Reducing Greenhouse Gas Emissions through Improving the Life Span of Wooden Power Electric Poles of Eucalyptus saligna

The present work deals with reducing greenhouse gas emissions through improving the life span of wooden power electric poles of Eucalyptus saligna. Indeed, in Sub-Saharan African countries, Cameroon in particular, most of the power line networks are made of wooden supports and according to the Cameroon energy distribution company, wooden poles represent 32% of the causes of death linked to the state of the network. The company’s 2019 annual report indicates that 40,000 wooden poles were in critical condition and should be replaced. A significant number of mechanical failures affecting these supports have been observed. For example, on the HVA/LV power line “D17 Nko- abang” in Yaoundé in Cameroon, less than three years old, 10 (ten) cases of poles falling and/or breaking, due to their mechanical loading, were observed over a period of fewer than nine months, causing an average service stoppage for more than 11 hours and affecting an average of 3280 customers. These incidents lead to questions about how the supports are dimensioned and what load capacities they are designed to support. The aim of this work is, therefore, to suggest a method of dimensioning wooden poles hence reducing green- house gas emissions due to the deforestation by reducing the number of woo- den poles at risk to be replaced on Cameroon’s electricity distribution network. And more specifically, to reduce the number of mechanical failures affecting the wooden supports observed by analyzing the current wooden supports with their loads and to make proposals for improving the actual dimensioning me- thods. From the study carried out, it appears that 449 out of 845 supports, i.e., 53% needed to be replaced or monitored because they support the nominal forces ranging from 85% to 150% of their admissible limit and proposals have been made to improve their dimensioning.

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.

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.

Identification of Key Links in Electric Power Operation Based-Spatiotemporal Mixing Convolution Neural Network

As the scale of the power system continues to expand,the environment for power operations becomes more and more complex.Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately.Therefore,more reliable and accurate security control methods are urgently needed.In order to improve the accuracy and reliability of the operation risk management and control method,this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network.To provide early warning and control of targeted risks,first,the video stream is framed adaptively according to the pixel changes in the video stream.Then,the optimized MobileNet is used to extract the feature map of the video stream,which contains both time-series and static spatial scene information.The feature maps are combined and non-linearly mapped to realize the identification of dynamic operating scenes.Finally,training samples and test samples are produced by using the whole process image of a power company in Xinjiang as a case study,and the proposed algorithm is compared with the unimproved MobileNet.The experimental results demonstrated that the method proposed in this paper can accurately identify the type and start and end time of each operation link in the whole process of electric power operation,and has good real-time performance.The average accuracy of the algorithm can reach 87.8%,and the frame rate is 61 frames/s,which is of great significance for improving the reliability and accuracy of security control methods.

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.

NOVEL AIRCRAFT ELECTRICAL POWER DISTRIBUTION SYSTEM BASED ON DISTRIBUTED COMPUTER

As a matured technique used in many fields,the distributed computer system is still a new management method for the aeronautical electrical power distribution system in our country. In this paper, a novel aircraft electrical power distribution system based on the distributed computer system is proposed. The principles, features and structure of the aircraft electrical power distribution system and the distributed computer system named electrical load management system (ELMS) are studied. The ELMS composed of four electrical load management centers (ELMCs) and two power source processors (PSPs) operates in the 1553B buses. Principles of the ELMCs and the PSPs are introduced. With the application of the distributed computer system, the aircraft electrical power distribution system is simple, adaptable and flexible.

PARAMETER OPTIMIZATION OF ELECTRIC POWER STEERING INTEGRATED WITH ACTIVE FRONT STEERING FUNCTION

The dynanaic model of a novel electric power steering（EPS） system integrated with active front steer- ing function and the three-freedom steering model are built. Based on these models, the concepts and the quanti- tative expressions of road feel, sensitivity, and operation stability of the steering are introduced. Then, according to constrained optimization features of multi-variable function, a genetic algorithm is designed. Making the road feel of the steering as optimization objective, and operation stability and sensitivity of the steering as constraints, the system parameters are optimized by the genetic and the coordinate rotation algorithms. Simulation results show that the optimization of the novel EPS system by the genetic algorithm can effectively improve the road feel, thus providing a theoretical basis for the design and optimization of the novel EPS system.

Integrated Automation of Power Plant Electrical System

Aiming at the comparatively laggard level of power plant electrical system automation, this paper analyzes the feasibility,necessity and some key points of the application of integrated automation technology to power plant electrical system. New idea using fieldbus control system technology is presented. This paper also gives the outline and detailed schemes.

