this model, the CNN module extracts the features from the sequential data, and then the features are passed to the LSTM module for modeling and capturing the long-term dependencies hidden in the sequences. Subsequently, an attention layer is employed to measure the importance of different features. Finally, the output is obtained through a fully connected layer, yielding the forecasting results of the power load. Extensive experiments have been conducted on a real-world dataset, and the metric R2 can reach 0.998, indicating that our proposed model can accurately forecast the power load. [ABSTRACT FROM AUTHOR]

To investigate the harmonic characteristics of electric locomotives connected to a photovoltaic (PV) power grid based on the actual parameters of a region in Tibet, this paper establishes a simulation model of an electric power grid, including PV and electric locomotive. First, theoretical analysis is conducted to study the harmonic characteristics of electric locomotives and PV power stations. On this basis, we built the MATLAB model to analyze the influence of dynamic working conditions on the locomotive and PV sides on the harmonic characteristics of the power grid. Through the first, second, and third working conditions, a simulation analysis is performed to examine the harmonic characteristics of an electric locomotive when connected to the grid, which includes a PV power source. The results show that the grid side current, including PV and electric locomotive, has a three-phase equilibrium phenomenon, and at the same time, the grid side current harmonic characteristics, including PV and electric locomotive, are mainly reflected in the 17, 19, 21, 23, and 25 frequency odd harmonics. [ABSTRACT FROM AUTHOR]

This paper deals with the control and performance improvement of parallel-operated voltage-source inverters (VSIs) controlled as virtual synchronous generators (VSGs). In publications regarding the parallel-operated VSGs, transmission lines are considered to be mainly inductive. However, less analytical works have been done regarding the control of paralleled VSGs in low-voltage grids with dominant resistive impedances. Once VSIs are controlled as VSGs in a microgrid with more resistive transmission lines, swing equation and system representation for the power-angle synchronization will change leading to a new control structure. Therefore, this paper deals with the control of parallel-operated converter-based VSGs in low-voltage grids with dominant resistive line impedances. In this way, the VSG representation, comprising the swing equation and V-P droop characteristic, for applications in highly resistive microgrids is presented, in which the swing equation and VSG frequency are related to reactive power. Then, the V-P droop characteristic is modified and an enhanced P-V droop characteristic for proper sharing of active power between the VSGs in highly resistive microgrids is proposed. Next, the VSG control is modified so that the R/X ratio at the VSG output increases and thus the decoupled control of active/reactive powers in relatively inductive cases is realized as well. [ABSTRACT FROM AUTHOR]

Electrical power generation in Oman depends mainly on natural gas, while in rural areas it is based mainly on diesel fuel. Oman has committed to net-zero emissions by 2050, in line with the Paris Agreement's goal of limiting global warming to 1.5°C. The objective of this paper is to propose an optimal energy mix model for electricity generation from various energy sources, such as gas, diesel, wind, and photovoltaic, that considers more renewable sources in the energy mix. The optimization model minimizes various costs such as construction cost, operation cost, fuel cost, and carbon emissions, while satisfying the load demand. In this paper, Masirah Island is selected to perform our analysis. Several scenarios are contemplated, including grid extension to the island. The results found that gas-powered generators with 20% PV and storage are the best option in terms of the levelized cost of electricity. The grid extension is an economically feasible option if the existing load is more than doubled. [ABSTRACT FROM AUTHOR]

This paper presents a power management (PMS)-based resource regulation system for combat robots equipped with batteries, supercapacitor banks, and solar cells. Hybrid energy storage source arrangements are needed to increase operational duration and increase the range of combat robots. Integration of multiple devices with different characteristics requires the implementation of a PMS. Distribution of the load of a combat robot by solving a power management problem, formulated as a finite quadratic program (CQP). Optimization of parameters is carried out, such as speed, drag coefficient and operating point of robot components, which are then regulated by the PMS controller. Data information during robot maneuvering by the PMS is measured and takes into account power management issues during the control period. In this research simulation, variations in weight factor parameters are given to determine various difficulties, namely regenerative power management. The simulation results show that the combat robot power management control system is capable of optimally generating electrical power loads for all components. In another study, a comparison of CQP performance in power management is comparable to benchmark performance after being analyzed based on nonlinear model predictive control. [ABSTRACT FROM AUTHOR]

China Power Grid is actively building a new energy-based ultra-high voltage grid system. Therefore, the researches on fire safety of power grid are of great importance. This paper firstly investigates the fire accident characteristics in the substation system. With the focuses on the transformer oil fires, the early detection and early warning, modification, fire monitoring and extinguishing systems of transformer oil are reviewed. It is found that the researches on flowing and jet fires should be reinforced while modified oil and pyrolysis gas detection can be applied for reducing the fire probability. Secondly, the fire risks and characteristics of cables are summarized for the transmission and distribution lines, and the methods of early warning, fire prevention and rescue are analyzed. For the wildfire threatening the transmission and distribution cables, the characteristics of wildfire and corresponding firefighting methods are reviewed. The water mist and liquid nitrogen are identified as the most effective ways of extinguishing cable fires and advanced fire detection and long-range drone fire extinguishing technologies should be improved for wildfires. Finally, the thermal runaway mechanism and fire characteristics of LIB in the energy storage system are summarized, and the difficulties in fire extinguishing are discussed. The application of the existing fire detection system in the field of LIB is proposed, and the early warning indicators for intelligent fire protection are introduced. In the future, the intelligent fire protection systems will improve the safety of energy storage systems, and efficient test platforms and reliable test standards will continue to be demanded to reduce the likelihood of thermal runaway and fire severity. [ABSTRACT FROM AUTHOR]

