Electrical Circuit Research Articles

Dynamics and energy harvesting from parametrically coupled self-excited electromechanical oscillator

The investigated parametrically coupled electromechanical structure is composed of a mechanical Duffing oscillator whose mass sits on a moving belt surface. The driving electrical network is a van der Pol oscillator whose aim is to actuate the attached DC motor to provide some rotatry unbalances and parametric coupling in the vibrating structure. The coupled oscillator is applied to energy harvesting and overcomes the limitation of low energy generation associated with a single oscillator of this kind. The system was solved analytically and validated by numerical methods. The global dynamics of the structure were investigated, and nonlinear phenomena such as Neimark–Sacker bifurcation, discontinuity-induced bifurcation, grazing–sliding, and bifurcation to multiple tori were identified. These nonlinear behaviors affect the harvested energy at bifurcation points, resulting in jumps from one energy level to another. In addition to harnessing the highest energy under hard parametric coupling, the coupling ensures that higher and more useful energy is harvested over a wider range of belt speeds. Finally, the qualitative validation of the numerical concept by experimental setup verifies the workings of the model.

Simulation Of Electrical Load With An Over Load System Shedding

A break in one of the circuits in a double circuit transmission network system can cause the system to overload. Where excess load on the transmission network system can cause quite dangerous impacts. The Over Load Shedding system is a protection system for the electric power transmission network which aims to prevent widespread blackouts by removing certain predetermined loads. By using the Arduino Mega 2560 as a control center, security against load abnormalities can be carried out and can be monitored automatically using Scada, apart from that, PMT taping for load balancing can also be done using Scada. The Arduino Mega 2560 will read the current on each phase wire using the ACS712 current sensor to detect the load of one of the circuits to be aware of whether it is overloaded or not. This simulator tool has carried out several measurements and tested how to operate it. This tool has a fairly high level of work accuracy, reaching 85% success in operation. So it is hoped that this tool can provide knowledge to the wider community about over load shedding systems in maintaining the electric power transmission system properly and easily to understand.

Integration of photovoltaic systems in Algeria's building electrical network: technical and financial analysis

This extensive study offers a thorough analysis of the complex technical and economical factors involved in incorporating photovoltaic (PV) systems into the buildings' electrical grid in Algeria. It focuses on a crucial element in the country's energy transition. This study aims to evaluate the viability and potential advantages of implementing solar panels on the rooftop of a university parking lot located at the prestigious Faculty of Electrical Engineering of the University of Sidi Bel Abbess. By utilising advanced modelling tools such as PVSOL and HOMER Pro, this study applies a comprehensive methodology to assess the feasibility of this facility. In the first step, a comprehensive three-dimensional model is carefully constructed using PVSOL software in order to assess the maximum achievable photovoltaic (PV) capacity for the neighbouring parking lot. This estimation considers several parameters, including potential shadows, size of furniture, direction, and slope. This thorough assessment establishes the foundation for subsequent examinations. Following this, a thorough technical-economic analysis is performed using HOMER Pro software to comprehensively evaluate the advantages and disadvantages of two separate scenarios: one that exclusively depends on the current electrical network and another that combines conventional grid power with solar-generated electricity. The study offers useful insights into the economic feasibility and sustainability of incorporating photovoltaic (PV) systems into the university's infrastructure, taking into account several aspects such as installation costs, maintenance requirements, electricity rates, and possible savings. The results highlight the considerable potential offered by integrating photovoltaic (PV) systems into the electrical grids of buildings, enabling the provision of electricity to both structures and perhaps facilitating the recycling of electric vehicles. Not only does this have the potential to reduce long-term energy costs, but it also plays a crucial role in promoting Algeria's shift towards more eco-friendly and sustainable energy options. This, in turn, contributes to global initiatives to address climate change and promote a more environmentally friendly future for future generations.