Technical Efficiency Analysis of Electric Power Industry with Stochastic Frontier Model

A kind of algorithm was provided to resolve the calculating problem of stochastic frontier model and applied to electric power industry.By Matlab,maximum likelihood estimation is adopted to evaluate σ and λ of stochastic frontier model in this paper, then the technical efficiency of electric power companies is calculated. The calculated and analyzed results reflect the situation of the management of electric power industry on the whole,that is ,the electric power companies with high technical efficiency are those which have developed their modern enterprise system successfully.

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.

H∞ control of novel active steering integrated with electric power steering function

Based on the traditional active steering system, a novel active steering system integrated with electric power steering function was introduced, which can achieve the functions of both active steering and electric power steering. In view of the interference from road random signal and sensor noise in the novel active steering system, the H∞ control model of the novel active steering system was built. With satisfying steering feel, good robust performance and steering stability being the control objectives, the H∞ controller for the novel active front steering (AFS) system was designed. The simulation results show that the novel AFS system with H∞ control strategy can attenuate the road interference quickly, and there is no resonance peak in the bode diagram. It can make the driver obtain more useful information in the low frequency range, and attenuate the road interference better in the high frequency range, thus the driver can get more satisfying road feeling. Therefore, the designed H∞ controller can synthesize the advantages of both robust performance and robust stability, and has certain contribution to the design of novel AFS system.

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

China＇s energy carbon emissions are projected to peak in 2030 with approximately 110% of its 2020 level under the following conditions： 1） China＇s gross primary energy consumption is 5 Gtce in 2020 and 6 Gtce in 2030; 2） coal＇s share of the energy consumption is 61% in 2020 and 55% in 2030; 3） non-fossil energy＇s share increases from 15% in 2020 to 20% in 2030; 4） through 2030, China＇s GDP grows at an average annual rate of 6%; 5） the annual energy consumption elasticity coefficient is 0.30 in average; and 6） the annual growth rate of energy consumption steadily reduces to within 1%. China＇s electricity generating capacity would be 1,990 GW, with 8,600 TW h of power generation output in 2020. Of that output 66% would be from coal, 5% from gas, and 29% from non-fossil energy. By 2030, electricity generating capacity would reach 3,170 GW with 11,900 TW h of power generation output. Of that output, 56% would be from coal, 6% from gas, and 37% from non-fossil energy. From 2020 to 2030, CO2 emissions from electric power would relatively fall by 0.2 Gt due to lower coal consumption, and rela- tively fall by nearly 0.3 Gt with the installation of more coal-fired cogeneration units. During 2020--2030, the portion of carbon emissions from electric power in China＇s energy consumption is projected to increase by 3.4 percentage points. Although the carbon emissions from electric power would keep increasing to 118% of the 2020 level in 2030, the electric power industry would continue to play a decisive role in achieving the goal of increase in non-fossil energy use. This study proposes countermeasures and recommendations to control carbon emissions peak, including energy system optimization, green-coal-fired electricity generation, and demand side management.

Integration optimization of novel electric power steering system based on quality engineering theory

The dynamic model of a novel electric power steering （EPS） system integrated with active front steering function （the novel EPS system） is built. The concepts and quantitative expressions of the steering road feel, steering sensibility, and steering operation stability are introduced. Based on quality engineering theory, the optimization algorithm is proposed by integrating the Monte Carlo descriptive sampling, elitist non-dominated sorting genetic algorithm （NSGA-II） and 6-sigma design method. With the steering road feel and the steering portability as optimization targets, the system parameters are optimized by the proposed optimization algorithm. The simulation results show that the system optimized based on quality engineering theory can improve the steering road feel, guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the novel electric power steering system.

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.

Performance optimization of electric power steering based on multi-objective genetic algorithm

The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.

Optimal design and applicability of electric power steering system for automotive platform

The ongoing need for better fuel economy and lower exhaust pollution of vehicles has increased the employment of electric power steering(EPS)in automotives.Optimal design of EPS for a product family reduces the development and fabrication costs significantly.In this paper,the TOPSIS method along with the NSGA-Ⅱis employed to find an optimum family of EPS for an automotive platform.A multi-objective optimization problem is defined considering road feel,steering portability,RMS of Ackerman error,and product family penalty function(PFPF)as the conflicting objective functions.The results for the single objective optimization problems and the ones for the multi-objective optimization problem,as well as two suggested trade-off design points are presented,compared and discussed.For the two suggested points,performance at one objective function is deteriorated by about 1%,while the commonality is increased by 20%–40%,which shows the effectiveness of the proposed method in first finding the non-dominated design points and then selecting the trade-off among the obtained points.The results indicate that the obtained trade-off points have superior performance within the product family with maximum number of common parts.