Wide Area Monitoring System (WAMS) using Phasor Measurement Unit (PMU) have been widely implemented in power systems. Due to its voltage and current measurements accuracy and precision, PMU can be adopted into power system defense plan as well as WAMS. However, there are considerations of the PMU data acquisition to be able to deliver performing analysis of the electrical power system, i.e.: the synchronization of data acquisition time, reporting rate effect, data sample acquisition, and data acquisition range. This paper addresses problems in PMU data collection and method to solve them prior to carrying out analysis to achieve reliable results. Further, the proposed method has been exercised and implemented in actual power systems accordingly the data collection issues in PMU for WAMS analysis have been solved. In contrast to other studies, this research offers insight into data collections and its solutions before they are examined. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency's (IEA's) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid's frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach. [ABSTRACT FROM AUTHOR]

The solar array drive assembly (SADA) slip ring is a critical link that provides electrical power and electric signal transmission between solar arrays and satellite power systems, which is prone to arc faults in the space environment. If these arc faults cannot be detected and eliminated quickly enough, they will seriously threaten the safety of the satellite power system and the satellite. In this paper, a fast arc detection method based on fractal dimension is proposed that adapts to different operating modes of power systems. The detection method collects the current differential signal data flowing through the SADA slip ring, and, according to the trend of the fractal dimension change in this signal, the fault identification algorithm is designed for different operating modes of the power system to achieve real-time and rapid identification of arc faults. Finally, the effectiveness of the proposed method is demonstrated using test data under several different fault conditions. [ABSTRACT FROM AUTHOR]

Deviations of power quality indices (PQI) from standard values in power supply systems of industrial consumers lead to defective products, complete shutdown of production processes, and significant damage. At the same time, the PQI requirements vary depending on the industrial consumer, which is due to different kinds, types, and composition of essential electrical loads. To ensure their reliable operation, it is crucial to introduce automatic PQI control devices, which evaluate the extent of distortion of the sinusoidal voltage waveform of a three-phase system. This allows the power dispatchers of grid companies and industrial enterprises to quickly make decisions on the measures to be taken in external and internal power supply networks to ensure that the PQI values are within the acceptable range. This paper proposes the use of an integrated indicator to assess the extent of distortion of the sinusoidal voltage waveform in a three-phase system. This indicator is based on the use of the magnitude of the ratio of complex amplitudes of the forward and reverse rotation of the space vector. In the study discussed, block diagrams of algorithms and flowcharts of automatic PQI control devices are developed, which implement parametric and nonparametric multiple-hypothesis sequential analysis using an integrated indicator. In this case, Palmer's algorithm and the nearest neighbor method are used. The calculations demonstrate that the developed algorithms have high speed and high performance in detecting deviations of the electrical power quality. [ABSTRACT FROM AUTHOR]

With the progress of modern times, automobile technology has become integral to human society. At the same time, the need for energy has also grown. In parallel, the total amount of waste energy that is liberated from different parts of the automobile has also increased. In this ever-increasing energy demand pool, future energy shortages and environmental pollution are the primary concerns. A thermoelectric generator (TEG) is a promising technology that utilizes waste heat and converts it into useful electrical power, which can reduce fuel consumption to a significant extent. This paper comprehensively reviews automobile thermoelectric generators and their technological advancements. The review begins by classifying different waste heat technologies and discussing the superiority of TEGs over the other existing technologies. Then, we demonstrate the basic concept of and advancements in new high-performance TEG materials. Following that, improvements and associated challenges with various aspects, such as the heat exchanger design, including metal foam, extended body, intermediate fluid and heat pipe, leg geometry design, segmentation, and multi-staging, are discussed extensively. Finally, the present study highlights research guidelines for TEG design, research gaps, and future directions for innovative works in automobile TEG technologies. [ABSTRACT FROM AUTHOR]

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different turbine topologies. This approach has been applied to single, and two-area power systems and has exhibited enhanced performance compared to other commonly referenced studies in the literature. To assess the effectiveness of the cascade control approach proposed performance metrics such as settling time, peak value (overshoot), and integral absolute error (IAE) value of frequency and tie-line power variations are utilized to gauge the system's response to a load perturbation. Additionally, the suggested cascade control technique and design process have undergone robustness testing with ±50% changes in system parameters to validate their reliability. [ABSTRACT FROM AUTHOR]

Marine electric propulsion is an important topic in the research of modern ships and underwater vehicles. The propulsion motor drives based on model predictive control (MPC) are becoming increasingly popular in marine propulsion systems as an emerging technology. However, the multi-objective optimization in conventional MPC requires cumbersome weighting factor tuning. The relatively large computational cost is also detrimental to the industrial application of MPC. Aiming at reducing the computational complexity of multi-objective optimization without weighting factors, this paper proposes an enhanced ranking-based MPC method for induction motor drives in marine electric power propulsion. The presented control set pre-optimization aims to reduce the computational complexity of enumeration and ranking. Based on the sign of torque prediction deviation, the proposed method avoids enumerating all fundamental voltage vectors. Consequently, the number of candidate elements in the initial control set are reduced to four without excessively excluding feasible solutions. By converting predicted numerical errors into ranking results, the proposed MPC seeks the optimal solution among the candidates through improved ranking evaluation. Considering the situation of simultaneous optimal ranking, the normalization error judgment is developed to further optimize the optimal solution selection process. The simulation and experimental results confirm that the proposed MPC is simple and effective. Without the involvement of tuning the weighting factors, the proposed method achieves good performance. [ABSTRACT FROM AUTHOR]

