Search Results (49)

Island electrical networks often face stability and resilience issues due to their weakly meshed structure, which lowers system inertia and compromises supply continuity. This challenge is further intensified by the increasing integration of renewable energy sources, promoted by decarbonization goals, whose intermittent and variable nature complicates grid stability management. To address this, Red Eléctrica de España—the transmission system operator of Spain—has planned several improvements in the Canary Islands, including the installation of new wind farms and a second transmission circuit on the island of La Palma. This new infrastructure will complement the existing one and ensure system stability in the event of N-1 contingencies. This article evaluates the stability of the island’s electrical network through dynamic simulations conducted in PSS^®E, analyzing four distinct fault scenarios across three different grid configurations (current, short-term upgrade and long-term upgrade with wind integration). Generator models are based on standard dynamic parameters (WECC) and calibrated load factors using real data from the day of peak demand in 2021. Results confirm that the planned developments ensure stable system operation under severe contingencies, while the integration of wind power leads to a 33% reduction in diesel generation, contributing to improved environmental and operational performance. Full article

In a smart microgrid (SMG) system that deals with unpredictable loads and incorporates fluctuating solar and wind energy, it is crucial to have an efficient method for controlling frequency in order to balance the power between generation and load. In the last decade, cyberattacks have become a growing menace, and SMG systems are commonly targeted by such attacks. This study proposes a framework for the frequency management of an SMG system using an innovative combination of a smart controller (i.e., the Fuzzy Logic Controller (FLC)) with three conventional cascaded controllers, including Fractional-Order PI (FOPI), Tilt Integral Fractional Derivative (TID^μ), and Proportional Integral Derivative Acceleration (PIDA). The recently released Eel and Grouper Optimization (EGO) algorithm is used to fine-tune the parameters of the proposed controller. This algorithm was inspired by how eels and groupers work together and find food in marine ecosystems. The Integral Time Squared Error (ITSE) of the frequency fluctuation (ΔF) around the nominal value is used as an objective function for the optimization process. A diesel engine generator (DEG), renewable sources such as wind turbine generators (WTGs), solar photovoltaics (PVs), and storage components such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) are all included in the SMG system. Additionally, electric vehicles (EVs) are also installed. In the beginning, the supremacy of the adopted EGO over the Gradient-Based Optimizer (GBO) and the Smell Agent Optimizer (SAO) can be witnessed by taking into consideration the optimization process of the recommended regulator’s parameters, in addition to the optimum design of the membership functions of the fuzzy logic controller by each of these distinct algorithms. The subsequent phase showcases the superiority of the proposed EGO-based FFOPI-TID^μ-PIDA structure compared to EGO-based conventional structures like PID and EGO-based intelligent structures such as Fuzzy PID (FPID) and Fuzzy PD-(1 + PI) (FPD-(1 + PI)); this is across diverse symmetry operating conditions and in the presence of various cyberattacks that result in a denial of service (DoS) and signal transmission delays. Based on the simulation results from the MATLAB/Simulink R2024b environment, the presented control methodology improves the dynamics of the SMG system by about 99.6% when compared to the other three control methodologies. The fitness function dropped to 0.00069 for the FFOPI-TID^μ-PIDA controller, which is about 200 times lower than the other controllers that were compared. Full article

To investigate the mechanisms of unexpected failures in a multi-stage gear transmission system under a relatively low load, a rigid–flexible coupled multi-body dynamics model with 10 spur gears and 12 helical gears is established. The dynamic condensation theory is applied to improve computational efficiency. The construction of this model incorporates critical nonlinear factors, ensuring high precision and reliability. Based on the proposed model, four critical dynamic parameters, including acceleration, mesh stiffness, dynamic transmission error, and vibration displacement, are analyzed. This research systematically reveals the nonlinear dynamic mechanism under the multi-gear coupling effect. The spectrum of the gears exhibits prominent low-frequency peaks at 320 Hz and 750 Hz. Notably, alternate load-dominated gears show a shift in prominent low-frequency peaks. The phenomenon of marked oscillations in mesh stiffness suggests a potential risk of localized weakening in the system’s load-carrying capacity. Critically, alternating torques induce periodic double-tooth contact regions in the gear at specific time points (0.115 s and 0.137 s), which are identified as critical factors leading to gear transmission system failures. The variation characteristics of the dynamic transmission error (DTE) demonstrate that the DTE is strongly correlated with the meshing state. The analysis of vibration displacement further indicates that the alternating external loads are the dominant excitation source of vibrations, noise, and failures in the gear transmission system. Full article

