Amount Of Electrical Energy Research Articles

Observing the interaction between energy generation carbon emissions and economic conditions could consider generation, intensity, and times of the day.

Management of carbon emissions of regional electricity generation involves resolving much nuanced relationships. However, current studies pertaining to the relationship between energy and the economy utilize only quarterly and annual data and focus on the long-run relationship but are oblivious to temporal associations. This study takes the context of the State of Texas and utilizes per 15min of data between 2007 and 2020 to derive the monthly time series of life-cycle emissions, emissions factor, and energy generation. The study also divides each day into three portions (0:00-8:00, 8:00-16:00, and 16:00-24:00) in order to descend precision down to the hourly level. Impulse-response analysis indicates that (1) employment conditions impact emissions by affecting the amount of electric energy generated, while demographic (population as reflected by property price) tends to impact emissions by affecting the carbon intensity of electricity, and (2) the emissions produced during 0:00-8:00 display different reaction to fluctuation of regional economic conditions compared to emissions produced during other periods, the effect emanates from either energy generation fluctuation or emissions factor shocks. The broader implication of the findings lies in an emphasis on time-interval-specific analysis and concurrent consideration of both energy generation and emissions factors that can lead to optimized policy implementation results.

Determination of I-V curves for photovoltaic generator by an analytical method; Akbaba model

In order to maximize the amount of electrical energy generated and ensure effective use, the conventional I-V or V-I characteristics derived from the diode model of Photovoltaic (PV) Solar Panels are important. Unfortunately, these features cannot be extracted using linear equations. It follows that the answer requires extremely drawn-out, time-consuming procedures. Many studies focus on calculating maximum power extraction. The analytical solutions to these equations are also nonexistent. Programming on computers can assist in solving the equations. The Akbaba Model was created specifically for the PVG to address these challenges. The Akbaba Model relies heavily on coefficients A, B, and C in this equation. The diode model serves as the true model in this case, and the coefficients A, B, and C are calculated. Another advantage of this model is that, because its qualities have partially deteriorated with time, the genuine I-V characteristics of the PV Panels can be recovered by measuring again.

Free vibrations and dynamic behavior of the three layered flexoelectric functionally graded microbeam under moving load

In this study, free vibrations and the dynamic responses of the three layered flexoelectric functionally graded microbeam under the effect of moving load are investigated. Using the first order shear deformation and the size-dependent piezoelectricity theories in the framework of Hamilton's principle, the governing equations of motion and the corresponding classical and non-classical boundary conditions are obtained. Next, the equations of motion were discretized and solved using the finite element method. In order to validate the governing equations and the solution method, the obtained results have been compared with the results of previous studies, which shows a good convergence between the current and previous results. The obtained results demonstrate the dynamic behavior of the microbeam is strongly influenced by the geometrical ratios, the flexoelectric layers thickness, the functionally graded power index, the flexoelectric coefficient and the load velocity. So that the escalation in the strain gradient from the augmentation of the flexoelectric layers' thickness leads to a corresponding rise in the electric potential function. Moreover, as the flexoelectric coefficient increases, the microbeam becomes more responsive to polarization, thereby generating a greater amount of electrical energy. In addition, changes in the velocity of the moving load significantly affect the dynamic behavior of the structure in such a way that with the increase in the load velocity, the dynamic deflection of the structure increases.

Analysis of the Influence of Variation in Medical Waste Heating Value on the Electrical Energy Output of Generator in Medical Waste Cogeneration Incinerator System using Gatecycle Solver

Abstract Medical waste incinerator is a technology capable of processing and exterminating hazardous medical waste through combustion at temperatures exceeding 800°C. Medical waste exhibits a range of heating values depending on its material composition. The heating value represents the potential heat energy released when a substance undergoes complete combustion. A cogeneration incinerator is designed to treat medical waste while also harnessing the heat of the flue gas that emanates from the combustion process. The flue gas acts as a hot fluid that transfers its heat, causing the water temperature inside the boiler to increase and transform into high-temperature steam. This steam drives a steam turbine connected to a generator to generate electrical energy. The amount of electrical energy generated is influenced by the steam quality produced through the boiler’s water-heating process. This study aims to investigate the influence of variation in the heating value in medical waste on the electrical energy output of the generator in a medical waste cogeneration incinerator system. The range of heating value variations used in the testing varies from 25 MJ/kg to 35 MJ/kg. The variation is tested through thorough simulations using GateCycle software to obtain data on the electrical energy generated. To achieve a maximum electrical energy output of 200 kW, fuel with a total heating value of 32.25 MJ/kg is required. This study is beneficial to be implemented as renewable energy sources based on biomass powerplant systems.