Waste heat is inherent to industrial activities, IT services (e.g., data centers and microprocessors), human mobility, and many other common processes. The power lost each year in this way has been estimated in the 1000 TWh in the EU which, owing to skyrocketing energy prices and not least the urgent need for decarbonizing the economy, has engendered tremendous research efforts among scientists and engineers to recover/recycle this waste energy. Beyond established thermal engineering solutions for waste heat, advances in multifunctional materials open new paradigms for waste heat harvesting. Two smart material types are of particular focus and interest at present; these are thermoelectric and pyroelectric materials, which can both transform heat to electrical power, though via different effects. The present paper summarizes our research work on a new class of pyroelectric materials, namely <111> oriented (1 − x)(Pb(Mg1/3Nb2/3)O3–xPbTiO3 (PMN-PT) and x-Pb(In1/2 Nb1/2)O3-y-Pb(Mg1/3 Nb2/3)O3-(1 − x − y)-PbTiO3 (PIN-PMN-PT) single crystals that exhibit some of the highest pyroelectric properties ever measured. First, a figure of merit for pyroelectric energy harvesting is derived, followed by a detailed assessment of the properties of the said crystals and how they depend on structure, poling, thickness, and temperature. The properties are further contrasted with those of conventional pyroelectric crystals. It is concluded that the PMN-PT-base single crystals are best suited for harvesting devices with a working temperature range from 40 to 100 °C, which encompasses waste heat generated by data centers and some chemical and industrial processes, affording the highest figure of merit among pyroelectric materials. [ABSTRACT FROM AUTHOR]

This paper presents a simple engineering method for evaluating the optical power emitted by light-emitting diodes (LEDs) using infrared thermography. The method is based on the simultaneous measurement of the electrical power and temperature of an LED and a heat source (resistor) that are enclosed in the same plastic packaging under the same cooling conditions. This ensures the calculation of the optical power emitted by the LED regardless of the value of the heat transfer coefficient. The obtained result was confirmed by comparing it with the standard direct measurement method using an integrated sphere. The values of the estimated optical power using the proposed method and the integrated sphere equipped with a spectrometer were consistent with each other. The tested LED exhibited a high optical energy efficiency, reaching approximately η ≈ 30%. In addition, an uncertainty analysis of the obtained results was performed. Compact modelling based on a thermal resistor network (Rth) and a 3D-FEM analysis were performed to confirm the experimental results. [ABSTRACT FROM AUTHOR]

Piezoelectric Energy Harvesting (PEH) has been increasingly adopted due to its substantial potential to harness unutilized vibrations for multiple small- and large-scale real-life applications. Various publications have discussed the PEH rationale and operating principles. Nonetheless, there is a considerable knowledge gap, reflected in a limited number of peer-reviewed articles, involving the selection of optimal PEH location during real-time operational excitations, like wind turbines. Subsequently, this paper considers the Vertical-Axis Wind Turbines (VAWTs) to accumulate vibrations realized mainly at the turbine's tower. Experimental Modal Analysis (EMA) and Operational Deflection Shape (ODS) analysis were employed to predict the natural frequency behavior, vibrational intensity, and electrical power output at various locations along the VAWT's tower. The tower was divided into eight zones to determine which region could yield the maximum power output from the VAWT-PEH system. Many publications have suggested that the region closer to the fixed base of the VAWT would experience the maximum deflection. Yet, this research has shown that the zone nearer the top of the VAWT tower exhibited the highest deflection rates and greater turbulence, resulting in better electrical power production. Consequently, region No. 1 gave the highest deflection, corresponding to a maximum electrical power from excitations with a peak-to-peak voltage of 2.834 V compared with 2.754 V for point No. 8. These lower charges could be practical for powering small-power consumption devices, such as sensors and LEDs, especially when they need a permanent power supply. [ABSTRACT FROM AUTHOR]

As an important component of the smart grid, vehicle-to-grid (V2G) networks can deliver diverse auxiliary services and enhance the overall resilience of electrical power systems. However, V2G networks face two main challenges due to a large number of devices that connect to it. First, V2G networks suffer from serious security threats, such as doubtful authenticity and privacy leakage. Second, the efficiency will decrease significantly due to the massive requirements of authentication. To tackle these problems, this paper proposes a cross-domain authentication scheme for V2G networks based on consortium blockchain and certificateless signature technology. Featuring decentralized, open, and transparent transactions that cannot be tampered with, this scheme achieves good performance on both security and efficiency, which proves to be suitable for V2G scenarios in the smart grid. [ABSTRACT FROM AUTHOR]

With the ongoing expansion and interconnection of electrical power systems, alongside the rapid proliferation of renewable distributed generations (DGs), the short-circuit extent in the power grid is experiencing a significant rise. Fault current limiters (FCLs) have been introduced in an effort to address this issue, ensuring the robustness and sustainability of expensive power system components when confronted with short-circuit faults. Among the various types of FCLs, bridge-type DC reactor fault current limiters (BDCR-FCLs) have emerged as one of the most promising options. While BDCR-FCLs have shown excellent properties in limiting harmful short-circuit currents, they are also advantageous in other respects. This paper investigates the supplementary functionalities of BDCR-FCLs as a multifaceted device towards the enhancement of the quality of supplied energy in terms of total harmonic distortion (THD) reduction, power factor (PF) correction, peak current reduction for nonlinear loads, and soft load variation effects, as well as their capability to limit fault current. To this aim, the capabilities of BDCR-FCLs have been studied through various simulated case studies in PSCAD/EMTDC software V5.0.1, in addition to experimental tests considering an AC microgrid connected to a DC system. The experimental and simulation investigations verify the superior multifaceted functionalities BDCR-FCLs introduce in addition to their excellent fault current-limiting capabilities. The results show that PF improved by 6.7% and 7%, respectively, in simulation and experimental tests. Furthermore, the current THD decreased by 20% and 18% in the simulation and experiment, respectively. [ABSTRACT FROM AUTHOR]

