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This paper considers a single-machine scheduling problem with sequence-dependent setup times and energy-generation and storage systems. Each job requires a sequence-dependent setup to be processed on the machine, and both setup and processing of the job require job-dependent amounts of energy. The energy consumed by the machine can be bought from an Electric Power Company (EPC) or generated by own Distributed Energy Resource (DER), such as solar photovoltaic or wind, and the energy can be stored in an Energy Storage System (ESS). The objective is to minimise the total cost, the sum of production cost depending on makespan and energy cost by considering energy usage from the EPC, DER and ESS. For the problem, a mathematical programming model is first derived by using period-based indexes. Then, a hybrid genetic algorithm, which adds appropriate idle times between jobs and determines an efficient energy schedule by storing some energy during less expensive periods into the ESS for later use in high-price periods, is developed. Finally, computational experiments show that the proposed algorithm provides effective solutions, and which component of the total cost affects the performance the most, how effective adding idle times between jobs is, and how much cost can be saved by having a DER and ESS. [ABSTRACT FROM AUTHOR]

Safety mishaps at electric power construction sites have been more frequent in recent years as a result of the growth of the electric power business, the inescapable carelessness of current safety oversight, and other causes. Traditional manual supervision and video surveillance methods demand a lot of human resources and suffer from issues like low efficiency and lack of objectivity, making it unable to provide security alerts in real-time and accurately. Therefore, solutions like intelligent monitoring based on object detection are required to address this issue. Many object detection methods now in use (such as R-CNN, Fast R-CNN, and YOLOV5) are computationally and energy intensive. They are typically installed on remote back-end servers, which makes it impossible to guarantee the real-time security alert. This paper trains a lightweight NanoDet network model to recognize the attire and actions of power construction workers in order to address the aforementioned issues. Additionally, in order to meet the real-time security warning requirements and fully utilize the limited computing resources of edge devices, the NanoDet network model is divided, with some layers being divided into CPU execution. According to experiments, power consumption can be reduced by deploying the Backbone or PAFPN blocks of the NanoDet model to CPUs and running them in 30W4Core mode. [ABSTRACT FROM AUTHOR]

The growing demand for electricity in long-duration space missions has become a pressing concern. The space nuclear closed-Brayton-cycle (CBC) power generation system offers advantages in power output, operational lifespan, and range. However, a significant speed disparity exists between its compressor and alternator. To address this challenge, this paper proposes a double-rotor CBC configuration. A corresponding dynamic model that couples the nuclear reactor and radiator is formulated, and dynamic analysis is conducted to facilitate system control. The study delves into the dynamic start-up process of the double-rotor CBC system and examines how various component parameters impact its power generation performance. The findings indicate that through the introduction of suitable reactivity to regulate reactor power and the incorporation of a PID controller to manage flow distribution between two turbines, the system can achieve start-up within 5200 s. Moreover, the innovative double-rotor structure suggested in this paper enables the separation of compressor and alternator speeds. Consequently, the compressor and alternator can operate within their optimal speed ranges independently, which is a feature that holds potential benefits for the system's practical implementation. In addition, the steady-state operation of the system showcases the recuperator's heat transfer power at around 1127.60 kW, a parameter of significant importance. Following steady-state operation, the double-rotor CBC system demonstrated an electrical power output of 175.99 kW and a thermal efficiency of 32.38%. [ABSTRACT FROM AUTHOR]