An Ecoflex-encapsulated interlayer-structured triboelectric nanogenerator for Sports activity monitoring

Incorporating self-powered devices with flexible sensors not only tackles the power obstacles linked to wearable electronics but also greatly broadens their capability and application fields. Triboelectric nanogenerator (TENG) have garnered significant interest in the wearable electronics sector because of their distinct ability to harness ambient energy. Several techniques have been suggested to improve the efficiency of TENG, but these strategies often result in higher intricacy and manufacturing expenses. This study presents an interlayer structure that efficiently increases the surface contact area of TENG, consequently improving their output performance. Using this structure, a cost-effective, highly sensitive, and easily manufacturable sensor called the Ecoflex-encapsulated interlayered triboelectric nanogenerator (EI-TENG), has been developed. The EI-TENG demonstrates superior performance compared to a monolayer TENG (M-TENG) of identical dimensions, exhibiting a 1.6-fold increase in voltage output, a fivefold enhancement in minimum measurement precision, and a 2.29-fold increase in sensitivity. In addition, the EI-TENG exhibits exceptional endurance, as it maintains a consistent output even after undergoing 10,000 cycles. Furthermore, it reliably functions under different temperature and humidity situations. The energy produced by the EI-TENG is adequate to power 45 LED lamps directly. The EI-TENG, when affixed to an athlete’s hand, is capable of sensing the distribution of pressure while dribbling and shooting a ball, which assists athletes in honing their methods and making necessary adjustments to their hand strength. This study not only demonstrates the creation of interlayer-structured TENG, which produces a high amount of electrical energy and is durable and stable in many environments, but also provides valuable information for the future advancement of affordable, self-sustaining electronic devices.

Regulation of the power of a wind turbine of a special design by changing the length of the blades

The object of this research is a model of a wind turbine with retractable blades. This model allows for the adjustment of the turbine’s screw radius by extending or retracting the blades, providing a basis for examining the impact of blade radius on turbine performance. The primary problem addressed by this study is to determine how changes in the screw radius, achieved by altering the blade length, affect the wind turbine’s performance, specifically its electrical output (voltage and current) and rotational speed, under constant wind conditions. The experimental results showed that when the turbine blades are fully extended (R1), the wind turbine generates higher voltage and current compared to when the blades are retracted (R2). This confirms that the turbine’s electrical output is significantly influenced by the screw radius. These results are explained by the aerodynamic principles governing wind turbines. An increased screw radius allows the turbine blades to capture more wind energy, leading to greater force applied to the blades, thus increasing the rotational speed and the amount of electrical energy generated. The linear relationship between the screw radius and the turbine’s performance was as summed to simplify the analysis, though the actual relationship may be more complex. The finding soft its study can be practically applied in the design and operation of wind turbines. Turbines with adjust table blade lengths can optimize performance across varying wind conditions, maximizing efficiency and power output. These results are particularly useful in environments where wind speed is variable, as turbine scan adjust their blade radius to maintain optimal performance. The study assumes consistent wind conditions and uniform air flow for the results to be accurate, so these conditions should be considered when implementing the findings in real-world scenarios

Thermal performance research on the zero liquid helium consumption cryostat for a superconducting undulator

Superconducting undulators generally depend on a liquid helium cryostat. If the cryostat can liquefy the boil-off helium completely, a large helium refrigerator can be avoided, and a large amount of electrical energy can be saved. However, many studies are limited by the excessively high heat load. In this work, systematic thermal analysis and optimization are carried out to minimize the total heat load so that it can be covered by the cooling capacity. Based on the analysis, one single thermal shield is set in the cryostat, and thermal interruptions are widely adopted together. Moreover, the cooling capacity matches the heat load well, and the excess cooling capacity is increased significantly. In the experiment, the cryostat was tested with no magnet, a small magnet and a full-scale magnet respectively so that the heat load could be analyzed step by step. Finally, zero liquid helium consumption was achieved with the full-scale superconducting magnet, which reached a current of 450 A. The excess cooling capacity accounts for approximately 40 % of the total cooling capacity, which is as high as approximately 2.0 W. This study can serve as a reference for the research of superconducting undulator and other magnet cryostats.