In the light of increasingly valuable resources and a trend towards more efficient processes pushed by climate change, distributed Waste Heat Recovery (WHR) is an important element in the transformation of the energy supply. In recent years, however, WHR systems have often been optimized and implemented for steady-state applications. In this paper, dynamic system modeling and a Steam Rankine Cycle (SRC) pilot plant with 40 kWel are used to investigate applications unutilized thus far for the conversion of high-temperature waste heat into electricity using a shell boiler with 1.27 m3 of liquid water for short-term energy storage. In addition to experimental investigations of the storage system as an Uninterruptible Power Supply (UPS) and the input and output of +/−100% electrical power peaks for grid-assistive operation, a control concept for the use of volatile waste heat is developed from a model-based controller design up to a Model Predictive Control (MPC) with the help of a dynamic system simulation. Based on the validated model and experimental measurement data, outlooks for concrete applications with higher storage capacity and power are provided. [ABSTRACT FROM AUTHOR]

In this paper, a two-layer optimization approach is proposed to facilitate the multi-energy complementarity and coupling and optimize the system configuration in an electric-hydrogen-integrated energy system (EH-IES). Firstly, an EH-IES with virtual energy storage is proposed to reduce the cost of physical energy storage equipment. Secondly, a two-layer optimal allocation method is proposed under a multi-timescale strategy to examine the comprehensive evaluation index of environmental protection and economy. The upper layer utilizes the NSGA-II multi-objective optimization method for system capacity allocation, while the lower layer performs economic dispatch at the lowest cost. Ultimately, the output includes the results of the equipment capacity allocation of the EH-IES that satisfies the reliability constraint interval and the daily scheduling results of the equipment. The results demonstrate that the electric-hydrogen-integrated energy system with the coupling of multiple energy equipment not only enhances the utilization of RENEWABLE energy sources but also reduces the usage of fossil energy and improves the system's reliability. [ABSTRACT FROM AUTHOR]

This paper is an extension of our previous research aimed to improve the performance of radiative-based thermoelectric power generator concept through the use of vertical finned absorber instead of horizontal one (TEG-RVFA). To this end, we used the experimental setup developed in previous study and modified it according to the objective of this paper. The TEG-RVFA is composed of a heated plate (297 mm×182 mm) and four sets of vertical finned absorbers (41 mm×55 mm) with 40×40 mm thermoelectric modules to absorb the heat emitted. At the back side, a finned aluminum heat sink 119 mm wide and 200 mm length with two DC fans was used for cooling. The electrical power supplied to the heater varied between 1000 - 1400 watts and the air gap between the heated plate and the finned absorber varied between 1 to 5 cm. Data recorded included the generated voltage, current, and temperatures at various locations. Results are also compared to those published earlier with horizontal finned absorber. It was observed that the electrical current generated varied like in the case with horizontal finned absorber (TEG-RHFA); it increased with the power supplied and reducing the air gap space. However, the TEG-RVFA led to better performance. The maximum power generated and the temperature difference between the hot and cool sides of thermoelectric modules observed at 1400 Watt and 3 cm air gap space were 1.63 Watt and 73.85℃ compared to 0.78 Watt and 58.93℃ for TEG-RHFA. The maximum power generation efficiency is 7.4% with horizontal fins and 9.1% for vertical finned absorber. This improvement is due to better heat transfer due to induced air circulation between the fins reducing heat accumulation at the base of the absorber and creating higher temperature difference between the two sides of thermoelectric modules. Therefore, TEG-RVFA is recommended for use when considering application in waste heat recovery such as furnaces and chimneys. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Power flow problems can be solved in a variety of ways by using the Newton–Raphson approach. The nonlinear power flow equations depend upon voltages V i and phase angle δ . An electrical power system is obtained by taking the partial derivatives of load flow equations which contain active and reactive powers. In this paper, we present an efficient seventh-order iterative scheme to obtain the solutions of nonlinear system of equations, with only three steps in its formulation. Then, we illustrate the computational cost for different operations such as matrix–matrix multiplication, matrix–vector multiplication, and LU-decomposition, which is then used to calculate the cost of our proposed method and is compared with the cost of already seventh-order methods. Furthermore, we elucidate the applicability of our newly developed scheme in an electrical power system. The two-bus, three-bus, and four-bus power flow problems are then solved by using load flow equations that describe the applicability of the new schemes. [ABSTRACT FROM AUTHOR]