Analysis of Electric Power Transmission Lines Through Graph Theory: Protecting Environmental Preservation Areas Through Strategic Planning

Electrical networks consist of generation plants, transmission and distribution substations of electrical en-ergy. Power is transmitted through towers and lines that span hundreds or even thousands of kilometers. To ensure the health, stability of ecosystems and our quality of life, we must protect the environmental areas where transmission lines intersect. Given the global challenges related to sustainability, the conservation of natural resources and the mitigation of climate change, these studies are imperative. Through graph algorithms, especially vertex degree search and depth-first search, we identify alternative routes, avoiding sensitive regions such as conservation areas within the 440kV transmission networks of São Paulo, Brazil. By reallocating energy transport, we can ensure net-work maintenance and reduce environmental impacts from potential accidents. The results highlight the sustainable planning of transmission lines, aligning energy needs with Brazilian environmental conservation efforts, including the Rio State Park Peixe, Aguapeí State Park, Itapetinga State Park and Itaberaba State Park. Combining existing environmental laws with the promotion of sustainable technologies and practices, promoting more efficient use of resources while protecting the environment.

Low-carbon economic scheduling for AIES considering flexible load coordination and multiple uncertainties

The disordered energy use in traditional agricultural production has resulted in high energy purchase costs and carbon emissions. The coupling of integrated energy systems with agriculture offers the potential for flexible coordination of agricultural loads while agricultural loads are highly influenced by changes in the natural environment. In this context, this paper proposes a low-carbon and economic scheduling optimization method for agricultural integrated energy system (AIES), which comprehensively takes temperature, light intensity, and the coordination of agricultural loads into consideration. Firstly, solar and biomass resources are integrated through energy conversion equipment to support energy supply from both the electrical distribution network (EDN) and the gas network. At the same time, the modelling process of agricultural load is refined, which is divided into crop irrigation, greenhouse temperature control and residential consumption. The models of agricultural multi-energy complementary and energy storage equipment are established to achieve flexible conversion between different energy sources. In addition, the distributionally robust optimization (DRO) method based on multiple discrete scenarios is adopted to deal with the uncertainties arising from environmental condition fluctuations during the optimization process. Finally, the proposed model is tested on 4 various regions and 2 different seasons. Numerical results show that the proposed model can effectively enhance the economic and environmental performance of the AIES.

Fuzzy-fractional modeling and simulation of electric circuits using extended He-Laplace-Carson algorithm

In literature, most of the electric circuits are found to be at integer order, which are unable to capture the involved uncertainties and memory effects. To understand these effects, the current study is focused on modeling and analysis of fuzzy-fractional L˜C˜ circuit, R˜C˜ circuit, R˜L˜ circuit, and R˜L˜C˜ circuit. Triangular fuzzy numbers (TFNs) are utilized to introduce uncertainties in circuits. The memory effect is considered through fractional derivative in Caputo sense. A hybrid homotopy perturbation method (HPM) is established for solution purpose, in which standard HPM is combined with Laplace-Carson transformation in fuzzy-Caputo sense. This leads to an excellent and well-organized approach to calculate numerical solutions in the aspect of fuzzy logic and fractional calculus. The results obtained through proposed approach are validated by comparing them with already existing results in literature. Residual errors are also calculated across the domain of r at fractional order to determine the convergence and stability of electric circuit models. To study the dynamics of inductor, resistor, and capacitor on current along with fractional and fuzzy parameters involved in the electric circuits, contour and three-dimensional plots are constructed. Several plots specifying the fuzzy membership function of models across various parameter values are also demonstrated. The results achieved through this study indicate that He-Laplace-Carson method can assist engineers and researchers when dealing with electric circuits characterized by fuzzy and fractional dynamics.