Internet of things-based electrical energy control and monitoring in households using spreadsheet datalogger

Today, the demand for electrical energy is paramount in various daily activities. Hence, individuals must be aware of the amount of electrical energy consumed to maintain the quality of electronic devices. Knowing the quality of electronic devices is essential since it can impact the performance and lifespan of electrical equipment. The value of electrical power is determined by the quality of electrical power and the number of hours. Monitoring electrical energy involves collecting or measuring data to assess the current level of energy consumption. The author is interested in researching the use of Datalogger Spreadsheets to monitor and gather real-time information on energy use, which is made possible through integration with internet of things (IoT) and microcontrollers. Through data analysis and observation, solutions to existing problems are sought by comparing and matching data. Monitoring daily energy usage in a home setting produces output data that can be viewed directly and remotely with real-time results. This tool is expected to address current issues.

Carbon-based brilliance: a novel approach to renewable energy in radiotherapy centers.

The energy produced from other sources which does neither come from fossil fuels nor contribute in the production of any greenhouse effects that causes climate changes is called as 'Alternative Energy'. Since our world's primary energy sources such as coal, oil and natural gases are exploited to a greater extent, we are in an urge to switch to an alternative energy. Scattered radiation, a common byproduct in radiation therapy and diagnostic radiology, presents a unique opportunity in the realm of alternative energy. As a potential source of interference, scattered radiation can be repurposed to contribute to sustainable energy solutions. Addressing the issue of scattered radiation wastage and utilizing it for alternative energy, an activated carbon-based solar cell emerges as a solution. This solar cell, a conventional one in which cadmium Telluride is replaced by coconut shell based carbon material, has the potential in producing a significant amount of electrical energy by utilizing scattered radiation from radiotherapy and radiology machines. Furthermore, this activated carbon based-material undergoes thorough characterization into various teletherapy and radiology machines, and it can be seamlessly integrated into clinical practices.

Decarbonizing cities through electrification: A strategic study for densely built residential districts in Southern Italy

This paper presents a strategic analysis of the potential for energy savings and decarbonization in a densely built residential district through the synergistic implementation of electrification and building retrofitting measures. The study specifically focuses on the energy performance achievable when completely electrifying the Heating, Cooling, and Domestic Hot Water (DHW) services of a densely built urban district in Catania (Italy), including more than 200 residential buildings. The research thus models the district's energy systems to assess the impact of various scenarios, which include individual measures tailored for thermal systems as well as a comprehensive approach that combines full electrification, on-site renewable energy integration and building envelope retrofitting. The findings underline the effectiveness of the combined scenario, which results in cancelling natural gas consumption while also reducing by around 57 % the amount of electrical energy purchased from the grid, with a final 70 % decrease in carbon emissions. Of particular relevance is the efficacy of upgrading thermal systems alongside PV system installation, under the hypothesis of creating a stand-alone electric grid for the entire district that can exchange electricity with the existing network when needed. Under these premises, the energy procurement from the electric network can be reduced by 40 %.