Copyright of Automotive Engineer (1674-6546) is the property of Auto Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An oscillating water column (OWC) is designed for the extraction and conversion of wave energy into usable electrical power, rather than being a standalone renewable energy source. This review paper presents a comprehensive analysis of the mathematical modeling approaches employed in OWC systems, aiming to provide an in-depth understanding of the underlying principles and challenges associated with this innovative technology. A prominent classification within the realm of wave energy devices comprises OWC systems, which exhibit either fixed or floating configurations. OWC devices constitute a significant proportion of the wave energy converter prototypes currently operational offshore. Within an OWC system, a hollow structure, either permanently fixed or floating, extends below the water's surface, creating an enclosed chamber where air is captured over the submerged inner free surface. This comprehensive study offers a thorough assessment of OWC technology in conjunction with air turbines. Additionally, the investigation delves into theoretical, computational, and experimental modeling techniques employed for analyzing OWC converters. Moreover, this review scrutinizes theoretical, computational, and experimental modeling methodologies, providing a holistic understanding of OWC converters. Ultimately, this work contributes a thorough assessment of OWC technology's current state, accentuating its potential for efficient wave energy extraction and suggesting future research avenues. [ABSTRACT FROM AUTHOR]

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes. [ABSTRACT FROM AUTHOR]

An alkaline electrolyzer is a traditional equipment to generate hydrogen. Improving the yield of electrolyzers has recently captured much attention. In this regard, the utilization of carbon-coated nanomaterial structures is a state-of-art method. On the other hand, considering the current crisis of fossil energies, the exploitation of renewables and green technologies is necessary and unavoidable. Additionally, the design and development of integrated energy systems with two or more output products and the maximum usage of thermal losses to enhance productivity can increase the flexibility and acceptability of the energy system. In this regard, the current paper develops a framework for the performance of a new solar and biomass energies-driven multigeneration system (MGS). The main units installed in MGS are three electric energy generation units based on a gas turbine process, a solid oxide fuel cell unit (SOFCU) and an organic Rankine cycle unit (ORCU), a biomass energy conversion unit to useful thermal energy, a seawater conversion unit into useable freshwater, a unit for converting water and electricity into hydrogen energy and oxygen gas via a nanomaterial-based alkaline electrolyzer, a unit for converting solar energy into useful thermal energy (based on Fresnel collector), and a cooling load generation unit. The planned MGS has a novel structure and layout that has not been considered by researchers in previous papers. The current article is based on presenting a multi-aspect evaluation in order to investigate thermodynamic-conceptual, environmental and exergoeconomic analyzes. The outcomes indicated that the planned MGS can produce about 6.31 MW of electrical power and 0.49 MW of thermal power. Furthermore, MGS is able to produce various products such as potable water (∼0.977 kg/s), cooling load (∼0.16 MW), hydrogen energy (∼1.578 g/s) and sanitary water (∼0.957 kg/s). The overall energy and exergy productivities were measured as 78.13% and 47.72%, respectively. Also, the total investment and unit exergy costs were 47.16 USD per hour and 11.07 USD per GJ, respectively. Further, the content of carbon dioxide released from the planned system was equal to 10.59 kmol per MWh. A parametric study has been also developed to identify influencing parameters. • The nanomaterial-based alkaline electrolyzer is utilized for hydrogen production. • The system is tested by thermodynamic and environmental aspects. • The developed system was capable of generating 1.578 g/s hydrogen energy. • The content of carbon dioxide released from the planned system was less than traditional systems. [ABSTRACT FROM AUTHOR]

In electrical power systems, FACTS devices effectively control power flow and change bus voltages, leading to lower system losses and excellent system stability. The article discusses the research from the last decade that evaluated various methods for placing FACTS devices using the meta-heuristic approach to address the positioning of FACTS devices to maintain proper bus voltages and control line flow and improve the overall system efficiency. The need for more efficient electricity systems management has given rise to innovative technologies in power generation and transmission. The combined cycle power station is a good example of a new development in power generation and flexible AC transmission systems, generally known as FACTS, are controllers that improve transmission systems. Worldwide transmission systems are undergoing continuous changes and restructuring. They are becoming more heavily loaded and are being operated in ways not originally envisioned. Transmission systems must be flexible to react to more diverse generation and load patterns. In addition, the economical utilization of transmission system assets is of vital importance to enable utilities in industrialized countries to remain competitive and to survive. In developing countries, the optimized use of transmission systems investments is also important to support industry, create employment and utilize efficiently scarce economic resources. FACTS controller is a technology that responds to these needs. It significantly alters the way transmission systems are developed and controlled together with improvements in asset utilization, system flexibility and system performance. Several models and techniques suggest that devices can be placed in a particular location with different parameter settings. Finally, the optimization problem improved system performance by decreasing power loss, improving the voltage profile and power angle at each bus, raising the L-index, and minimizing generating costs. FACTS devices can increase the transmission line's capacity for transferring power by increasing the voltage at its terminals at both ends and reducing line reactance. The FACTS controller must be installed in the distribution and transmission lines to maximize the power flow. Various techniques are used for the best placement of FACTS controllers, including analytical methods, arithmetic programming approaches, meta-heuristic optimization approaches, and hybrid approaches—this paper analyses numerous analytical and meta-heuristic optimization techniques to place FACTS controllers in the most advantageous locations. The fundamental problems in intelligent power systems, such as improving stability, power quality, and managing congestion, are discussed in this study, along with several applications of FACTS devices. The cutting-edge power systems of today provide users with constant, high-quality power through smart grids and smart meters. [ABSTRACT FROM AUTHOR]