Design of Radial Distribution System to Study Load-Flow and Short Circuit Analysis Using ETAP Software

This work's analysis provides information on fault analysis and load flow studies, which help to understand how radial distribution networks operate both in normal and emergency circumstances. The research explores optimization methods, describing capacitor placement, transformer size, and feeder reconfiguration in order to lower losses and increase system efficacy. Moreover, the work looks at reliability-focused maintenance techniques, stressing the need of predictive maintenance and condition monitoring in raising the dependability of radial distribution networks. Modern electrical power networks depend heavily on their radial distribution system, which effectively and dependable distributes electricity to customers. Many radial distribution system-related topics are covered in detail on this website, including analytical methods, optimization processes, and dependability enhancement strategies. Power flow, voltage control, and losses in radial networks are investigated in this paper under a range of operational situations. The last and crucial stage of a power system, the electrical distribution system makes sure that customers have a steady supply of electricity. Regretfully, because it is often neglected and exposed to environmental risks, our distribution network has a number of problems. Our distribution feeder is rigorously analyzed for load flow and short-circuits in order to overcome these challenges and find and fix problems. The main topics of this study are the load flow and short-circuit analysis of a radial distribution feeder, which is mostly constructed with (ETAP). The final and crucial part of a power system, the electrical distribution system ensures that consumers receive an uninterrupted and steady supply of electricity. Our distribution feeder undergoes a rigorous and cautious process to address these issues front on because of the uncontrollable nature and susceptibility of our network to environmental hazards. This paper delves deeply into the issues of short-circuiting and load flow in radial distribution feeders. Both symmetrical and asymmetrical faults are thoroughly investigated by mathematical computations and ETAP simulations; the results of the software simulations are contrasted with those of the mathematical analysis. These discoveries will definitely influence the development and management of our system and point us in the direction of workable and practical solutions.

Temperature Fluctuations in Power conductors: Analysis and Overcurrent Relay Adaptation Strategies for Mitigation

In electrical networks, the efficient flow of energy faces constraints primarily associated with the conductor’s temperature. By assessing transmission infrastructure, identifying critical geographical and climatic zones, one can compute the line’s temperature. Focusing on the importance of maintaining optimal conductor temperature for efficient power transmission, this paper evaluates the critical role of conductor temperature in overhead transmission lines and explores its dynamic variations influenced by various ambient conditions. Emphasizing the significance of maintaining optimal conductor temperature, the study delves into mitigation strategies and adaptive protection mechanism, with a focus on overcurrent relays, with specific emphasis on the efficacy of current-time graphs. By addressing these factors, the research aims to enhance the reliability and efficiency of power transmission systems, ensuring sustained performance under diverse environmental scenarios. Overall, the paper contributes valuable insights to optimize the flow of energy in overhead transmission lines, thereby enhance the robustness also, improving the resilience and functionality of electrical networks.

Electrorheological and magnetorheological properties of liquid composites based on polypyrrole nanotubes/magnetite nanoparticles

This research presents an in-depth exploration of the electrical and magnetic properties of a polypyrrole nanotubes/magnetite nanoparticles (PPyM) material embedded in a silicone oil matrix. A key finding of our study is the dual nature of the composite, i.e. it exhibits a behaviour akin to both electro- and magnetorheological suspensions. This unique duality is evident in its response to varying electric and magnetic field intensities. Our study focuses on examining the electrical properties of the composite, including its dielectric permittivity and dielectric loss factor. Additionally, we conduct an extensive analysis of its rheological behavior, with a particular emphasis on how its viscosity changes in response to electromagnetic stimuli. This property notably underscores the material’s dual-responsive nature. Employing a custom experimental design, we integrate the composite into a passive electrical circuit element subjected to alternating electric fields. This methodological approach allows us to precisely measure the material’s response in terms of resistance, capacitance, and charge under different field conditions. Our findings reveal substantial changes in the material’s electrical conductivity and rheological characteristics, which are significantly influenced by the intensity of the applied fields. These results enhance the understanding of electro-magnetorheological properties of PPyM-based magnetic composites, and also highlight their potential in applications involving smart materials. The distinct electrical, magnetic and rheological modulation capabilities demonstrated by this composite render it as promising candidate for advanced applications. These include sensory technology, actuation systems, and energy storage solutions.