The motor drive system is pivotal for vehicles, particularly in new energy applications. However, conventional hybrid systems, which combine generator sets and single batteries in parallel configurations, fail to meet the operational demands of large pure electric mining dump trucks under fluctuating power requirements—such as high reserve power during acceleration and robust energy recovery during braking. Traditional single-motor configurations struggle to balance low-speed, high-torque operations and high-speed driving within cost-effective ranges, often necessitating oversized motors or multi-gear transmissions. To address these challenges, this paper proposes a dual-motor symmetric powertrain configuration with a seven-speed gearbox, tailored to the extreme operating conditions of mining environments. By integrating a high-speed, low-torque motor and a low-speed, high-torque motor through dynamic power coupling, the system optimizes energy utilization while ensuring sufficient driving force. The simulation results under extreme conditions (e.g., 33% gradient climbs and heavy-load downhill braking) demonstrate that the proposed configuration achieves a peak torque of 267 kNm (200% improvement over single-motor systems) and a system efficiency of 92.4% (vs. 41.7% for diesel counterparts). Additionally, energy recovery efficiency reaches 85%, reducing energy consumption to 4.75 kWh/km (83% lower than diesel trucks) and life cycle costs by 38% (USD 5.34/km). Field tests in open-pit mines validate the reliability of the design, with less than a 1.5% deviation in simulated versus actual performance. The modular architecture supports scalability for 60–400-ton mining trucks, offering a replicable solution for zero-emission mining operations in high-altitude regions, such as Tibet’s lithium mines, and advancing global efforts toward carbon neutrality. Full article

This paper investigates the application of high-capacity supercapacitors in railway systems, with a particular focus on their role in energy recovery during braking processes. The study highlights the potential for significant energy savings by capturing and storing energy generated through electrodynamic braking. Experimental measurements conducted on a diesel–electric multiple unit revealed that approximately 28.3% to 30.5% of the energy could be recovered from the traction network, regardless of the type of drive used—whether electric or diesel. This research also explores the integration of starch-based carbon as an electrode material in supercapacitors, offering an innovative, sustainable alternative to traditional graphite or graphene electrodes. The carbon material was obtained through a simple carbonization process, with experimental results demonstrating a material capacity of approximately 130 F/g. To quantify the energy recovery, calculations were made regarding the mass and power requirements of the supercapacitors. For the tested vehicle, it was estimated that around 28.7% of the energy could be recovered during the braking process. To store 15 kWh of energy, the total mass of the capacitors required is approximately 245.1 kg. The study emphasizes the importance of increasing voltage levels in railway systems, which can enhance energy transmission and utilization efficiency. Additionally, the paper discusses the necessity of controlled energy discharge, allowing for the flexible management of energy release to meet the varying power demands of trains. By integrating high-voltage supercapacitors and advanced materials like starch-based carbon, this research paves the way for more sustainable and efficient railway systems, contributing to the industry’s goals of reducing emissions and improving operational performance. The findings underscore the crucial role of these capacitors in modernizing railway infrastructure and promoting environmentally responsible transportation solutions. Full article

This article studies the transformation and assembly process of the Volkswagen (VW) Crafter from conventional to hybrid vehicle of the department of vehicles engineering, University of Debrecen, and uses a computer-aided simulation (CAS) to design the vehicle based on the real measurement data (hardware-in-the-loop, HIL method) obtained from an online CAN bus data measurement platform using MATLAB/Simulink/Simscape and LabVIEW software. The conventional vehicle powered by a 6-speed manual transmission and a 4-stroke, 2.0 Turbocharged Direct Injection Common Rail (TDI CR) Diesel engine and the transformed hybrid electrified powertrain are designed to compare performance. A novel methodology is introduced using Netcan plus 110 devices for the CAN bus analysis of the vehicle’s hybrid version. The acquired raw CAN data is analyzed using LabVIEW and decoded with the help of the database (DBC) file into physical values. A classical proportional integral derivative (PID) controller is utilized in the hybrid powertrain system to manage the vehicle consumption and CO₂ emissions. However, the intricate nonlinearities and other external environments could make its performance unsatisfactory. This study develops the energy management strategies (EMSs) on the basis of enhanced proportional integral derivative-based genetic algorithm (GA-PID), and compares with proportional integral-based particle swarm optimization (PSO-PI) and fractional order proportional integral derivative (FOPID) controllers, regulating the vehicle speed, allocating optimal torque and speed to the motor and engine and reducing the fuel and energy consumption and the CO₂ emissions. The integral time absolute error (ITAE) is proposed as a fitness function for the optimization. The GA-PID demonstrates superior performance, achieving energy efficiency of 90%, extending the battery pack range from 128.75 km to 185.3281 km and reducing the emissions to 74.79 gCO₂/km. It outperforms the PSO-PI and FOPID strategies by consuming less battery and motor energy and achieving higher system efficiency. Full article

