Research on the longitudinal protection of a through-type cophase traction direct power supply system based on the empirical wavelet transform

This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a distinctive boundary structure.This approach capitalizes on the boundary’s capacity to attenuate the high-frequency component of fault signals,resulting in a variation in the high-frequency transient energy ratio when faults occur inside or outside the line.During internal line faults,the high-frequency transient energy at the checkpoints located at both ends surpasses that of its neighboring lines.Conversely,for faults external to the line,the energy is lower compared to adjacent lines.EWT is employed to decompose the collected fault current signals,allowing access to the high-frequency transient energy.The longitudinal protection for the traction network line is established based on disparities between both ends of the traction network line and the high-frequency transient energy on either side of the boundary.Moreover,simulation verification through experimental results demonstrates the effectiveness of the proposed protection scheme across various initial fault angles,distances to faults,and fault transition resistances.

Operation Control Method of Relay Protection in Flexible DC Distribution Network Compatible with Distributed Power Supply

A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.

Control of Hydraulic Power System by Mixed Neural Network PID in Unmanned Walking Platform

To speedily regulate and precisely control a hydraulic power system in a unmanned walking platform(UWP),based on the brief analysis of digital PID and its shortcomings,dual control parameters in a hydraulic power system are given for the precision requirement,and a control strategy for dual relative control parameters in the dual loop PID is put forward,a load and throttle rotation-speed response model for variable pump and gasoline engine is provided according to a physical process,a simplified neural network structure PID is introduced,and formed mixed neural network PID(MNN PID)to control rotation speed of engine and pressure of variable pump,calculation using the back propagation(BP)algorithm and a self-adapted learning step is made,including a mathematic principle and a calculation flow scheme,the BP algorithm of neural network PID is trained and the control effect of system is simulated in Matlab environment,real control effects of engine rotation speed and variable pump pressure are verified in the experimental bench.Results show that algorithm effect of MNN PID is stable and MNN PID can meet the adjusting requirement of control parameters.

Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.

Scheme of long distance power supply for electrified railway traction network based on traction cable

Purpose–The traction cable is paralleled with the existing traction network of electrified railway through transverse connecting line to form the scheme of long distance power supply for the traction network.This paper aims to study the scheme composition and power supply distance(PSD)of the scheme.Design/methodology/approach–Based on the structure of parallel traction network(referred to as“cable traction network(CTN)”),the power supply modes(PSMs)are divided into cableþdirect PSM and cableþautotransformer(AT)PSM(including Japanese mode,French mode and new mode).Taking cableþJapanese AT PSM as an example,the scheme of long distance power supply for CTN under the PSMs of co-phase and out-of-phase power supply are designed.On the basis of establishing the equivalent circuit model and the chain circuit model of CTN,taking the train working voltage as the constraint condition,and based on the power flow calculation of multiple train loads,the calculation formula and process for determining the PSD of CTN are given.The impedance and PSD of CTN under the cableþAT PSM are simulated and analyzed,and a certain line is taken as an example to compare the scheme design.Findings–Results show that the equivalent impedance of CTN under the cableþAT PSM is smaller,and the PSD is about 2.5 times of that under the AT PSM,which can effectively increase the PSD and the flexibility of external power supply location.Originality/value–The research content can effectively improve the PSD of traction power supply system and has important reference value for the engineering application of the scheme.

Outage Performance of Non-Orthogonal Multiple Access Based Unmanned Aerial Vehicles Satellite Networks

With rapid development of unmanned aerial vehicles(UAVs), more and more UAVs access satellite networks for data transmission. To improve the spectral efficiency, non-orthogonal multiple access(NOMA) is adopted to integrate UAVs into the satellite network, where multiple satellites cooperatively serve the UAVs and mobile terminal using the Ku-band and above. Taking into account the rain fading and the fading correlation, the outage performance is first analytically obtained for fixed power allocation and then efficiently calculated by the proposed power allocation algorithm to guarantee the user fairness. Simulation results verify the outage performance analysis and show the performance improvement of the proposed power allocation scheme.