EDUPERES and GAMERES: A smart interactive education platform and digital gamification for basic circuit analysis

AbstractThis paper introduces Education Platform for Equivalent Resistance (EDUPERES) and Gamification of Equivalent Resistance (GAMERES), two different parts of a new computer aided education platform with interactive and imaginative design and game elements, which have been created during 4 years. In Vocational School of Transportation of Eskişehir Technical University, electrical circuit analysis is a compact course which exhaustively yet quickly covers all the DC and AC circuit concepts. During the course, it is observed that some students have difficulties in some basic capabilities such as calculation of equivalent resistance of either a standard or a compact circuit, dividing currents, and so on. More sadly, this inability spreads to the rest of the semester. This study aims to overcome this issue through a smart interactive education platform and gamification. The first part, that is, EDUPERES visualizes and animates the solutions of electrical circuits. To make the students exercise circuit questions, it provides an interface which simulates the comfort of using paper and pencil. This platform is powered by a smart algorithm to watch almost all of the actions of the students and to give prompt warnings. It allows students to transform the shapes of compact circuits during circuit reduction. The second part, that is, GAMERES imaginatively converts the circuit questions into action, competition, shooter, puzzle, and maze games. Via box plots and Mann–Whitney–Wilcoxon nonparametric tests, it is shown that EDUPERES and GAMERES can significantly increase students' learning. The success of EDUPERES and GAMERES is discussed with regard to previous studies and gamers' motivations.

A logic device based on memristor-diode crossbar and CMOS periphery as spike router for hardware neural network

A programmable logic device based on a memristor-diode crossbar and CMOS logic has been developed. The crossbar implements NAND logic gates using memristor ratioed logic and CMOS inverters. The digitally controlled peripheral circuit provides digital signals transmission and allows modification and evaluation memristor states in the crossbar. The proposed logic device circuit requires fewer transistors than known analogues and less area on the chip.The maximum size of the crossbar in a logic device is estimated by numerical simulation at the level of electrical circuits. The limited size is caused by the degradation of the logic levels voltages in the memristor-diode crossbar. The operability of peripheral circuits as part of a complete electrical circuit of a logic device is demonstrated during the simulation of the execution of logical operations, the processes of modification and evaluation states of individual memristors.

A Novel Approach for Dynamic Analysis of Wind-Integrated Multi-Machine Power Systems

Indeed, the rapid expansion of Renewable Energy Sources (RES) in recent years has brought about numerous benefits, including reduced carbon emissions, increased energy independence, and the creation of new economic opportunities. However, integrating these variable and intermittent sources into existing power systems poses several challenges for power system management. Faults in electrical networks are among the key factors and sources of network disturbances. Control and automation strategies are among the key fault clearing techniques responsible for the safe operation of the system. In recent years, the increasing penetration of wind energy in multi-machine power systems has posed unique challenges to power grid stability and reliability. Accurate assessment methodologies are required to ensure the effective integration of wind energy sources while maintaining grid stability. Several researchers have revealed various constraints of control and automation strategies such as a slow dynamic response, the inability to switch the network on and off remotely, a high fault clearing time and loss minimization. It's important to note that the impact of wind energy on system inertia is a complex and dynamic aspect of power system operation. Ongoing research and technological advancements aim to improve the integration of wind and other renewable energy sources while ensuring grid stability and reliability. As the energy transition continues, addressing these technical challenges is crucial for building a sustainable and resilient power system. In this paper, the influence of doubly-fed induction generator (DFIG) penetration is analyzed to examine the transient stability of power system networks. The concept of a Coupling Strength Index (CSI) derived from Network Structural Characteristics Theory sounds intriguing, especially in the context of identifying critical elements susceptible to the impact of a three-phase fault in a network. The investigation involves studying the transient stability of a power system under different conditions, specifically with and without doubly-fed induction generators (DFIGs) connected to a weak bus. Additionally, a three-phase fault is applied at the middle of the identified weakest line for both the IEEE 9 and 39 bus systems. The investigation of generator speed, rotor angle, and electric power during transient stability analysis provides a holistic view of how a power system responds to disturbances. This information is crucial for ensuring the reliability and stability of the system, especially when studying the integration of renewable energy sources and addressing potential challenges associated with faults and weak buses. This paper presents a pioneering non-iterative framework for dynamically assessing wind energy dominated multi-machine power systems. The proposed framework aims to address the shortcomings of traditional iterative methods, providing a more efficient and reliable approach to power system analysis.