For ultra‐high‐voltage (UHV) systems together with high‐voltage facilities, more rationalized insulation coordination and equipment design are required. To this end, making large‐scale and long‐term field lightning‐strike observations, large amount of and practical experiments, and introducing new analysis techniques have enabled the development of advanced technologies capable of transforming conventional techniques. This paper reviews what has been developed in a Japanese electric power company in this regard. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Currently, there are strong and sustained growth trends observed in multi-disciplinary industrial technologies such as building-integrated photovoltaics and agrivoltaics, where renewable energy production is featured in building envelopes of varying degrees of transparency. Novel glass products can provide a combination of thermal energy savings and solar energy harvesting, enabled by either patterned-semiconductor thin-film energy converters on glass substrates, or by using luminescent concentrator-type approaches to achieve high transparency. Significant progress has been demonstrated recently in building integrated solar windows featuring visible light transmission of up to 70%, with electric power outputs of up to Pmax ~ 30–33 Wp/m2. Several slightly different designs were tested during 2021–2023 in a greenhouse installation at Murdoch University in Perth, Western Australia; their long-term energy harvesting performance differences were found to be on the scale of ~10% in wall-mounted locations. Solar greenhouse generated electricity at rates of up to 19 kWh/day, offsetting nearly 40% of energy costs. The objective of this paper is to report on the field performance of these PV windows in the context of agrivoltaics and to provide some detail of the performance differences measured in several solar window designs related to their glazing structure materials. Methods for the identification and quantification of long-term field performance differences and energy generation trends in solar windows of marginally different design types are reported. The paper also aims to outline the practical application potential of these transparent construction materials in built environments, focusing on the measured renewable energy figures and seasonal trends observed during the long-term study. [ABSTRACT FROM AUTHOR]

Subsea oil and gas (O&G) exploration demands significantly high power to supply the electrical loads for extraction and pumping of the oil and gas. The energy demand is usually met by fossil fuel combustion-based platform generation, which releases a substantial volume of greenhouse gases including carbon dioxide (CO2) and methane into the atmosphere. The severity of the resulting adverse environmental impact has increased the focus on more sustainable and environment-friendly power processing for deepwater O&G production. The most feasible way toward sustainable power processing lies in the complete electrification of subsea systems. This paper aims to dive deep into the technology trends that enable an all-electric subsea grid and the real-world challenges that hinder the proliferation of these technologies. Two main enabling technologies are the transmission of electrical power from the onshore electrical grid to the subsea petroleum installations or the integration of offshore renewable energy sources to form a microgrid to power the platform-based and subsea loads. This paper reviews the feasible power generation sources for interconnection with subsea oil installations. Next, this interconnection's possible power transmission and distribution architectures are presented, including auxiliary power processing systems like subsea electric heating. As the electrical fault is one of the major challenges for DC systems, the fault protection topologies for the subsea HVDC architectures are also reviewed. A brief discussion and comparison of the reviewed technologies are presented. Finally, the critical findings are summarized in the conclusion section. [ABSTRACT FROM AUTHOR]

Synchronization is one of the key issues in three-phase AC power systems. Its characteristics have been dramatically changed with the large-scale integration of power-electronic-based renewable energy, mainly including a permanent magnetic synchronous generator (PMSG) and a double-fed induction generator (DFIG) for wind energy and a photovoltaic (PV) generator for solar energy. In this paper, we review recent progresses on the synchronization stability and multi-timescale properties of the renewable-dominated power system (RDPS), from nodes and network perspectives. All PMSG, DFIG, and PV are studied. In the traditional synchronous generator (SG) dominated power system, its dynamics can be described by the differential–algebraic equations (DAEs), where the dynamic apparatuses are modeled by differential equations and the stationary networks are described by algebraic equations. Unlike the single electromechanical timescale and DAE description for the SG-dominated power system, the RDPS dynamics should be described by the multiscale dynamics of both nodes and networks. For three different timescales, including the AC current control, DC voltage control, and rotor electromechanical timescales, their corresponding models are well established. In addition, for the multiscale network dynamics, the dynamical network within the AC current control timescale, which should be described by differential equations, can also be simplified as algebraic equations. Thus, the RDPS dynamics can be put into a similar DAE diagram for each timescale to the traditional power system dynamics, with which most of power electrical engineers are familiar. It is also found that the phase-locked loop for synchronization plays a crucial role in the whole system dynamics. The differences in the synchronization and multiscale characteristics between the traditional power system and the RDPS are well uncovered and summarized. Therefore, the merit of this paper is to establish a basic physical picture for the stability mechanism in the RDPS, which still lacks systematic studies and is controversial in the field of electrical power engineering. [ABSTRACT FROM AUTHOR]