The Application of Fuzzy Image Recognition in Power System

Electrified railway is an important but disturbing load in power system. In China railway electrification is gaining momentum at the end of this century.The Ministry of Railway has a clear indication that the development trend of railway transportation is the coexistence of internal-combustion engine locomotive and electrified locomotive. Meanwhile it will make strenuous efforts to develop the electrified railWay for the plain land, the main lines and the busy areas of transportation. It is obvious that the importance of electrified railway in railWay transpoftation will be enhanced more and more. It is going to be an important load to power systems all over China. But it is a disturbing load It gives serious harmonics pollution to power system if not properly maintained. This paper describes a new advanced method, fuzzy image recognition technique, to improve the adjustment during maintenance of the supply line so that good contact of the pantograph with the power line is ensured. This case also serves as an example to illustrate how the work on the demand side effectively improves the operation of the power system.

Joint UAV 3D deployment and sensor power allocation for energy-efficient and secure data collection

Unmanned aerial vehicles(UAVs) are advantageous for data collection in wireless sensor networks(WSNs) due to its low cost of use,flexible deployment,controllable mobility,etc. However,how to cope with the inherent issues of energy limitation and data security in the WSNs is challenging in such an application paradigm. To this end,based on the framework of physical layer security,an optimization problem for maximizing secrecy energy efficiency(EE) of data collection is formulated,which focuses on optimizing the UAV’s positions and the sensors’ transmit power. To overcome the difficulties in solving the optimization problem,the methods of fractional programming and successive convex approximation are then adopted to gradually transform the original problem into a series of tractable subproblems which are solved in an iterative manner. As shown in simulation results,by the joint designs in the spatial domain of UAV and the power domain of sensors,the proposed algorithm achieves a significant improvement of secrecy EE and rate.

故障关联矩阵下弹性配电网可靠性评估

配电网弹性是指系统受到干扰后恢复原有状态的能力,而自然灾害的频发要求配电网不仅在正常条件下能够可靠运行,而且还能够在极端灾害出现时保持必要能力。据此,提出一种基于故障关联矩阵(fault incidence matrix,FIM)的弹性配电网可靠性评价方法。通过建立FIM,使用简化的矩阵代数、布尔运算即可实现配电系统可靠性、弹性和供电能力的显式解析计算,避免了评估过程中故障枚举的重复性搜索工作,节省了计算时间,并且可适用于结构复杂的配电网,易于扩展。最后结果表明:采用文中方法的计算时间仅为约0.055 s,相较于故障扩散算法和分块算法分别减少87%和75%的时间。

集中式馈线自动化配电网供电可靠性评估

计及集中式馈线自动化的配电网可靠性评估尚存在较多研究空白,且多数研究仅计及故障停电的影响,在考虑预安排检修容量约束的情况下,计及负荷转供影响,结合馈线自动化的类型及运行逻辑,依据馈线自动化相关技术指标,对恢复供电过程中出现的负荷点进行详细分类,推导出不同类型负荷期望恢复供电时间和配电网供电可靠性指标计算公式。结合算例进行分析可知,不同终端配置下馈线系统平均停电持续时间SAIDI可减少0.95~1.08 h/(用户·a),说明了优化终端配置可有效提高配电网供电可靠性,证明了所提评估方法的准确性和实用性,并比较了不同终端配置对可靠性的影响。

基于多导体回路法的AT供电方式长回路电容计算方法研究

提出了一种基于多导体回路法以接触网和正馈线为传输导体的电气化铁路AT供电方式牵引网长回路电容计算方法。该方法以与电荷唯一对应的回路为基本单元,对复杂多导体传输线系统开展电场描述,实现了AT供电方式牵引网长回路电容的精确计算。

A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight;hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell,battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.

