Amount Of Electricity Research Articles

Implications of hydrogen import prices for the German energy system in a model-comparison experiment

With its ability to store and transport energy without releasing greenhouse gases, hydrogen is considered an important driver for the decarbonisation of energy systems. As future hydrogen import prices from global markets are subject to large uncertainties, it is unclear what impact different hydrogen and derivative import prices will have on the future German energy system. To answer that research question, this paper explores the impact of three different import price scenarios for hydrogen and its derivatives on the German energy system in a climate-neutral setting for Europe in 2045 using three different energy system models. The analysis shows that the quantities of electricity generated as well as the installed capacities for electricity generation and electrolysis increase as the hydrogen import price rises. However, the resulting differences between the import price scenarios vary across the models. The results further indicate that domestic German (and European) hydrogen production is often cost-efficient.

A research report on the phase-domain trajectories of fault recording and their mathematical models

In currently known theories and algorithms of fault recording analysis and application, there is little literature where fault feature parameters are mined deeply from electrical physical quantities themselves. In this report the calculation method of the phase angles of the reference point and sample points is obtained, which ensures the correspondence of the time-domain waveform of digital fault recording with its phase-domain trajectory. The relationship between the initial phase angle of a sinusoid and the position of its trajectory, the characteristics of the trajectories of three-phase short-circuit currents containing dc components and the mathematical models of these trajectories are analyzed. Taking a rectangular wave current and a triangle wave current as example, the characteristics of the trajectories of non-sinusoidal and periodical waveforms containing harmonics are analyzed as well as their mathematical models. The research results show that the relationship between the initial phase angle of a sinusoid and the position of its circular trajectory is definite; the dc components have no impact on the positions of the trajectories of the short-circuit currents, but on their sizes and shapes; the harmonics have an impact on the shapes of the trajectories, and their positions are decided by the initial phase angles of the ac fundamental components in the waveforms. Subsequent study of the algorithm of fault recording analysis will be spread based on the contents in this report.

A fault diagnosis method of battery internal short circuit based on multi-feature recognition

The internal short circuit (ISC) fault has been considered as one of the most serious problems, which may pose a threat to the operation safety of the battery system. To solve this problem, this paper proposes an ISC fault diagnosis method based on multi-feature recognition to distinguish aging and ISC fault. The ISC equivalent circuit model is established first. In addition, three characteristic parameters, including the slope of the “rebound” voltage curve, the “valley” ordinate in the differential voltage (DV) curve, and the electric quantity, namely high segment charging capacity (HSCC) between the valley point of the DV curve and the end of charging position, are extracted to distinguish the ISC battery from aging battery. The results show that the proposed method can effectively distinguish between ISC batteries, aging batteries, and normal batteries. Moreover, the ISC resistance is able to be estimated accurately, with an error of less than 5.44%.

Environmental impact analysis of lithium iron phosphate batteries for energy storage in China

The deployment of energy storage systems can play a role in peak and frequency regulation, solve the issue of limited flexibility in cleaner power systems in China, and ensure the stability and safety of the power grid. This paper presents a comprehensive environmental impact analysis of a lithium iron phosphate (LFP) battery system for the storage and delivery of 1 kW-hour of electricity. Quantities of copper, graphite, aluminum, lithium iron phosphate, and electricity consumption are set as uncertainty and sensitivity parameters with a variation of [90%, 110%]. The results show that global warming potential is 9.08E+01 kg CO2 eq. and fossil resource use is 1.21E+03 MJ, with uncertainty ranges of [8.54E+01, 9.23E+01] and [1.15E+03, 1.23E+03], respectively. Electricity consumption during the manufacture and installation process is the greatest contributor to climate change (CO2 eq. emissions), accounting for 39.71% and largely owing to non-renewable sources, followed by cathode materials at 27.85% and anode materials at 18.36%. The disposal and recycling process offers emission reductions but requires an additional 1.17% use of fossil resources. Sobol T indices for the quantity of electricity are the highest for acidification, climate change, fossil resource use, and ionizing radiation. By considering the pathway of China’s electricity mix from 2020 to 2050 under the Paris Agreement’s 2° target, the potential for environmental emission reduction in the system is evaluated. The results show that the greener electricity mix could lead to a 24.59% reduction in acidification impact, a 35.74% reduction in climate change impact, a 33.24% reduction in fossil resource use, and a 44.13% reduction in ionizing radiation impact. This study offers a comprehensive view of the environmental impact reductions associated with the lithium iron phosphate battery and its industry.