A systematic simulation model is proposed in this research paper to estimate the energy consumption of electric vehicles. The main advantage of this model is that it is made in a generic and simplified way in order to be adaptable to different electric vehicles. The overall electrical power corresponding to the performed maneuver is estimated considering: a tabular form of electric motor efficiency, mechanical power losses, a generalized efficiency map of the power electronics, the auxiliary power losses, and an electro-thermal Lithium-Ion battery pack model. The battery model was developed in a previous work, which simulates the open circuit voltage curves at different temperatures and the alteration in the internal resistance of the battery cells. The proposed model is validated with experimental data from the maneuver tests. The battery model proved high accuracy in estimating the voltage values relevant to the WLTP2 driving cycle on the chassis roller test bench. Furthermore, the mechanical and electrical power were estimated with excellent matching compared to actual test field driving test measurements, giving only the measured vehicle speed and auxiliary power losses. Finally, the state of charge change is predicted accurately along the performed test field dynamic maneuver. [ABSTRACT FROM AUTHOR]

Under-frequency load shedding (UFLS) schemes are the latest safety measures applied for safeguarding the integrity of the grid against abrupt frequency imbalances. The overall inertia of electrical power systems is expected to decrease with an increased penetration of renewable energy as well as elements connected through power electronic interfaces. However, voltage source converter-based high voltage direct current (VSC-HVDC) links can provide virtual inertia through a control loop that allows for a reaction to occur at certain frequency fluctuations. This paper evaluates a UFLS scheme that considers the injection of virtual inertia through a VSC-HVDC link. A genetic algorithm (GA) is used to determine the location of the UFLS relays, the activation threshold of each stage, the delay time and the percentage of load shedding at each stage. It was found that the virtual inertia causes the nadir to delay and sometimes reach a greater depth. Furthermore, the implemented GA approximates the frequency response to the limits set with the constraints, reducing the load shedding but achieving a steeper nadir and a lower steady-state frequency level than traditional UFLS. The simulations were performed using the IEEE 39-bus test system. [ABSTRACT FROM AUTHOR]

The interval type II fuzzy logic controller (IT2FL) is a recent artificial intelligent technology which is applied in many aspects of electrical power engineering and controlling strategies these days. The improving of Distribution Static Synchronous Compensator (DSTATCOM) control algorithms is still ongoing, because the control strategy of DSTATCOM device is considered as a decisive factor which affects the performance of DSTATCOM device in enhancing the quality of power in the distribution grids. The improving process focuses in two main aspects the DC capacitor voltage response to the control system and the mitigation of the harmonics which are produced by the controlled and uncontrolled rectified loads. In this paper, the interval type II fuzzy logic controller (IT2FL) based the Unit Voltage Template strategy (UVT) is examined by the MATLAB program with two different ranges of input signals, and compared with the type I Fuzzy logic controller (T1FL). The IT2FL based UVT shows promising results in improving the deformed shape of source current waves in comparison with the other controllers. [ABSTRACT FROM AUTHOR]

This paper explores the integration of Autonomous Mobile Robots (AMRs) in industrial settings, revolutionizing task scheduling. Focused on minimizing operational completion time, it delves into the physical processes within information systems. The study emphasizes the hardware, software, and robotics intersection, providing an overview of key AMR components and their role in task execution. Mobility, sensing capabilities, and interaction with the environment are crucial considerations for effective scheduling algorithms. Real-time data acquisition through AMR-mounted sensors informs scheduling algorithms, emphasizing the importance of accurate information. Data storage's pivotal role in maintaining efficiency is highlighted, stressing quick retrieval for rapid decision-making. The study examines central processing units (CPU) and arithmetic logic units (ALU) roles in processing scheduling algorithms, emphasizing the need for computational power. Communication processes, network communication, and data transmission reliability are paramount for coordinating multiple AMRs. Power supply and cooling systems' significance in sustaining AMR infrastructure is explored, addressing electrical power provision and environmental controls. Physical security measures and maintenance processes, including hardware and software updates, ensure peak AMR efficiency. In conclusion, this research illuminates the integral physical processes within information systems for AMR-based task scheduling, offering insights for enhanced efficiency in diverse industrial settings. [ABSTRACT FROM AUTHOR]

It has been reported that electrical engineering schools might be facing a decline in newly enrolled students combined with an increase in the number of dropouts due to motivation and engagement problems. At the same time, companies in the electric power industry require safe and realistic training environments for their trainees to reduce induction program times, costs, and accidents. Game‐based learning (GBL) applications offer alternatives in both sectors, that is, education and training, for increasing engagement, motivation, and knowledge transfer in controlled environments. This paper aims to show applications of GBL techniques towards educational and training objectives in electrical power and energy systems in the period spanning from 2002 to 2021. This review points to two main research questions: what GBL tools have been used for education and training purposes in electrical power and energy systems during 2002 to 2021? Also, what are the methodologies used for assessing the efficacy of using GBL applications in electrical power and energy systems? A structured review methodology was applied to identify how GBL has been used in electrical power and energy systems. A total of 81 papers were selected for full review. The procedure included the formulation of research questions, identification and selection of studies, and data synthesis of results. Our review showed that most GBL applications in electrical power and energy systems were developed with education purposes (63%), from which 29% used graphic user interfaces and 23% used serious games. On the other hand, for training purposes, the most popular GBL tool was virtual reality, applications of which were discussed in 56% of the reviewed papers. The review also showed that only 42% of the education papers and 37% of the training papers performed learning efficacy analyses; in which qualitative postevaluations or postsurveys were the most popular methodologies used in over 50% of those papers. [ABSTRACT FROM AUTHOR]

