Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

Intelligent Power Grid Load Transferring Based on Safe Action-Correction Reinforcement Learning

When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be conducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. Consideringthat the reinforcement learning model performs poorly in satisfying safety constraints, a safe action-correctionframework is proposed to modify the learning model. In the framework, the action of load shedding is correctedaccording to sensitivity analysis results under a small discrete increment so as to match the constraints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.

Tracking Performance of Electric Power Steering System Based on the Mixed H_2/H_∞ Strategy

The tracking performance of motor current is an important factor that affects the assistance torque of electric power steering （EPS） system. Bad tracking performance will cause assistant torque delay, and make road feeling bad, and is influenced by the input steering torque and system measuring noise. However the existing methods have some shortages on system＇s robust dynamic performance and robust stability. The mixed H2/H∞ strategy for recirculating ball-type EPS system in a pure electric bus is proposed, and vehicle dynamic model of the system is established. Due to the existence of system model uncertainty, disturbance signals, sensor noises and the demand of system dynamic performance, the indexes of robust performance and road feeling for drivers are defined as the appraisal control objectives. The H∞ method is introduced to design the H∞ controller, and the H2 method is applied to optimize the H∞ controller, thus the mixed H2/H∞ controller is designed. The response of EPS system to the motor current command with amplitude of 20 A, the road disturbance with amplitude of 500 N and the sensor random noise with the amplitude of 1 A is simulated. The simulation results show that the recirculating ball-type EPS system with the mixed H2/H∞ controller can attenuate the random noises and disturbances and track the boost curve well, so the mixed H2/H∞ controller can improve the system＇s robust performance and dynamic performance. For the purpose of verifying the performance of the designed control strategy, the motor current tracking performance ground tests are conducted with step response input of the steering wheel, double-lane steering test and lemniscate steering test, respectively. The tests show that the mixed H2/H∞ controller for the recirculating ball-type EPS system of pure electric bus is feasible. The designed controller can solve the robust performance and robust stability of the system, thus improve the tracking performance of the EPS system and provide satisfied road feeling for the drivers.

Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

Model development and parameter investigation of a column-type electric power steering system

In this paper, the performance of a column-type electric power steering （EPS） system and vehicle has been studied and a detailed mathematical model for the system has been established. Based on the mathematic model of the optimization design for steering feel, the parameters of the EPS system and vehicle on steering performance have been investigated. Moreover, the effects of the parameters on system stability have been analyzed and compared by the method of absolute sensitivity and the results are given in the end.

Economic Dispatch of Electrical Power System Based on the Multi-objective Co-evolutionary Algorithm

It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex when the general power systems are combined with wind farms. The short term wind power prediction method was discussed in this paper. The method was based on the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). Furthermore,the effect of wind farms on the traditional economic dispatch of electrical power system was analyzed. The mathematical model of the economic dispatch was established considering the environmental factors and extra spinning reserve cost. The multi-objective co-evolutionary algorithm was used to figure out the model. And the results were compared with the NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ) to verify its feasibility.

Intelligent Vehicle Electrical Power Supply System with Central Coordinated Protection

The current research of vehicle electrical power supply system mainly focuses on electric vehicles（EV） and hybrid electric vehicles（HEV）.The vehicle electrical power supply system used in traditional fuel vehicles is rather simple and imperfect;electrical/electronic devices（EEDs） applied in vehicles are usually directly connected with the vehicle＇s battery.With increasing numbers of EEDs being applied in traditional fuel vehicles,vehicle electrical power supply systems should be optimized and improved so that they can work more safely and more effectively.In this paper,a new vehicle electrical power supply system for traditional fuel vehicles,which accounts for all electrical/electronic devices and complex work conditions,is proposed based on a smart electrical/electronic device（SEED） system.Working as an independent intelligent electrical power supply network,the proposed system is isolated from the electrical control module and communication network,and access to the vehicle system is made through a bus interface.This results in a clean controller power supply with no electromagnetic interference.A new practical battery state of charge（So C） estimation method is also proposed to achieve more accurate So C estimation for lead-acid batteries in traditional fuel vehicles so that the intelligent power system can monitor the status of the battery for an over-current state in each power channel.Optimized protection methods are also used to ensure power supply safety.Experiments and tests on a traditional fuel vehicle are performed,and the results reveal that the battery So C is calculated quickly and sufficiently accurately for battery over-discharge protection.Over-current protection is achieved,and the entire vehicle＇s power utilization is optimized.For traditional fuel vehicles,the proposed vehicle electrical power supply system is comprehensive and has a unified system architecture,enhancing system reliability and security.