Improving flatness of machined surface in rotating cathode electrochemical milling

Electrochemical milling has broad application prospects for machining large aeronautical thin-walled components. This is because this technique has no cutting force, has no heat-affected zones, and is considerably flexible. In contrast to the non-rotating tool cathode of traditional electrochemical milling, the rotating cathode used in electrochemical milling has more promising prospects because it has the same motion mode as the milling cutter employed in mechanical milling. However, because of the uneven electric quantity supply from the cylindrical rotating cathode, the machined surface typically has a curved profile with inadequate surface flatness; this is the main drawback of rotating-cathode electrochemical milling. To improve the flatness of surfaces processed by rotating-cathode electrochemical milling, a novel multichannel cathode with the outlet hole arrangement that can improve the uniformity of electric quantity supply is proposed. Numerous large outlet holes are bored at the bottom center of multichannel rotating cathode. Numerical simulation results indicate that these holes cause a decrease in the electric quantity supply from the inner area at the bottom of the cathode from the perspectives of electric and flow fields, minimizing the unevenness of the electric quantity supply distribution. Validation experiments prove that compared with previously reported rotating cathodes, the straightness index and depth error of the surface machined by novel multichannel cathode are reduced by 80.9 % and 69.4 %, respectively. After obtaining grooves with flat surfaces, the step-over distance required to machine a plane using a multichannel rotating cathode increases; meanwhile, the flatness of the machined plane significantly improves. With the applied voltage of 25 V, electrolyte pressure of 0.2 MPa, initial inter-electrode gap of 0.2 mm, and cathode rotational speed of 500 rpm, a 42 × 40 mm plane is finally machined, whose planeness index (Δhp) is only 0.047.

Study on the algorithm of fault recording analysis combining its time-domain waveforms with phase-domain trajectories

The untimely handling of faults in a power system has a negative impact on its operation and even the national economy, and this requires coordination in the functions of protective relaying as well as supervisory & control devices, where digital fault recorders are used to record fault waveforms of electrical physical quantities. The fault recording of a simulated current is taken as the research object in this article, and it is transformed from the time-domain waveform into a phase-domain trajectory, which is used to analyze fault feature parameters and then reformulate the waveform. The original waveform of the current will be substituted by the reformulated one with fault features to realize functions in the power system. The algorithm of reformulating fault recording, the correlativity of the reformulated waveform and its original one, and errors produced in the research process are researched. The high correlation coefficient between the reformulated waveform and its original one shows that the algorithm studied in the article offers a simple and convenient option for fault recording analysis.

Analysis and Determination of Self-Inductance through Direct and Indirect Measurements Methods

Practicum is an activity that helps students to understand an abstract concept. One of the concepts in physics that requires practicum is the concept of electricity. Inductance is an electrical quantity studied in high and vocational high schools. This study aims to determine the inductor's inductance value using several methods and analyze the most suitable method for determining the inductor inductance value. The inductor used is a commercial inductor with a color band code with an inductance value of 2.7 mH and a tolerance of 10%. Inductor inductance measurements were carried out using a benchtop LCR meter, handheld LCR meter, series RLC method, and LC resonance method. Each measuring instrument requires a frequency setting: refer to the manual for benchtop and handheld LCR meters, the resonant frequency for the serial RLC method, and adjusting the AFG (arbitrary function generator) frequency. Hence, a clear oscillation pattern is visible on the oscilloscope. The results of this study indicate that measurements using benchtop LCR meters, handheld LCR meters, and LC resonance methods produce inductance values within the inductance tolerance limits.