During the operation of any source of electrical energy, thermal energy is also generated. The heating of generator parts is accompanied by the loss of the efficiency of the entire system as a whole and eventually leads to failure. In order to remove the heat load from generators based on renewable energy, such as wind turbines and solar panels, it is possible to use heat pumps based on various refrigerants. This article presents a comparative analysis of methods for evaluating the efficiency of the technological process, using the example of increasing the efficiency of the heat pump based on the heat produced by renewable energy installations. An example of improving the efficiency of a laboratory stand is used. Exergetic calculation, fluid selection, an analysis of external sources and emission reduction were performed. This thermal energy transmission system uses a solar panel as an additional low-potential source of heat. Options for increasing the energy efficiency of the installation are considered. An assessment of the reduction in emissions when using an equivalent diesel power plant was carried out using the developed mathematical model. Full article

Marine diesel engines are the preferred power equipment for ships and are the most important component among the numerous electromechanical devices on board. Accidents involving these engines can potentially cause immeasurable damage to the vessel, making fault detection in marine diesel engines crucial. This design enables the detection and reporting of faults in marine diesel engines at the earliest possible time through the computation of convolutional neural networks, which is of great significance for ensuring the safe navigation of ships. For this functionality, the Xilinx ZYNQ-7000 XC7Z010 is selected as the main control chip, and the LoRa wireless network is used as the transmission module. The FreeRTOS embedded operating system is ported, with sensor data collection completed on the PS side of the ZYNQ chip and algorithm acceleration calculations on the PL side. Data are then transmitted to the host computer via the LoRa module paired with a custom protocol. Experimental test results show that the program provides stable data transmission, with each module of the algorithm generally accelerating by more than 95% and an accuracy rate of 92.86%. Additionally, the host computer can display the received data in real time. The custom protocol’s header also allows for precise judgments about the completeness and origin of messages, facilitating the expansion of other SOC’s message uplink and the host computer’s message downlink. Full article

Recently, environmental regulations have been strengthened due to climate change. This change comes in a way that limits emissions from ships in the shipbuilding industry. According to these changes, the trend of ship construction is changing installing pollutant emission reduction facilities such as scrubbers or applying alternative fuels such as low sulfur oil and LNG to satisfy rule requirements. However, these changes are focused on large ships. Small ships are limited in size. So, it is hard to install large facilities such as scrubbers and LNG propulsion systems, such as fishing boats that require operating space. In addition, in order to apply the pure electric propulsion method, there is a risk of marine distress during battery discharge. Therefore, the application of the electric–diesel hybrid propulsion method for small ships is being studied as a compromised solution. Since hybrid propulsion uses various energy sources, a method that can estimate effective efficiency is required for efficient operation. Therefore, in this study, a Bond graph is used to model the various energy sources of hybrid propulsion ships in an integrated manner. Furthermore, based on energy system modeling using the Bond graph, the study aims to propose a method for finding the optimal operational scenarios and reduction ratios for the entire voyage, considering the navigation feature of each different maritime region. In particular, the reduction gear is an important component at the junction of the power transmission of the hybrid propulsion ship. It is expected to be useful in the initial design stage as it can change the efficient operation performance with minimum design change. Full article

Diesel particulate matter is one of the most dangerous environmental stressors affecting human health. Many plant-derived compounds with antioxidant and anti-inflammatory properties have been proposed to protect the skin from pollution damage. Curcumin (CUR) has a plethora of pharmacological activities, including anticancer, antimicrobial, anti-inflammatory and antioxidant. However, it has low bioavailability due to its difficult absorption and rapid metabolism and elimination. CUR encapsulation in nanotechnological systems and its combination with biopotentiators such as piperine (PIP) can improve its pharmacokinetics, stability and activity. In this study, ethosomes (ETs) were investigated for CUR and PIP delivery to protect the skin from damage induced by diesel particulate matter. ETs were produced by different strategies and characterized for their size distribution by photon correlation spectroscopy, for their morphology by transmission electron microscopy, and for their drug encapsulation efficiency by high-performance liquid chromatography. Franz cells enabled us to evaluate in vitro the drug diffusion from ETs. The results highlighted that ETs can promote the skin permeation of curcumin. The studies carried out on their antioxidant activity demonstrated an increase in the antioxidant power of CUR using a combination of CUR and PIP separately loaded in ETs, suggesting their possible application for the prevention of skin damage due to exogenous stressors. Ex vivo studies on human skin explants have shown the suitability of drug-loaded ETs to prevent the structural damage to the skin induced by diesel engine exhaust exposure. Full article