Study on Fume Hood Improvements for Energy Savings and Minimum Face Velocity

A fume hood is a device that safely exhausts harmful substances generated during the experimental process to the outside, and for the safety of researchers and the protection of experimental samples, the balance between the amount of air flowing in and the speed at which it is discharged to the outside is extremely important. The Face velocity of the fume hood is recommended to be 0.5m/s (ASHRAE 110-2016) specified by the American National Standards Institute (ANSI). The Korea Occupational Safety and Health Corporation specifies 0.4 m/s (KOSHA-G-7-1999). To increase the functionality of the fume hood, it must be operated 24 hours a day while maintaining the prescribed Face velocity to make a safe laboratory environment. However, constantly powering them consumes a significant amount of electrical energy. Therefore, it's crucial to make efforts to reduce energy consumption. Some labs have adopted a method to minimize electrical usage by powering the hoods only when they're in use. In that case, it should be done with great caution. Because hazardous substances inside the hood could be leaked, putting the entire lab at risk. By implementing such measures, organizations and institutions managing lab facilities can effectively reduce energy consumption while ensuring the use of safe fume hoods. Additionally, there's a growing trend in research facilities to maintain Face velocity of fume hoods below 0.25 m/s as part of efforts to decrease and conserve electrical energy. This study stems from preliminary research aimed at achieving a stable face velocity in fume hoods. In this study, to reduce the face velocity of the fume hood, we changed the structural design of the fume hood based on existing research. As a result, the face velocity of the fume hood is reduced from 0.5 m/s to 0.297 m/s. the study reduced the face velocity to a maximum of 0.297m/s. To verify the performance of the fume hood with minimum face velocity, we tested the ventilation performance with the international standard test method. It proves that the fume hood with face velocity 0.297 m/s make no differences compared to existing fume hood with higher face velocity. In addition, the fume hood with minimum face velocity enables the reduction of energy consumption.

Resolution of the bi-objective optimization problem for the dispatch of hydroelectric plants under conditions of low inflow using the NSGA II algorithm

Among the consequences of climate change are increased temperatures and changes in rainfall patterns that bring longer periods of drought. This creates limitations in the administration of hydroelectric plant reservoirs, restricting, in some cases, the amount of electrical energy generated. The objective of this research is to solve the multi-objective optimization problem that seeks to minimize the production of electrical energy from hydroelectric plants with low inflow and, at the same time, minimize electrical rationing due to this low production. As these objectives conflict with each other, it is necessary to apply multi-objective optimization problem-solving methodologies, among which are genetic algorithms. The mathematical model is built considering the operating conditions of the reservoirs of the hydroelectric plants under study, including their minimum operating levels, which are included in the model restrictions. The non-dominated genetic classification algorithm II is used to obtain the Pareto front, which is composed of a total of 78 non-dominated solutions that are useful to manage the considered reservoirs at the time of maximum demand. It is recommended to use other multi-objective optimization algorithms for comparison purposes, selecting the ideal indicators to evaluate the performance of each algorithm used, in addition to incorporating monetary and environmental cost restrictions into the model

Zero-dimensional model of a pumped heat energy storage system with reciprocating machines

The technology of Pumped Heat Energy Storage allows for the storage of large amounts of electrical energy, which is currently crucial due to the worldwide use of renewable energy sources (intrinsic and highly variable). In these systems, electrical energy is used to feed a heat pump cycle (charging phase) that exchanges heat with two thermal reservoirs, storing part of the input energy in the form of thermal energy. This energy is then supplied to the grid through a power cycle (discharging phase) when needed. This article presents a zero-dimensional model of a Pumped Heat Energy Storage system that uses a numerical zero-dimensional model for the reciprocating machines and an analytical model for the heat exchangers. By feeding the model with the operating point data (rotational speed of the reciprocating machines, pressure at a point in the system, fluid temperatures in the reservoirs, and mass flows of the thermal fluids circulating through the heat exchangers) and the geometric dimensions of all the machines, the steady-state evolution of the system can be obtained as result and also the powers of the reciprocating machines and heat exchanged with the thermal reservoirs, circulating mass flow of the working fluid, inlet and outlet temperatures and pressures of each machine, and the round-trip efficiency of a certain configuration, among others. Evaluating the coupling of the machines in a particular setup an overall efficiency of around 36% was calculated for the condition with the maximum local performance coefficient. Analysing the dependency between the stages of charge and discharge an operating condition that improved this value up to an efficiency of approximately 40% was obtained. Both values are conditioned for the use of molten salt, particularly its high melting temperature, which imposes higher temperatures at the expander inlet thus decreasing the overall efficiency of the system.

Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV

Abstract The aim of this study is to energy harvesting and modeling from a soft and flexible nanogenerator based on nanofibers (PVDF/ZnO-RGO) on the arm of a multi-rotor UAV. The nanogenerator modeling was done to improve the usability of piezoelectric nanogenerators to provide part of the electric energy required by drones. Tests were conducted on the experimental setup and practical flight conditions. In each test and a period of 30 s, the vibration signals of the UAV arm were stored, and the vibration data extracted in the time domain and the electrical voltage of the nanogenerator were obtained through the vibrations of the drone, and its values were recorded in each experiment. After signal processing, the best vibration features were used for modeling. In the modeling process, some data were considered for training and testing in ANFIS network. The ANFIS inputs included the selected vibration features and the outputs included the stored voltage. The modeling results were analyzed based on increasing the amplitude of vibrations and the duration of exposure of the nanogenerator to vibration led to higher voltage generation. The maximum voltage recorded during the 30-s flight time of the tested UAV was 64 mV at 3.54, 49.8, and 0.48 Hz along the x, y, and z axes, respectively. The results showed that the application of energy harvesting on different vibration systems could be improved through modeling. It can be used to predict the amount of electric energy produced according to the vibrations of the drone in the future.

Enhanced water production and improving solar water distillation efficiency of double-slope solar stills: Modeling and validation

Solar distillation is a promising technology for producing clean water using renewable energy, especially in regions with water scarcity and contamination. This study investigates the impact of design modifications on the efficiency of a double-slope solar still coupled with evacuated tubes and external reflectors. Using Matlab software analysis, key findings indicate that packing factors, temperature control, and solar radiation exposure all contribute to the system’s optimal performance. Solar radiation levels directly correlate with production rates, emphasizing the need for effective sunlight exposure. The system’s ability to rely on stored heat at night enhances its practicality. This study shows how to make solar stills more efficient at producing clean water. It is found that the best way to do this is to use PV cells with a packing factor of 0.25. A packing factor of 0.25 outperforms other factors, significantly increasing water production and system efficiency. With this optimal factor, the system achieved a remarkable thermal efficiency of 83.5 % and a maximum daily production of 19 L per square meter during peak solar radiation hours. The system’s overall efficiency is 94 % increased by 13 % over the highest value recorded in previous studies. Furthermore, the system’s productivity increased by 40 % from the highest value recorded in previous studies. The amount of electrical energy produced is directly proportional to the packing factor, by the power of 41.1 W-hours (Wh) at a PV cell with a packing factor of 0.25.

An Example of Remote Monitoring for A Refrigerated Display Cabinet: Effects on Energy Performance

Refrigerated display cabinets, which are widely used in supermarkets, are one of the parts of the cold chain. These refrigerators are used for both cold storage and frozen storage of products at specific temperature ranges by standards. In refrigerated display cabinets, the air refrigerated by the heat drawn by the evaporator is blown to the food products. Due to negative interactions with hot ambient air, open-type refrigerated display cabinets consume large amounts of electrical energy. Therefore, the refrigerated display cabinet must have high energy efficiency. Energy labeling was made mandatory for refrigerated display cabinets launched in 2021 and energy labeling was classified from A to G. With this application, refrigerators are classified according to their efficiency. The energy consumption values of the compressor, evaporator fan, condenser fan, PTC resistor, and lighting units that cause energy consumption in the refrigerator were determined, and an algorithm was developed to keep these parameters under control. With this algorithm, energy consumption data is presented and, possible problems are detected, and warnings are given for these problems. With this algorithm that warns the refrigerator when necessary, malfunctions that may occur in the refrigerating system will be prevented. With this remote monitoring method, which aims to check whether the refrigerated display cabinets' meet the energy consumption values specified by the manufacturer under actual operating conditions, the impact of the remote monitoring method on energy efficiency has been revealed, and it was concluded that it can contribute to operational efficiency by reducing energy costs and carbon emissions.

Particle swarm optimization based sliding mode control for maximum power point tracking in solar PV systems

One of the most significant renewable energies is photovoltaic (PV) energy, however it has a low efficiency due to its variable maximum power point that depends on weather conditions. In order to guarantee the system's best performance, intelligent algorithms can effectively track this point in real-time utilizing the maximum power point tracking (MPPT) method. Consequently, it is crucial to maximize the use of the solar energy that has been captured as well as the PV system's generated electricity. Variations in solar irradiance affects the amount of electric energy obtained from solar arrays. For efficient extraction of electricity from solar PV systems, MPPT algorithms are required. Sliding mode control (SMC) can be used in the control of nonlinear systems. However, the effectiveness of SMC can be improved by the choice of the sliding coefficients. In this paper, optimal search using particle swarm optimization (PSO) is used in the design of the sliding manifold. Results obtained via simulations showed that MPPT tracking efficiencies obtained for the PSO based SMC and the conventional SMC are 99.65% and 96.79% respectively. That means, PSO based SMC is 2.86% better than conventional SMC.