A multi-objective energy scheduling of the reconfigurable off-grid microgrid with electric vehicles using demand response program

Microgrids are essential in ensuring responsible energy consumption and production patterns to support and advance the United Nations’ sustainable development goals. However, due to the limited supply in the off-grid microgrids, an increase in the integration of electric vehicles (EVs) into electrical networks for their charging operation is expected to create a void between the energy supply and demand. Demand response (DR) programs provide a better solution to the energy management problem of microgrids. However, the difference in the objectives of the stakeholders of the off-grid microgrid can create an issue in providing optimal solutions to its energy scheduling problem. This paper focuses on the multi-objective energy scheduling strategy of the off-grid microgrid to manage its limited energy supply optimally using an incentive-based DR program. A fast heuristic approach is also presented in this work to reconfigure off-grid microgrid optimally during its hourly operations. Furthermore, Hong’s (2m+1) point estimation method is used in this work to consider the uncertainties in the EVs and other DR participants. The proposed work is analyzed on the 33-bus and 69-bus off-grid microgrid consisting of droop-controlled distributed generations, EV charging stations, and consumers with curtailable loads. For the day-ahead operation of the off-grid microgrids, the analysis shows that the proposed work reduces the operational cost of the two off-grid microgrids by 2.3% and 4.56%, respectively.

A Review on the Recent Advances in Battery Development and Energy Storage Technologies

Energy storage is a more sustainable choice to meet net-zero carbon foot print and decarbonization of the environment in the pursuit of an energy independent future, green energy transition, and uptake. The journey to reduced greenhouse gas emissions, increased grid stability and reliability, and improved green energy access and security are the result of innovation in energy storage systems. Renewable energy sources are fundamentally intermittent, which means they rely on the availability of natural resources like the sun and wind rather than continuously producing energy. Due to its ability to address the inherent intermittency of renewable energy sources, manage peak demand, enhance grid stability and reliability, and make it possible to integrate small-scale renewable energy systems into the grid, energy storage is essential for the continued development of renewable energy sources and the decentralization of energy generation. Accordingly, the development of an effective energy storage system has been prompted by the demand for unlimited supply of energy, primarily through harnessing of solar, chemical, and mechanical energy. Nonetheless, in order to achieve green energy transition and mitigate climate risks resulting from the use of fossil-based fuels, robust energy storage systems are necessary. Herein, the need for better, more effective energy storage devices such as batteries, supercapacitors, and bio-batteries is critically reviewed. Due to their low maintenance needs, supercapacitors are the devices of choice for energy storage in renewable energy producing facilities, most notably in harnessing wind energy. Moreover, supercapacitors possess robust charging and discharging cycles, high power density, low maintenance requirements, extended lifespan, and are environmentally friendly. On the other hand, combining aluminum with nonaqueous charge storage materials such as conductive polymers to make use of each material’s unique capabilities could be crucial for continued development of robust storage batteries. In general, energy density is a key component in battery development, and scientists are constantly developing new methods and technologies to make existing batteries more energy proficient and safe. This will make it possible to design energy storage devices that are more powerful and lighter for a range of applications. When there is an imbalance between supply and demand, energy storage systems (ESS) offer a way of increasing the effectiveness of electrical systems. They also play a central role in enhancing the reliability and excellence of electrical networks that can also be deployed in off-grid localities.