Design and analysis of control system using neural network for regulated DC power supply

Conventional control systems used for regulated power supplies,including the proportional integral and derivation(PID)controller,have some serious disadvantages.The PID controller has a delayed feedback associated with the control action and requires a lot of mathematical derivations.This paper presents a novel controlling system based on the artificial neural network(ANN),which can be used to regulate the output voltage of the DC power supply.Using MATLABTM,the designed control system was tested and analyzed with two types of back-propagation algorithms.This paper presents the results of the simulation that includes sum-squared error(SSE)and mean-squared error(MSE),and gives a detailed comparison of these values for the two algorithms.Hardware verification of the new system,using RS232 interface and Microsoft Visual Basic 6.0,was implemented,showing very good consistency with the simulation results.The proposed control system,compared to PID and other conventional controllers,requires less mathematical derivation in design and it is easier to implement.

考虑转供与重构协同的多端柔性互联配电网供电恢复策略

柔性互联装置(FID)实现配电网不同馈线之间的柔性互联,可实现故障后配电网的快速恢复供电。该文以含直流网络的四端柔性互联配电网为研究对象,提出基于FID和网络重构的多端柔性互联配电网两阶段供电恢复策略。首先,在分析FID运行模式工作原理的基础上,提出了故障快速转供的FID平滑控制结构和考虑开关同期并网控制虚拟同步发电机(VSG)控制策略,支撑故障后第一阶段FID的快速供电恢复;然后,通过建立和求解考虑联络开关和FID容量限制的全局优化模型得出FID与网络重构相结合的第二阶段供电恢复策略,更大限度地恢复失电负荷;最后,利用PSCAD/MTDC仿真软件搭建了一个58节点四端含直流网络的柔性配电系统进行仿真验证。结果表明,所述供电恢复策略不仅能实现部分负荷的不停电转供,还能够通过网络重构大幅提高负荷恢复水平。

含高比例分布式电源配电网分布式供电恢复方法

针对高比例分布式电源(DG)接入配电网,现有供电恢复方法未充分考虑DG故障穿越特性。文中提出了基于分布式控制的配电网多阶段供电恢复方法,以充分利用DG的电网支撑能力。分析了DG故障穿越特性及其电网支撑能力,并基于高比例DG接入后配电网不同运行方式,提出了负荷容量估算方法和DG分类处理策略。建立了分布式控制的供电恢复模型,并基于联络线路容量裕度指标提出多联络路径选择策略。最后,提出了适应高比例DG接入配电网的多阶段供电恢复方案。所提方法可以更好地发挥DG支撑作用,提高快速供电恢复能力。仿真算例验证了所提方法的有效性。

光储接入牵引供电系统应急供电方案下低频稳定性研究

“双碳”目标背景下,新能源较大规模接入牵引网可能成为铁路运输新趋势。为对意外失电的列车紧急牵引并打破铁路领域传统用能壁垒,实现铁路能源自给型低碳供电并与电网互为备用,各系统能量互联互通,首次提出一种应急供电方案灵活利用牵引网侧接入的光储装置牵引列车并对“光-储-车网”耦合系统的低频稳定性展开研究。首先,制定RPC双模式单相全桥逆变器的控制方法结合光储运行状态协调控制策略划分工作模态;然后,利用小信号及状态空间平均法建立光储、客车(CRH3型动车)以及投影到dq坐标系下铁路功率调节器直流侧阻抗模型;最后,利用所得“光-储-车网”3个子系统的导纳模型,引入一种适应多工况的无源判据,揭示控制器参数及多源对牵引供电系统电气稳定性的影响规律。研究结果表明:所提方案通过新能源及储能装置在昼夜多工况下均能长时持续稳定牵引列车,当新能源或电网供电出现意外二者可互补切换,故障条件下机车仍可受电稳定行走。此外,光储电压环比例增益对该系统阻抗匹配性稳定性有较强的电气敏感性,所建模型结合无源判据指导调参接入不同供电源补偿系统阻抗可治理部分失稳现象,该方案下储能系统具有良好的补偿特性。在Starsim半实物实验平台验证了“光-储-车网”耦合系统应急供电方案的可行性及稳定性研究的正确性。