A distributed-power-generating source (DPGS) is intended to locally supply the increased power demand at a load bus. When applied in small amounts, a DPGS offers many technical and economic benefits. However, with large DPGS penetrations, the stability of the transmission system becomes a significant issue. This paper investigates the stability of a transmission system equipped with a DPGS at load centres supplying power to both a constant power (CP) and induction motor (IM) load. The DPGSs considered in the present study are microturbine and diesel turbine power generators (MTGS and DTGS), both interfaced with synchronous generators. The influence of an IM load supplied by the DPGS on small-signal stability is studied by a critical damping ratio analysis. On the other hand, time-domain indicators of the transient response following a short circuit are employed in the analysis. Further, a variance analysis test (VAT) is performed to determine the contribution of IM and CP loads on the system stability. The study revealed that large penetration levels of IM loads significantly affect the stability and depend on the kind of DPGS technology used. Full article

In a smart grid (SG) system with load uncertainties and the integration of variable solar and wind energies, an effective frequency control strategy is necessary for generation and load balancing. Cyberattacks are emerging threats, and SG systems are typical cyber-attack targets. This work suggests an improved gorilla troops optimizer (iGTO)-based fuzzy PD-(1+PI) (FPD-(1+PI)) structure for the frequency control of an SG system. The SG contains a diesel engine generator (DEG), renewable sources like wind turbine generators(WTGs), solar photovoltaic (PV), and storage elements such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) in conjunction with electric vehicles (EVs). Initially, the dominance of the projected iGTO over the gorilla troops optimizer (GTO) and some recently suggested optimization algorithms are demonstrated by considering benchmark test functions. In the next step, a traditional PID controller is used, and the efficacy of the GTO method is compared with that of the GTO, particle swarm optimization (PSO), and genetic algorithm (GA) methods. In the next stage, the superiority of the proposed FPD-(1+PI) structure over fuzzy PID (FPID) and PID structures is demonstrated under various symmetry operating conditions as well as under different cyberattacks, leading to a denial of service (DoS) and delay in signal transmission. Full article

Hybrid power systems based on renewable energy sources and diesel generators are efficient solutions for supplying electricity to remote and off-grid locations. One of the most crucial problems in hybrid power systems is frequency regulation, which is established by balancing the supplied power with the load demand using the load frequency control approach. Since most feedback signals are analog and the control setups are digital, the resulting control system is a sampled-data system, which requires careful designs for both the control law and the sampling frequency to guarantee closed-loop stability. This paper is concerned with the state-feedback load frequency regulation for hybrid wind–diesel power systems under event-triggered implementation. It is assumed that the full state measurement is available for feedback and that sensors and controllers communicate over a shared digital network. To mitigate the communication load on the network, an event-triggering mechanism is constructed by emulation, based on the time-regularization principle in the sense that each consecutive triggering instant is speared by a specified minimum dwell time. The closed-loop system is described as a hybrid dynamical system to account for mixed dynamical behaviors naturally arising in networked control systems. By means of appropriate Lyapunov functions, the closed-loop stability is ensured under the proposed triggering rule. Moreover, the enforced dwell time between transmissions ensures that the accumulation of sampling times is prevented, which is crucial for the event-triggering condition to be implementable in practice. The required conditions to apply this technique are derived in terms of a linear matrix inequality. Numerical simulations on an isolated hybrid power system were implemented to demonstrate the efficiency of the proposed method. Comparative simulations with relevant techniques in the literature were carried out, which showed that the proposed approach can produce fewer transmission numbers over the network. Full article

This paper presents case studies for replacing diesel generators (DGs) that are used as the main and emergency power sources for alternating current (AC) auxiliary services in substations (SS) within the transmission network (voltage greater than or equal to 230 kV). The objective of this research is to present a solution that is more reliable, environmentally friendly, and financially viable than DGs. To achieve this, the proposed solutions incorporate Battery Energy Storage Systems (BESSs) with or without the integration of Photovoltaic (PV) Systems. These solutions were simulated using the HOMER PRO Version 3.14.5 software for the Messias SS /AL, and the results were analyzed and compared to the DG in terms of reliability, financial viability, and environmental impact. Based on the conducted analyses, the BESS solution with the PV system was found to be the most suitable for the main source. However, in the case of the emergency source, if one of the main sources is a DG/BESS, maintaining the emergency DG is the preferable option. If both main sources are independent, the BESS solution with the PV system is a suitable solution. Full article

The article concerns the issue of retrofitting (i.e., the conversion of worn-out diesel buses into electric buses). As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses. Full article