Due to the growth in the consumption of avocado in recent years, the amount of waste caused by avocado peel and seed has increased. Avocado waste can be transformed into valuable products such as energy, biofuels, and biological products using integrated processes in a biorefinery. This paper considers the detailed modeling, simulation, and optimization of a biorefinery for the production of phenolic compounds, bioethanol, biological xylitol, syngas, and electrical power from avocado seed and peel, using Aspen Plus in equation-oriented mode as a process simulation tool. For a biorefinery in nominal conditions, it is possible to achieve a gross profit of approximately 30 × 10 6 USD/year for capital costs of USD 31.4 × 10 6 , while the combined effect of process optimization and heat integration allows reaching a gross profit of 37 × 10 6 USD/year for capital costs of USD 30.7 × 10 6 . These results of the optimized plant show its potential to take advantage of avocado seed and peel in a profitable and sustainable way. This detailed equation-based model paves the way for superstructure optimization of a biorefinery for avocado waste processing. [ABSTRACT FROM AUTHOR]

Solar energy is an important power source. Given this, the development in the direction of converting solar radiation into electrical energy using holographic concentrators is of great importance. The purpose of the study is to determine the electrical characteristics of the solar cell inside the solar cells. To determine the electrical characteristics of the solar cell inside the photovoltaic panel, digital sensors HC-SR04, INA219 and the "Arduino Nano" microprocessor controller were used. The paper presents the results of experimental studies of a solar panel with a holographic concentrator and photovoltaic cells based on gallium arsenide. The high efficiency of converting solar energy into electrical power is shown when dispersing and focusing different wavelengths on a photocell. During elaboration of the obtained volt-ampere characteristics of solar photovoltaic conversion elements, which determine the output power of the photovoltaic panel, the high potential of the developed design of the photovoltaic panel has been revealed. The practical value of the study lies in the fact that with the help of a holographic concentrator it is possible to increase the efficiency of solar energy conversion. [ABSTRACT FROM AUTHOR]

The importance of diversified energy production lies in addressing the fuel shortage resulting from high prices, high temperatures, and environmental pollution associated with its production and consumption. Vibrational energy plays a crucial role in generating electrical power. This paper introduces a new concept based on utilizing the vibration forces of chimneys caused by wind and earthquakes. A mechatronic energy-absorbing system was designed, analyzed, and the output power was calculated using SolidWorks and Matlab programs. The design of the Regenerative Damping Chimney (RDC) primarily focuses on converting vibrations into rotational movement of the chimney, which is generated by wind forces. This is achieved by using a metal rope and pulleys to transmit motion to a set of gears. The opposite direction rotation is facilitated by bevel gears and clutches, and a planetary gearbox is employed to increase the rotation of the DC 24 V 400 W generator. The use of a high-watt generator aims to enhance energy production and the damping factor, ensuring the stability of the chimney during storms and vortex winds. The results show the efficiency of 35 % may reach 45 % watts under test to verify that the proposed system is effective and suitable for chimneys and renewable energy applications in factories and companies. [ABSTRACT FROM AUTHOR]

Advances in medical technology suggest that the application of implantable medical devices or Smart Hospital Devices (SHD) can enhance the control and treatment of chronic disorders. However, most of these developments require an electrical power source for operation, making the use of batteries unfeasible. This paper presents the design and resonance analysis of four different geometries for the fabrication of planar antennas as an alternative to a contactless power supply. Previously published software (Santiago-Amaya, López-García, Aguilar-Guggembuhl, Sánchez-Díaz, 2022) was used to calculate the electrical parameters for each coil design. Operating trials were executed under laboratory conditions, and a bracket manufactured using polylactic acid (PLA) through a 3D printer was used to accurately define the distances between coils to achieve correct alignment between them. Based on the experimental results, it was possible to calculate the resonant frequency of the inductive links at a 5 mm spacing. Similarly, it is possible to calculate the capacitive effect necessary to improve the resonant circuit in different transmitter-receiver planar antenna pairs. The most efficient combination to induce voltage in these links is to use the hexagonal profile design as a transmitter and receiver antenna, applying a sinusoidal signal with 8 MHz frequency. [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]

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]

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]

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]

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]

The virtual synchronous generator (VSG) has been widely used to improve the system inertia and damping in the renewable energy generation system. However, the in-depth understanding of VSG's stability under disturbances on different control parameters is lacked. In order to solve the problem, the small-signal model of single-VSG is established at first. The influences of key control parameters on the stability of system are analyzed by using the eigenvalue analysis method in detail. On this basis, a novel optimization strategy for control parameters is proposed based on the Particle Swarm Optimization (PSO) algorithm. The control parameters are optimized to realize excellent damping and stability of VSG system. Finally, the simulation and experimental results verify the effectiveness of stability analysis and parameter optimization strategy. [ABSTRACT FROM AUTHOR]

Fault diagnosis and detection in electrical power systems need a development of new and robust supervision structures. In the last years, different intelligent monitoring methods have been successfully proposed to deal with the problem of fault diagnosis in power transmission lines. In this work, a new hybrid strategy called FFT-FL combining Fuzzy Logic (FL) approach with Fast Fourier Transform (FFT) is proposed and applied to fault diagnosis in power line network. The elaborated fault detection structure consists of indicating whether the electrical transmission is working correctly or a fault has occurred with an effective isolation step to determine the faulty zone in the line. Whereas, an identification step consists of determining faulty phase thus fault classification in the studied line network. The novel proposed algorithm (FFT-FL) is used to improve the fault diagnosis response time and to decouple between faults and disturbances. In this paper, a comparative study is presented between the two intelligent methods for detection, isolation and identification of faults using only FL and the hybrid FFT-FL structure. The obtained simulation results verify the effectiveness and the correctness of the proposed fault method for all types of faults in the power line networks and in different zones. [ABSTRACT FROM AUTHOR]