Design of Resonant Converter of Trans cutaneous Energy Transfer System to Power Artificial Heart

Wireless technologies have matured to recharge the batteries of consumer devices efficiently. The benefit of the technology is being used by mobile communication devices, personal computation devices, and wearable entertainment devices. The wireless energy transfer techniques employ the transfer of electrical energy between two-tesla coils in surface contact and not by electrical contact through the phenomenon of electromagnetic induction. Many international consortiums have made guidelines for designing and manufacturing these devices. However, for active implantable medical devices such as artificial hearts, a large amount of electrical energy usually in the range of 15W to 30W needs to be transferred across the skin at a depth of 10mm to 30mm. The design needs to be optimized for maximum power transfer with the highest possible efficiency. Any loss in power will be reflected as heat energy and cause burns and tissue death. A transcutaneous energy transfer system is such type of wireless energy transfer mechanism across the skin to power implanted life-saving devices. In this paper, the design of a resonant converter and its performance is investigated to wirelessly transfer electrical power up to a tissue thickness of about 25mm.

Analysis of reducing thermal resistance between the PCM and ambient air for improving the power generation characteristics of PCM-based thermoelectric power generators

A power generator comprising a thermoelectric device (TED) and a phase change material (PCM) allows energy harvesting from ambient temperature variations, which exist ubiquitously; thus, such a device has received considerable attention as an energy harvester that can operate at any location. We developed a model for estimating the characteristics of a power generator in ambient air, whose temperature is forcibly changed between two temperature values, such as when an air conditioner is turned on and off. We calculated the influence of latent heat and thermal conductivity of the PCM on the characteristics of power generators with various thermal resistances between the TED/PCM interface and ambient air. Latent heat and thermal conductivity of the PCM affect the amount of heat energy (Q) transfer between the ambient air and PCM and the energy conversion efficiency (ηE), respectively, where the amount of electric energy is given by Q × ηE. The increase in Q caused by an increase in the latent heat of the PCM was almost independent of the thermal resistance between the TED/PCM interface and air. However, the increase in ηE caused by an increase in the thermal conductivity of the PCM decreased as the thermal resistance between the TED/PCM interface and air increased. These results indicate that the techniques to improve the power generation characteristics by increasing the thermal conductivity of PCM, which have been frequently investigated in recent years, are effective only when the thermal resistance between the TED/PCM interface and ambient air is small.

AUTOMATIC AMOUNT CALCULATION SYSTEM - SMART ENERGY METER USING IOT

In today's reality, Automatic frameworks are being favored over manual frameworks. The quick increment in the number of clients of the web over the previous decade has made the Internet an integral part of life, and IoT is the most recent and rising web innovation. Electricity is one of the fundamental necessities of human beings, it is commonly used for domestic, industrial, and agricultural purposes. These days, power theft is the main issue, costing electricity boards a lot of money and creating payment issues for customers. In our country, these situations are more often. If these thefts are prevented then a lot of power can be saved. This is done using a Smart EB meter. An energy meter chip is used in SEMs to measure the amount of electric energy used, and wireless protocols are used for data transmission. This project presents an EB meter box via automatic billing system by display. electricity continues to rise, the existing grid faces challenges related to aging infrastructure, poor visibility, and mechanical switches. Additionally, greenhouse gas emissions from the electricity industry and other stressors necessitate grid modernization. The proposed smart energy meter leverages Internet of Things (IoT) technology, enabling two-way data communication over LPWAN (Low Power Wide Area Network). These are this system's salient characteristics. The meter incorporates theft and tamper detection capabilities. Users receive notifications in case of any unauthorized interference. Key Words: Internet of Things (IoT), Light-dependent resistor (LDR), ESP8266 Microcontroller (NodeMCU), Liquid-crystal display, LoRaWAN, Energy Meter.