Analysis of the Efficiency of Landfill Gas Treatment for Power Generation in a Cogeneration System in Terms of the European Green Deal

Climate change and environmental degradation pose a threat to Europe and the world. The mechanism that will address these challenges is the European Green Deal, which envisions transforming the EU into a modern, resourceful, economical and competitive economy, aiming for zero greenhouse gas emissions. Landfill gas generated in a landfill waste deposit poses a threat to the environment and people. In this aspect, its capture, treatment and safe neutralization or use for energy purposes are important. Treatment of landfill gas, which is the fuel for gas engines in cogeneration units, is crucial for their proper operation and the quantity and quality of electricity and heat generated. The purpose of this study was to perform research to determine the hydrogen sulfide content of landfill gas and the actual efficiency of hydrogen sulfide removal from the gas using activated carbon. The tests performed constitute the basis for the reliable operation of gas engines in cogeneration installations and are dedicated mainly to the operators of these installations. Accordingly, three measurement campaigns were carried out, each with 42 measurements, the first for the “raw” gas obtained directly from the landfill, the second for the gas before entering the carbon filter and the third after its treatment. In addition, surface analysis was performed, and the elemental composition of the “fresh” molded activated carbon constituting the filter material was determined using a scanning electron microscope with an EDS system. The results showed a high elemental content of carbon in the test sample at 92.78%, while the efficiency of hydrogen sulfide removal from landfill gas by activated carbon, calculated from the measurements, was 97.05%. The obtained test results confirmed the validity of using impregnated activated carbon to remove hydrogen sulfide from landfill gas and its high adsorption efficiency, which can consequently result in reliable operation of the gas engine in the cogeneration unit and ultimately fit in with the objectives of the European Green Deal. The research results are an incentive for operators of cogeneration installations to systematically examine the quality of landfill gas and the efficiency of biogas purification devices.

Pair of dyon production near magnetized dyonic Reissner-Nordstrom black holes* *Supported by LPPM UNPAR

We investigate the phenomenon of pair production of massive scalar particles with magnetic charge near the horizon of a magnetized dyonic Reissner-Nordstrom black hole. The intrinsic symmetry between the electric and magnetic quantities in the Einstein-Maxwell equations suggests that the pair can be generated through Hawking radiation and the Schwinger effect, provided that the Dirac quantization condition is satisfied.

A real-time energy flow management of a grid-connected renewable energy sources-based EV charging station

ABSTRACT As the sales of electric vehicles (EVs) increase in India, there will be an increase in the number of charging stations in the future. Meanwhile, the demand for extra power from the grid and intermittent power from renewable energy presents significant challenges for charging infrastructure. This paper presents a real-time energy flow management strategy (EFMS) designed for an EV charging station (EVCS) that utilises power from renewable energy sources (RES), an energy storage battery unit (ESBU), and the grid. The primary objective is to increase the utilisation of renewable energy and minimise the quantity of electricity bought during the peak period of the grid by implementing direct electric vehicle load control. EVCS has been designed to charge up to 80 EVs using five DC chargers. The EFMS aims to enhance the scheduling of EV charging by considering grid time-of-use (ToU) pricing and efficient usage of ESBU in terms of battery degradation effect and maximising the use of RES. A multi-objective optimisation algorithm has been developed for EV scheduling. The baseline uncoordinated charge method is contrasted with the proposed approach. The EFMS effectiveness is tested in MATLAB, and the subsequent analysis and results are drawn and discussed.

ANN-Fuzzy Hybrid Control Strategy for MPPT of Grid-connected PV System with Battery Storage under Fast-charging Atmospheric Condition

Abstract: The use of solar energy through photovoltaic arrays is continually expanding and has recently been regarded as one of the cleanest sources of energy. Increasing the amount of electricity provided to the load is one method for lowering the cost of solar systems. Contrarily, altering the load creates a divergence from the maximum power point (MPP) and changes the operating point of the solar conversion system. Due to this, attention has been given to MPPT techniques that can be used with solar systems in numerous research investigations. In this paper, we implement an MPPT method based on an Artificial Neural Network (ANN). This method combined two controllers, ANN and fuzzy logic controller, under the name ANNFuzzy logic hybrid. In the first stage, ANN can determine Vmpp from irradiation and temperature, and both of them are variable. In the second stage, this Vmpp has been corrected by implementing Fuzzy logic in order to minimize the error of the voltage and VMPP. ANN-fuzzy hybrid has been simulated in Matlab-Simulink and was found to be the best solution to follow the maximum power point when irradiation and temperature are varied. The energy extracted from PV is delivered to a battery in order to inject this power into the smart grid by using an inverter controlled by PID. Finally, a LC filter has been used to eliminate the harmonics and compensate for the reactive power. For energy storage, we consider the utilization of lithiumion batteries, which are recognized as an optimal solution for storing energy efficiently. To manage the charge and discharge of the battery, we employ a PID controller and a buck-boost converter. Through this research, we aim to explore the performance and effectiveness of the hybrid ANN-fuzzy simulation for the boost converter system. By combining the capabilities of ANN and fuzzy logic, we expect to achieve improved control and optimization of the power conversion processes in the system. Additionally, the integration of lithium-ion batteries and the use of the PID controller and buck-boost converter allow for efficient management of energy storage and retrieval. Overall, this study investigates the hybrid ANN-fuzzy simulation for the boost converter system, highlighting the integration of various components and control techniques to enhance the performance and efficiency of the system.