Protection Strategies against Cascading Failure for Power Systems of Ring Network

Power grid vulnerability is a key issue with large blackouts, causing power disruption for millions of people. The complexity of power grid, together with excessive number of components, makes it difficult to be modeled. Currently, researchers use complex networks to model and study the performance of power grids. In fact, power grids can be modeled into a complex network by making use of ring network topology, with substations and transmission lines denoted as nodes and edges, respectively. In this paper, three protection schemes are proposed and their effectiveness in protecting the power network under high and low-load attacks is studied. The proposed schemes, namely, Cascaded Load Cut-off (CLC), Cascaded Load Overflow (CLO) and Adaptive-Cascaded Load Overflow (A-CLO), improve the robustness of the power grids, i.e., decrease the value of critical tolerance. Simulation results show that CLC and CLO protection schemes are more effective in improving the robustness of networks than the A-CLO protection scheme. However, the CLC protection scheme is effective only at the expense that certain percentage of the network will have no power supply. Thus, results show that the CLO protection scheme dominates the other protection schemes, CLC and A-CLO, in terms of the robustness of the network, improved with the precise amount of load cut-off determined.

Seismic reliability analysis of large electric power systems

Based on the De.Morgan laws and Boolean simplification, a recursive decomposition method is introduced in this paper to identify the main exclusive safe paths and failed paths of a network. The reliability or the reliability bound of a network can be conveniently expressed as the summation of the joint probabilities of these paths. Under the multivariate normal distribution assumption, a conditioned reliability index method is developed to evaluate joint probabilities of various exclusive safe paths and failed paths, and, finally, the seismic reliability or the reliability bound of an electric power system. Examples given in the paper show that the method is very simple and provides accurate results in the seismic reliability analysis.

Development of Simulated Testbed for Electrical Power Subsystem of a Certain Kind of Satellite

In order to testify and examine the ability and correctness of an expert system for diagnosing the faults in the electrical power system of a certain kind of satellite, the authors have developed a simulated testbed according to the operational principle of the electrical power system. This paper takes the solar battery array as an instance to introduce the designing principle of its hardware circuits, and presents the methods to design the interface and the software program of the single-chip microprocessor system. The software scheme of the upper computer is introduced at the end of this paper. It has been proved that this simulated system could effectively achieve the complete functions coupled with the simple design by using of various mature techniques in the fields of electronic circuits, single-chip microprocessor and numerical emulation.

Development of a methodology for assessing the adequacy of electric power systems

This study presents the results of a research into the developing a methodology for assessing the adequacy of advanced electric power systems characterized by the integration of various innovative technologies,which complicates their analysis.The methodology development is aimed at solving two main problems:(1)increase the adequacy of modeling the processes that occur in the electric power system and (2)enhance the computational efficiency of the adequacy assessment methodology.This study proposes a new mathematical model to minimize the power shortage and enhance the adequacy of modeling the processes.The model considers quadratic power transmission losses and network coefficients.The computational efficiency of the adequacy assessment methodology is enhanced using efficient random-number generators to form the calculated states of electric power systems and machine learning methods to assess power shortages and other reliability characteristics in the calculated states.

Smart Meter Development for Cloud-Based Home Electricity Monitor System

Αcloud-based home electricity data-monitoring system,which is based on an Arduino Mega controller,is proposed for monitoring the electricity consumption(electrical power)and power quality(PQ)in home.This system is also capable of monitoring the fundamental frequency and supply-voltage transients to ensure that the appliances operate in a safe operation range.The measured data(voltage and current)are transmitted through a Wi Fi device between the Arduino controller and server.The transmission control protocol(TCP)server is set up to acquire the high-data transmission rate.The server system immediately displays the calculated parameters and the waveform of the acquired signal.A comparison with a standard measurement device shows that the proposed system,which can be built at a low cost,exhibits the same functions as a factory product.