Hybrid renewable power generation becomes essential in most of electric power networks. Battery storage is commonly used in renewable energy systems (RESs) with distributed generation, such as solar and wind energy systems, to reduce power fluctuations caused by the intermittent behavior of renewable energy sources. A battery has been connected with the dc grid through a dc–dc bi-directional converter. The control scheme of the dc–dc bi-directional converter (BDC) is having two controlled loops. One is voltage-controlled loop, and another is the current-controlled loop. In this work, two-degree-of-freedom fractional order proportional integral derivative + proportional integral controller (2-DOF FOPID + PI) is proposed and applied in the voltage-controlled loop to stabilize the dc bus voltage and power flow effectively for both islanded mode and grid-connected mode. A novel meta-heuristic algorithm, i.e., modified sine cosine algorithm (m-SCA), is used to tune the controller parameters of the proposed controller. To test the performance of the modified SCA algorithm, various well-known uni-modal and multi-modal benchmark functions are taken in this paper. To confer the viability of the proposed controller, its performance is compared with other literature-based conventional controllers. This paper presents time-domain analysis, stability, and robustness test to illustrate the effectiveness of the proposed controller. MATLAB/Simulink has been used for computational work to analyze the system's efficiency. Finally, the proposed technique is validated by using OPAL-RT platform (Opal-RT-OP4510 model) with the power management of RES (PV and wind) and battery energy storage. Experimental work proved the effectiveness of the proposed m-SCA optimized 2-DOF FOPID + PI controller. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of winter temperatures in Norway and northern Sweden, covering a period of 50 to 70 years. The analysis utilizes Singular Spectrum Analysis (SSA) to investigate temperature trends at six selected locations. The results demonstrate an overall long-term rise in temperatures, which can be attributed to global warming. However, when investigating variations in highest, lowest, and average temperatures for December, January, and February, 50% of the cases exhibit a significant decrease in recent years, indicating colder winters, especially in December. The study also explores the variations in Atlantic Meridional Overturning Circulation (AMOC) variations as a crucial climate factor over the last 15 years, estimating a possible 20% decrease/slowdown within the first half of the 21st century. Subsequently, the study investigates potential similarities between winter AMOC and winter temperatures in the mid to high latitudes over the chosen locations. Additionally, the study examines another important climatic index, the North Atlantic Oscillation (NAO), and explores possible similarities between the winter NAO index and winter temperatures. The findings reveal a moderate observed lagged correlation for AMOC-smoothed temperatures, particularly in December, along the coastal areas of Norway. Conversely, a stronger lagged correlation is observed between the winter NAO index and temperatures in northwest Sweden and coastal areas of Norway. Thus, NAO may influence both AMOC and winter temperatures (NAO drives both AMOC and temperatures). Furthermore, the paper investigates the impact of colder winters, whether caused by AMOC, NAO, or other factors like winds or sea ice changes, on electrical power and energy systems, highlighting potential challenges such as reduced electricity generation, increased electricity consumption, and the vulnerability of power grids to winter storms. The study concludes by emphasizing the importance of enhancing the knowledge of electrical engineering researchers regarding important climate indices, AMOC and NAO, the possible associations between them and winter temperatures, and addressing the challenges posed by the likelihood of colder winters in power systems. [ABSTRACT FROM AUTHOR]

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A Lead-Cooled Fast Reactor (LFR) is one of the six advanced fourth-generation reactors that many countries have been interested in designing, constructing, or develop them in the world. ALFRED reactor design investigated in this paper has 125 (MW) electric power and is being cooled by lead. The main purpose of the ALFRED project is to design and construct a reactor with high safety performance and reliability in all operation modes. In the present study, Monte Carlo codes MCNPX and SuperMC are used to calculate the neutronic parameters of the ALFRED reactor core including effective multiplication factor, kinetic parameters, neutron flux, and power distribution based on the latest design data. According to the results, the insertion of the control rods into the core can move the maximum flux height of about 40% to 50% to the end. Also, comparing codes' results show an appropriate consistency. [ABSTRACT FROM AUTHOR]

Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time series of the leakage current of contaminated insulators. In a controlled high-voltage laboratory simulation, 15 kV-class insulators from an electrical power distribution network were exposed to increasing contamination in a salt chamber. The leakage current was recorded over 28 h of effective exposure, culminating in a flashover in all considered insulators. This flashover event served as the prediction mark that this paper proposes to evaluate. The proposed method applies the Christiano–Fitzgerald random walk (CFRW) filter for trend decomposition and the group data-handling (GMDH) method for time series prediction. The CFRW filter, with its versatility, proved to be more effective than the seasonal decomposition using moving averages in reducing non-linearities. The CFRW-GMDH method, with a root-mean-squared error of 3.44 × 10 − 12 , outperformed both the standard GMDH and long short-term memory models in fault prediction. This superior performance suggested that the CFRW-GMDH method is a promising tool for predicting faults in power grid insulators based on leakage current data. This approach can provide power utilities with a reliable tool for monitoring insulator health and predicting failures, thereby enhancing the reliability of the power supply. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China's electricity consumption, this paper analyzes the data characteristics of China's electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China's power demand from 2004 to 2019, the ARMA time series model is used to analyze China's future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China's electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China's power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China's power. [ABSTRACT FROM AUTHOR]

The development of more electric aircrafts (MEA) and all electric aircrafts (AEA) inevitably implies an increase in electric power and a consequent increase in distribution voltage levels. Increased operating voltages coupled with low pressure in some areas of the aircraft greatly increase the chances of premature insulation failure. Insulation failure manifests itself as surface discharges, arc tracking, arcing, and disruptive or breakdown discharges, in order of increasing severity. Unfortunately, on-board electrical protections cannot detect discharges at an early stage, so other strategies must be explored. In their early stage, insulation faults manifest as surface and corona discharges. They generate optical radiation, mainly in the near-ultraviolet (UV) and visible spectral regions. This paper focuses on a method to detect the discharges, locate the discharge sites, and determine their intensity to facilitate predictive maintenance tasks. It is shown that by using small size and low-cost image sensors, it is possible to detect, locate, and quantify the intensity of the discharges. This paper also proposes and evaluates the behavior of a discharge severity indicator, which is based on determining the intensity of digital images of the discharges, so it can be useful to apply predictive maintenance tasks. The behavior and accuracy of this indicator has been tested in the laboratory using a low-pressure chamber operating in the pressure range of 10–100 kPa, which is characteristic of aircraft applications, analyzing a needle-plane air gap geometry and using an image sensor. The proposed method can be extended to other applications where electrical discharges are an issue. [ABSTRACT FROM AUTHOR]

Smart electric grids are practising flexible, reliable and robust operations during delivery and consumption of power. However, these grids are highly vulnerable to a wide range of cyber attacks due to the deployment of an extensive communication network. In this paper, the nature of cyber attack on given power system based on proposed cyber attack models and theorems is analysed by utilizing steady state voltage stability (L index). Further, a cyber attack factor is introduced which may mislead the bus voltage stability virtually. The proposed cyber attack models and theorems are validated by executing cyber attacks on WSCC 9 bus and IEEE 14 bus test systems by using Siemens PSS/E and MATLAB softwares. Through the proposed theorems, the paper exposes and quantifies the threat of cyber attacks in the electric power grid. The simulation results reveal that the proposed cyber attack models may misrepresent the bus voltage stability, thereby misleading the energy management centre (EMC) operator into taking incorrect countermeasures. The above incorrect actions may force voltage instability which further leads to major interruptions in the electric power supply and possible cascading failure of the electric power grid. Moreover, the proposed theorems and rigorous simulations presented in the paper support the EMC operator in intelligently identifying a cyber attack, thereby enabling development of appropriate corrective actions during such cyber attacks on the smart electric grid. Thus, the concept of proposed methodology could best assist the power system operator to build detection algorithms for discrimination of cyber attacks from electrical faults towards strong electric grid resilience character. [ABSTRACT FROM AUTHOR]

Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper. [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]