考虑负荷供电连续性的孤岛配电网负荷恢复策略

上级输电网发生故障停运后,配电网可依靠分布式电源维持运行,当分布式电源出力波动难以平抑时,需要通过投切负荷来平抑波动,这会造成非重要负荷频繁投入或切出电网,产生大量单时段或双时段的短时供电场景,进一步降低了非重要负荷供电的可靠性。针对此问题提出一种考虑负荷供电连续性的配电网负荷恢复优化方法,从单个负荷角度出发,引入单负荷供电连续性指标构建目标函数,并计及潮流、网络拓扑、连通性等约束构建模型,使得非重要负荷也尽量连续供电,提高供电的连续可靠性。采用PG&E69节点配电系统作为算例进行验证,模型结果与传统恢复相比供电连续性显著提高。供电连续性参数的引入使得负荷恢复更加趋向于连续,大大减小了因为分布式电源波动而产生的短时供电问题。

基于需求功率预测的电动拖拉机能量管理策略

针对电动拖拉机在犁耕工况下电机需求电流波动比较大的特点,为了改善动力电池的输出电流过高或过低及电动拖拉机犁耕持续作业时间短的现象,利用超级电容高功率密度的特点,设计了一种锂电池+超级电容结构的双电源电动拖拉机,并建立了Amesim/Simulink联合仿真模型。以模型预测控制作为双电源系统的能量管理方法,基于长短期记忆神经网络建立电动拖拉机犁耕工况下的需求功率预测模型,使用动态规划算法求解最佳的锂电池输出电流。仿真结果表明:相比于模糊控制策略,基于模型预测控制策略有效降低了锂电池大电流放电的频率且峰值电流降低了40%,有效提高了锂电池的使用寿命;超级电容的SOC保持在比较高的范围内,且电动拖拉机在犁耕工况下的单位里程能量消耗降低了2.17%,实现了双电源电流分配最优,提高了电动拖拉机的动力性和经济性。

热网蓄热特性及其对机组调峰能力的影响研究

为了提高热电联产机组调峰能力,利用热网蓄热实现机组的“热电解耦”。建立了某350 MW热电联产机组及其热网系统的动态仿真模型,研究了热网及其热用户在蓄/放热阶段的动态特性及环境温度对机组调峰能力的影响规律。结果表明:热用户滞后时间随着热用户与换热首站的距离的增加而增加,同时也受自身热负荷的直接影响和其余热用户热负荷的间接影响;热网相对蓄/放热功率在改变抽汽质量流量后先迅速变化再缓慢变化;热用户温度近似呈线性变化,其变化速率随着抽汽质量流量变化幅度的增大而增大,且开始变化时间也随之提前;机组最大调峰能力随着环境温度降低而略有增加,环境温度从0℃下降至-15℃时,机组调峰能力从23.8 MW增加至29.7 MW;增加蓄热时长,提高蓄热温度,降低放热温度均有利于提高机组调峰能力。

基于区间证据理论的多源融合广域后备保护

针对传统保护方案在光伏接入系统时存在的可靠性不足问题,该文提出了一种基于区间证据理论的多源融合广域后备保护方案。首先,将光伏输出电流对保护的影响解耦分析,提出了保护方案的基本概率分配函数,将传统保护结果的0,1值转化为描述故障概率的区间值,定量考虑了光伏接入对配网保护的影响。其次,利用改进的区间证据理论对多种保护的判别结果进行融合,得到每条线路的综合故障概率区间,进而识别故障线路。该方法将光伏接入对保护判别的影响定量化,利用了多个保护综合判断,提高了广域后备保护的可靠性。同时,改进的区间证据理论消除了冲突证据的影响,在保护存在数据缺失及错误时仍能可靠识别故障线路。最后仿真验证了该文方法的可靠性。