Identification of Prospective Physics Teacher’s Problem Solving Skills: A Study on Simple Electrical Circuits Topic

Problem-solving is one of the essential and crucial skills for physical learning. This study describes the problem-solving skills of college students taking physics education programs and their incorrect answers on simple electrical circuits topic. We used four essay questions representing the series, parallel, combined series-parallel, and double-loop electrical circuits concepts to measure their problem-solving skills. Meanwhile, for describing their problem-solving skills, we used five categories of problem-solving processes, consisting of useful description (UD), physics approach (PA), specific application of physics (SAP), mathematical procedures (MP), and logical progression (LP). Further, to identify their mistakes, we examined the general mistakes in each problem-solving process. Our analysis results suggested that the college students taking the physics education program have relatively high problem-solving skills in the UD and PA categories. Still, they have low skills in SAP and MP categories, with poor ability in the LP category. Their mistakes were mostly observed in drawing complete electrical circuits and the circuits with missing and changing components (UD category), the correlation between each physic concept, law, and principle with the simple electrical circuits topic (PA category), confusion and inconsistency to correctly determine the + or – symbols for every source of voltage and difficulty in using the Kirchoff’s second law following the loop direction. Besides, the participants also frequently used incorrect V, and I value on the problem being reviewed (SAP category), did not re-evaluate the order and completeness of their answer, as well as the logical reasoning for the obtained V and I from their problem-solving process based on the scientific and physic concepts and characteristics (LP category).

Development of an electric drive for personal light electric vehicles

Problem. The article addresses the challenge of enhancing inclusive mobility and environmental cleanliness by developing a traction electric drive for personal light electric vehicles. A study was conducted on modern electric drive systems for personal light electric vehicles. Goal. The aim is to boost inclusive mobility and environmental cleanliness through the development of a traction electric drive for a personal light electric vehicle, specifically based on a tricycle. Methodology. The methodology involves scientific analysis and synthesis of traction electric drives for electric vehicles. An assessment of the nominal capacity of the battery module from the Nissan Leaf electric car was conducted using both partial discharge procedures and the Leaf Spy Pro program. Results. Based on an analysis of existing electric drive systems, a traction electric drive for a tricycle was developed. A functional diagram of the electric bicycle drive was generated. A control system for a sensorless brushless motor was developed, determining rotor position by measuring EMF in the free phase. This led to the creation of a stable voltage electrical circuit with a virtual midpoint. The tricycle's electric drive utilizes two 10-inch motor wheels on the rear wheels, enabling high speed and efficiency. Controllers specifically designed for electric wheel motors with a power of 350 W were selected to control the traction electric drive. Modules from the 2015 Nissan Leaf electric car's battery, which had depleted 20% of their capacity, were chosen to power the electric drive. The battery health status is 77.95%. A model of the battery's electrical equivalent circuit was constructed, and partial discharge graphs of the Nissan Leaf battery module were analyzed. Originality. The results provide a comprehensive insight into the development of a traction electric drive for personal light electric vehicles, using a tricycle as an example. Practical value. The research led to the development of an electric drive for a three-wheeled vehicle, with two motor wheels of 350 W nominal power each. The power supply voltage ranges from 36 V to 48 V, powered by six battery modules from the Nissan Leaf electric car, totaling 48 V. The energy capacity of one battery module is 0.3898 kWh, resulting in a total energy capacity of 2.3388 kWh for the vehicle's battery. However, the realizable capacity does not exceed 1.871 kWh, providing a travel distance of approximately 75 km on one battery charge. These findings demonstrate the feasibility of reusing batteries from electric cars with diminished capacity to power light electric vehicles. The results are relevant for scientific and technical professionals involved in electric vehicle development.