A graphic monitoring method for electric power of VVVF hydraulic system

In order to online monitor the running state of variable voltage and variable frequency(VVVF)hydraulic system,this paper presents a graphic monitoring method that fuses the information of variable frequency electric parameters.This paper first analyzes how the voltage and current of the motor stator change with the operation conditions of VVVF hydraulic system.As a result,we draw the relationship between the electric parameters(voltage and current)and power frequency.Then,the signals of the voltage and current are fused as dynamic figures based on the idea of Lissajous figures,and the values of the electric parameters are related to the features of the dynamic figures.Rigorous theoretical analysis establishes the function between the electric power of the variable frequency motor(VFM)and the features of the plotted dynamic figures including area of diagram,area of bounding rectangle,tilt angle,etc.Finally,the effectiveness of the proposed method is verified by two cases,in which the speed of VFM and the load of VVVF hydraulic system are changed.The results show that the increase of the speed of VFM enhances its three-phase electric power,but reduces the tilt angle of the plotted dynamic figures.In addition,as the load of VVVF hydraulic system is increased,the three-phase electric power of VFM and the tilt angle of the plotted dynamic figures are both increased.This paper provides a new way to online monitor the running state of VVVF hydraulic system.

Precise Compound Control of Loading Force for Electric Load Simulator of Electric Power Steering Test Bench

Electric load simulator(ELS) systems are employed for electric power steering(EPS) test benches to load rack force by precise control. Precise ELS control is strongly influenced by nonlinear factors. When the steering motor rapidly rotates, extra force is directly superimposed on the original static loading error, which becomes one of the main sources of the final error. It is key to achieve ELS precise loading control for the entire EPS test bench. Therefore, a three-part compound control algorithm is proposed to improve the loading accuracy. First, a fuzzy proportional–integral plus feedforward controller with force feedback is presented. Second, a friction compensation algorithm is established to reduce the influence of friction. Then, the relationships between each quantity and the extra force are analyzed when the steering motor rapidly rotates, and a net torque feedforward compensation algorithm is proposed to eliminate the extra force. The compound control algorithm was verified through simulations and experiments. The results show that the tracking performance of the compound control algorithm satisfies the demands of engineering practice, and the extra force in the ELS system can be suppressed by the net torque corresponding to the actuator’s acceleration.

Increased summer electric power demand in Beijing driven by preceding spring tropical North Atlantic warming

By using electric power data,observational station temperature data in Beijing,CN05.1 temperature data,ERA5 atmospheric reanalysis data,and ERSST.v3 b sea surface temperature(SST) data,it is found that summer(JulyAugust) electric power demand in Beijing is remarkably positively correlated with the previous spring(MarchApril) tropical North Atlantic(TNA) SST anomaly(SSTA).The possible physical mechanism of the TNA SSTA affecting summer electric power in Beijing is also revealed.When a positive SSTA occurs in the TNA during spring,anomalous easterlies prevail over the tropical central Pacific,which can persist to the following summer.Trade winds are thus enhanced over the northern Pacific,which favors a strengthening of upwelling cold water in the tropical central-eastern Pacific.As a result,a negative SSTA appears in the central-eastern Pacific in summer,which means a La Nina event is triggered by the previous TNA SSTA through the Bjerknes feedback.During the La Nina event,an anomalous anticyclonic circulation occupies the northwestern Pacific.The southerly anomalies at the western edge of this anomalous anticyclone strengthen the transportation of warm and humid airflow from the low latitudes to North China,where Beijing is located,causing higher summer temperatures and increased electricity usage for air conditioning,and vice versa.The results of this study might provide a new scientific basis and dues for the seasonal prediction of summer electric power demand in Beijing.

Study on Characteristic of Electric Power Assist Steering System

A pinion-type electric power steering (EPS) equipped on a sedan is reached in this paper. A three-freedom dynamic model of this system is created. The variables affecting assist character is analyzed. The formulas of simpled steering resistance force and the relationship between assist gain and vehicle speed are presented for the first time. Assist character is found based on the parameters of a sedan at last. This assist character is fit for the control rule of the EPS system through analyzing this character. The assist character figure offers reference for system design and control. Furthermore, this research method has generality for assist character of different kinds of vehicles.