An Improved Immune Clone Selection Algorithm for Parameters Optimization of Marine Electric Power System Stabilizer

In themarine electric power system,the marine generators will be disturbed by the large change of loads or the fault of the power system.The marine generators usually installed power system stabilizers to damp power system oscillations through the excitation control.This paper proposes a novel method to obtain optimal parameter values for Power System Stabilizer(PSS)to suppress low-frequency oscillations in the marine electric power system.In this paper,a newly developed immune clone selection algorithm was improved from the three aspects of the adaptive incentive degree,vaccination,and adaptive mutation strategies.Firstly,the typical PSS implementation type of leader-lag structure was adopted and the objective function was set in the optimization process.The performance of PSS tuned by improved immune clone selection algorithm was compared with PSS tuned by basic immune clone selection algorithm(ICSA)under various operating conditions and disturbances.Then,an improved immune clone selection algorithm(IICSA)optimization technique was implemented on two test systems for test purposes.Based on the simulations,it is found that an improved immune clone selection algorithm demonstrates superiority over the basic immune clone selection algorithm in getting a smaller number of iterations and fast convergence rates to achieve the optimal parameters of the power system stabilizers.Moreover,the proposed approach improves the stability and dynamic performance under various loads conditions and disturbances of the marine electric power system.

Towards an Ethical and Ecological Approach to Electricity Generation: A Comparative Analysis of Coal and Nuclear Power in the USA

According to the US Energy Information Administration, about 4118 billion kilowatt-hours (kWh) electricity was generated at large-scale generation facilities in 2019. About 63% of this was from fossil fuels, e.g., coal, natural gas, petroleum, and other gases. Environmental exposure to particulates, sulfur dioxide, nitrogen oxides, mercury, arsenic, radioactive fly ash, and other pollutants are extremely detrimental to the human cardiovascular, respiratory, and nervous systems. Such exposure increases the risk of lung cancer, stroke, heart disease, chronic respiratory diseases, respiratory infections, and other illnesses. In light of the challenges associated with renewables providing large quantities of base load power, as well as other factors, the benefits offered by nuclear power should be reexamined by policy makers to move the country towards a more ecological and ethical method of electric power production. This paper offers a concise analysis of many of the salient issues, comparing electricity generation from coal plants and light water nuclear reactors.

Experimental Study on Cloud-Computing-Based Electric Power SCADA System

With the development of smart grid, the electric power supervisory control and data acquisition （SCADA） system is limited by the traditional IT infrastructure, leading to low resource utilization and poor scalability. Information islands are formed due to poor system interoperability. The development of innovative applications is limited, and the launching period of new businesses is long. Management costs and risks increase, and equipment utilization declines. To address these issues, a professional private cloud solution is introduced to integrate the electric power SCADA system, and conduct experimental study of its applicability, reliability, security, and real time. The experimental results show that the professional private cloud solution is technical and commercial feasible, meeting the requirements of the electric power SCADA system.

Cross-spectral root-min-norm algorithm for harmonics analysis in electric power system

To avoid drawbacks of classic discrete Fourier transform(DFT)method,modern spectral estimation theory was introduced into harmonics and inter-harmonics analysis in electric power system.Idea of the subspace-based root-min-norm algorithm was described,but it is susceptive to noises with unstable performance in different SNRs.So the modified root-min-norm algorithm based on cross-spectral estimation was proposed,utilizing cross-correlation matrix and independence of different Gaussian noise series.Lots of simulation experiments were carried out to test performance of the algorithm in different conditions,and its statistical characteristics was presented.Simulation results show that the modified algorithm can efficiently suppress influence of the noises,and has high frequency resolution,high precision and high stability,and it is much superior to the classic DFT method.

Impacts of a Japan–South Korea power system interconnection on the competitiveness of electric power companies according to power exchange prices

In many regions,international power system interconnections provide economic,energy-security,environmental,and technical benefits.In contrast,such interconnections remain scarce in Northeast Asia.In 2016,after approving a joint memorandum of understanding between major electric power companies from China,Japan,South Korea,and Russia,related initiatives regained momentum in the region.Nevertheless,the corresponding developments in Japan remain limited,mainly owing to the lack of involvement of Japanese electric power companies.This study represents a pioneering attempt to provide an economic assessment based on power exchange prices of a power system interconnection between Japan and South Korea regarding the competitiveness of electric power companies in terms of competitive business segments and strategic consequences.We found that although the position of Japanese generators may slightly deteriorate,that of the supply segment would substantially improve,thus suggesting that more opportunities than threats are derived from the interconnection.This promising outcome may foster the adoption of an interconnection with South Korea considering the positive economic and business perspectives in Japan.Furthermore,realizing the interconnection may improve the energy security and air quality in the region.