A study of voltage rise in distribution grids with high concentration of power generators

The growing demand for electric power together with the environmental agencies pressure for decreasing polluting gases emission are the main causes of the big expansion that Distributed Generation systems have been undergoing lately. This kind of electric generation system allows to produce parts of the electricity power nearby the costumers making energy costs cheaper for final consumer and improving the share of clean sources on the energy matrix. Despite Germany’s great experience with photovoltaic plants, Distributed Generation systems are not well widespread around the world. Most governmental regulations about the theme are recent and sometimes do not cover all the specificities, so it has been continuously rewritten. Although Brazilian market has a small concentration of sources connected to the distribution grids, the annual relative growth is significant. High concentration of sources nearby the costumers may cause problems in the operation and in the stability of electric quantities. Some of these problems are voltage rises, harmonics and general damages to electrical equipment. This paper presents the voltage rise effect in distribution grids with high concentration of generators; it also suggests mitigation techniques for this outcome. It becomes clear that is possible to reverse power flow without voltage rise beyond legal limits.

Analyzing electric power quality in arc furnaces

The paper presents the analysis of the results carried out at Lloyds Steel Industries, Wardha, Maharashtra State, India. The various electrical quantities like voltages, currents, frequency, and flicker etc. regarding power quality are measured and recorded at different voltage buses; the same are compared with power quality standards. The AC Electric arc furnaces generate harmonics. Power quality disturbances such as harmonics, snapshots, and transients are investigated and found to be high.

Load Profile Forecasting using a Time Series Model for Solar Rooftop and Integrated Carpark of a Public University in Malaysia

A precise and accurate load prediction is critical in a developing country like Malaysia to save the energy consumption. Power producers use load profile data and statistics to analyze and forecast the quantity of electricity required to be available at a given time. Load forecasting is the process of predicting future load requirements and this research focuses on the short-term load forecasting (STLF) for solar rooftop and integrated car park built at one of the public universities in Malaysia. Power system planners and demand controllers must ensure that there is enough generation to meet the increased demand. Load forecasting models that are accurate can lead to better budgeting, maintenance scheduling, and fuel management. This project seeks to anticipate the highest demand of power utilized by the consumer based on prior load profiles using a Multiple Regression Time Series model developed using MATLAB software. It consists of the following steps: data collection, clustering, series transformation using differentiation transform to remove trend and seasonal structure from the dataset, model identification using autocorrelation function (ACF) and partial correlation function (PCF), model estimation using ARIMA time series errors and maximum likelihood probability, and finally model forecasting using Auto Regression (AR), Moving Average. In this case, the goal is to ensure the power production equals electricity demand, and achieving the target will assure energy security, dependability, and the capacity to maximize profits while minimizing losses.

Enhancing Electric Vehicle Battery Capacity through Anode Material Modification

With global attention to environmental protection and sustainable development, the demand for electric vehicles is rapidly increasing. The high energy density, long lifespan, and fast charging ability of high-capacity lithium-ion batteries (LIBs) make them an ideal choice for electric vehicles. They provide a longer range for electric vehicles and meet the needs of consumers for efficient and environmentally friendly modes of transportation. The electrode material has a crucial impact on the capacity of lithium-ion batteries. A battery’s capacity is the maximum quantity of electricity it can discharge under specific discharge circumstances, and electrode material is one of the key factors determining this performance. This article summarizes several methods for modifying LIBs electrode materials, including nanostructures, surface modification, and alloying, to reveal the pathways that can be applied to enhance lithium-ion battery performance. In addition, this article also explores the current challenges faced by LIBs technology and proposes potential avenues for future research, providing useful information to anyone who wants to support the advancement of lithium-ion battery technologies.