A pareto strategy based on multi-objective optimal integration of distributed generation and compensation devices regarding weather and load fluctuations

In this study, we present a comprehensive optimization framework employing the Multi-Objective Multi-Verse Optimization (MOMVO) algorithm for the optimal integration of Distributed Generations (DGs) and Capacitor Banks (CBs) into electrical distribution networks. Designed with the dual objectives of minimizing energy losses and voltage deviations, this framework significantly enhances the operational efficiency and reliability of the network. Rigorous simulations on the standard IEEE 33-bus and IEEE 69-bus test systems underscore the effectiveness of the MOMVO algorithm, demonstrating up to a 47% reduction in energy losses and up to a 55% improvement in voltage stability. Comparative analysis highlights MOMVO's superiority in terms of convergence speed and solution quality over leading algorithms such as the Multi-Objective Jellyfish Search (MOJS), Multi-Objective Flower Pollination Algorithm (MOFPA), and Multi-Objective Lichtenberg Algorithm (MOLA). The efficacy of the study is particularly evident in the identification of the best compromise solutions using MOMVO. For the IEEE 33 network, the application of MOMVO led to a significant 47.58% reduction in daily energy loss and enhanced voltage profile stability from 0.89 to 0.94 pu. Additionally, it realized a 36.97% decrease in the annual cost of energy losses, highlighting substantial economic benefits. For the larger IEEE 69 network, MOMVO achieved a remarkable 50.15% reduction in energy loss and improved voltage profiles from 0.89 to 0.93 pu, accompanied by a 47.59% reduction in the annual cost of energy losses. These results not only confirm the robustness of the MOMVO algorithm in optimizing technical and economic efficiencies but also underline the potential of advanced optimization techniques in facilitating the sustainable integration of renewable energy resources into existing power infrastructures. This research significantly contributes to the field of electrical distribution network optimization, paving the way for future advancements in renewable energy integration and optimization techniques for enhanced system efficiency, reliability, and sustainability.

Joint energy management with integration of renewable energy sources considering energy and reserve minimization

In light of electric vehicles (EVs) and demand-side management, a combined optimization paradigm for microgrid (MG) resource scheduling is proposed in this study. Renewable energy sources, including wind and solar power, fulfill a fraction of the consumption demand, while the MG maintains a connection to the electrical network to facilitate power transactions. By utilizing EVs, we can mitigate the inherent volatility of renewable energy production with manageable loads and level out the system's demand profile. The proposed system employs a bi-level programming strategy, wherein the initial level is dedicated to the minimization of aggregate costs, encompassing those related to energy and reserves. Additionally, costs associated with resource redistribution due to the uncertainty of solar and wind power output are minimized at the second level. Subsequently, the objective function is addressed using the enhanced adapted approach of modified marine predators algorithm (MMPA), chosen for its robustness and effectiveness as an optimization technique. The outcomes obtained for a microgrid underscore the superior performance of the results achieved through the application of the MMPA algorithm when contrasted with alternative established methodologies. The outcomes have demonstrated that integrating EVs and adaptable loads contributes to a decrease in operational expenses and emissions. Furthermore, the uncertainties associated with WT and PV are effectively counterbalanced. Additionally, the results garnered from the simulations indicate that the recommended MMPA technique has the capacity to yield superior solutions compared to several other widely recognized optimization algorithms. Scheduling with both DR and EVs with three cost components are considered, generation cost, reserve cost, and initial unit cost, amounting to $740.11, $9.61, and $6.07, correspondingly and it can lead to decreased emission levels and increased incentives for proprietors of EVs, responsive load participants, and RES.

A Design and Construction of the Vibration Perception Threshold Measurement Device for Diabetes

A Design and Construction of the Vibration Perception Threshold Measurement Device for Diabetes

A super-hydrophilic graphite directly from lignin enabled by a room-temperature cascade catalytic carbonization

A cost-effective, and low-energy room-temperature cascade catalytic carbonization strategy is demonstrated for converting lignin into graphite with a high yield of 87 %, a high surface potential of −37 eV and super-hydrophilicity. This super-hydrophilic feature endows the lignin-derived graphite to be dispersed in a variety of polar solvents, which is important for its future applications. Encapsulating of liquid metals with the graphite for electrical circuit patterning on flexible substrates is also advocated. These written patterns show superb conductivity of 4.9 × 106 S/m, offering good performance stability and reliability while being repeatedly stretched, folded, twisted, and bent. This will offer new designs for flexible electronic devices, sensors, and biomedical devices.