To minimize total operating costs, emissions, and power losses, the optimum power generation and scheduling of renewable integrated hydro-thermal systems are one of the most significant objectives in short-term scheduling. The solution to these problems becomes more difficult with constraints and renewable uncertainties. The paper presents an improved cheetah optimizer (ICO) for solving the optimum wind-solar-hydro-thermal scheduling problem considering valve loading effects, ramp-rate limits, power loss, and prohibited operational zone constraints. The main objective is to optimize the total fuel cost and emissions for thermal power generators, where electric power can be fully harnessed from renewable generators. Different test systems are employed to evaluate the proposed ICO solution method's performance. The proposed ICO solution method is compared with other algorithms like grey wolf optimizer, and particle swarm optimizer, in terms of optimal fuel costs, emissions, convergence success rate, and computation time. The test systems are incorporated with wind farms, solar farm, hydropower generators, and thermal power generators scheduled for 24-h, 1-h subintervals. The simulation solutions of the renewable integrated system have been acquired by ICO, CO, GWO, and PSO. The total generation cost obtained by ICO is 0.0698%, and 0.1514% lower than the cost obtained by GWO, and PSO respectively. The total power loss was minimized by 1.8554% and 7.4002%. The total emissions can be reduced to 25% with increasing penetration of renewable energy sources. It is realized from the comparison that the proposed ICO method has the potential to provide better-quality solutions. [ABSTRACT FROM AUTHOR]

The electrical power system (EPS) has been heavily stressed due to high load demand. It operates close to the total capacity limits, resulting in voltage instability that can lead to voltage collapse. In this regard, incorporating flexible alternating current transmission system (FACTS) devices and renewable energy sources (RESs) to obtain the optimum values of the generator voltage, reactive compensation, and transformer tab in optimal reactive power dispatch (ORPD) is essential in increasing the reliability and safety of the system. ORPD involves discrete and continuous variables, which are nonlinear, noncontinuous, non-convex, and complex problems. The objective functions of ORPD are reduction in active power loss (Ploss), voltage deviation, and voltage profile enhancement. This paper presents a recent advancement of the ORPD problem, mathematical formulation of the objectives function, and a summary of various metaheuristic optimization methods (single and hybrid) used to solve the ORPD problems. The hybrid method combines two or more methods to improve the demerits of one method to obtain a quality solution to a problem. This review covered incorporating FACTS devices and RESs used in solving the ORPD problem to reduce the active Ploss and improve the voltage profile in the EPS. The benefits of FACTS devices and RESs are also discussed. Also, various metaheuristic algorithms (single, modified, and hybrid) employed to solve the ORPD problem were discussed. The future direction for researchers in this field was provided to give insight into the applicability and performance. Overall, this research explores different techniques used in solving ORPD problems from the optimization point of view to incorporating RESs and FACTS devices to obtain quality solutions. Some existing methods do not guarantee an optimum solution, but incorporating RESs and FACTS devices will help attain the best solution to the problem for better power system operation to improve system reliability and voltage profile. Based on the review journal, it can be concluded that hybrid techniques offer efficient quality solutions to the ORPD problem. [ABSTRACT FROM AUTHOR]

Electric vehicles are in vogue nowadays and it has been gaining some ground in India after Tesla entered into the Indian automobile market. Electric vehicles do not require conventional fuel sources such as fuel, oil, etc., so they do not pollute the environment. BLDC motors are used as the motor of electric vehicles, as they provide a higher speed as well as higher efficiency as compared to other motors. Since the vehicles are powered electrically, it is imperative for us to charge the vehicles just like cell phones. Just like fuel cars have fuel stations for filling up fuel for the operation of vehicles, there must also be battery charging or swapping stations for charging the battery of electric vehicles. This paper would determine how we must charge the electric vehicle using solar along with the traditional grid charging architecture. These two must work in tandem to provide the necessary electrical power to assuring the sufficiently charged battery at the swapping station for uninterrupted use of electric vehicles even in emergency cases. Here, the solar PV along with the traditional grid (Renewable and Conventional both respectively) is used to charge the battery at the swapping station, so it is named a hybrid battery swapping station (HBSS). Also, the concept of charging the battery packs in batches with scheduling is used which reduces the installation cost and the area requirement for the swapping stations compared to other existing battery swapping stations (BSS) or battery charging stations (BCS). [ABSTRACT FROM AUTHOR]

Most microelectromechanical systems (MEMS) devices require suspended structures with high metallic thickness, which is not possible with standard sputtering techniques. Electroplating-based UV LIGA is a cost-effective technique preferred for fabricating thick metallic structures. Gold is preferred as a structural material for MEMS devices such as RF switches, among other metals, due to its high conductivity and low reactivity. For electroplating, a constant current supply is applied between the cathode (electroplating wafers) and the anode (metallic mesh) dipped in gold electrolyte. The value of electric potential is determined by the constant current supply, which is determined by the plating area/current density. The standard DC current supply produces bone structures and non-uniform deposition across the wafer. The Helmholtz or electrical double layer plays a vital role in controlling the profile of the electroplated film. This paper addresses the issues of non-uniform deposition and bone structures with agitation, wafer rotation and bipolar pulsed power supply. [ABSTRACT FROM AUTHOR]