Napelem hőterjedés vizsgálata elektromos paramétereinek a meghatározásához

Heat transfer processes in a photovoltaic (PV) silicon solar panel are simulated under standard circumstances. A model containing an intricate treatment of the incoming solar radiation, long-wave radiation, conduction, convection, and electrical power output is developed in mathematical form. To solve heat transfer problems, recent explicit numerical methods are utilized by our research group, which are efficient for different real-life problems, for example, simulating heat transfer in photovoltaic panels. Since very realistic results are obtained for the temperature of the silicon layer and the dependent electrical variables such as the power output, one can conclude that our model can adequately predict the electrical quantities.

Equilibrium Risk Decision Model for Bidding Electricity Quantity Deviation of Cascade Hydropower Stations

Equilibrium Risk Decision Model for Bidding Electricity Quantity Deviation of Cascade Hydropower Stations

Multi-Objective PSO for Control-Loop Tuning of DFIG Wind Turbines with Chopper Protection and Reactive-Current Injection

The control systems for the variable-speed wind turbine based on the Doubly Fed Induction Generator (DFIG) pose some tuning challenges. The performance and stability of DFIG wind turbines during faults in power grids are directly related to their controller settings. This work investigates how incorporating protection via a braking-Chopper controller connected to the DC link (DC Chopper) and a reactive-current injection during the PI-tuning process affects the performance of DFIG wind turbines during electrical faults. For the tuning process, the Multi-Objective-Particle-Swarm-Optimization (MOPSO) algorithm was used. Thus, two different approaches adopting this methodology were investigated, considering sequential and simultaneous tuning. The results showed that sequential tuning presented a better performance in relation to the reactive-current injection and lower amplitude deviations of the electrical quantities during and after the fault. On the other hand, simultaneous tuning reached damping of the mechanical oscillations faster and presented better performance of the protection system.

Research on high proportion of clean energy grid-connected oscillation risk prediction technology based on CNN and trend feature analysis

Oscillations, commonly known as a universal, propagative, and intricate event in the new power system, often give rise to generator tripping and load shedding, not only adversely affecting the power flow limit and the power angle stability but also posing threats to the lines of defense for stability and protection. Traditionally, emphasis has been laid on post-fault oscillation management, an emergency measure to deal with the impact and damage that have already affected the power grid. As such, this paper focuses on an oscillation prediction technique to detect oscillation energy early and intervene proactively to prevent further faults. This technique effectively lessens the damage caused by impacts and disconnects to the power grid. Firstly, this paper proposes the concept of disturbance power density and establishes the correlation between disturbance energy and the time domain, thereby exploring a method for evaluating the pattern of electrical quantities before power system oscillation. Secondly, it speeds up the time it takes to detect faults by catching nuances of voltage-current phase angle and impedance. Lastly, it puts forward a technique to cope with the intricacy and variety of power grid equipment using the convolutional neural network (CNN). This technique incorporates an integrated attention mechanism within a one-dimensional CNN model to capture the implicit mapping between voltage, active power, and reactive power at any time in the power system. This enables the model to self-learn multi-device characteristics and enhances the possibility of using theory in practical ways. Moreover, practical case studies also show that the prediction technique proposed in this paper can effectively issue warnings eight minutes before the occurrence of oscillation.

Smart Demand Side Management for Techno-Economic Analysis of Microgrid System

The world uses about 20 trillion kilowatt hours of electricity annually. Because of this great level of necessity, the use of green energy is growing and is becoming more and more significant in today's society. Demand-side management (DSM) programs are described as the procedures for planning, carrying out, and overseeing the tasks assigned by electric utilities to encourage customers to adjust their loads and energy usage in order to reduce power consumption and lower their electricity costs. It is utilized in smart grid systems to balance energy generation and consumption in a way that benefits both customers and utilities, to achieve the goals of utility energy policies, and to modify the quantity and quality of power and electricity used. Customers should have the capacity to control their energy consumption, especially during peak usage, to enable them to make better informed decisions. Demand response (DR) and energy efficiency techniques were employed by DSM to assist energy users in lowering their consumption. to increase resilience, economy, sustainability, and efficiency. The main objective of this study is to apply two demand side management strategies, examine power flow analysis on distribution networks utilizing IEEE rules both before and after PV cells are integrated, and assess the impact of doing so. The approaches' practicality is confirmed by comparing the simulation results from one technique with the other. For the end user, lowering their electricity cost is their primary goal.