阳光供热公司收费系统的设计与实现

本供热收费系统基于C／S模式开发,前台采用Microsoft公司的VB6．0作为界面开发工具,后台数据库采用SQL Server2008。本文按照软件工程的方法对系统的设计与实现进行了重点阐述。系统具有严密的多用户访问、海量数据存储、内置安全性等功能。通过编程测试,该系统能够稳定可靠地运行,具有一定的使用和推广价值。     

Electron cryo-microscopy of biological specimens on conductive titanium-silicon metal glass films

Thin films of the metal glass Ti88Si12 were produced by evaporation and characterized by AFM and conductivity measurements. Thin Ti88Si12 support films for electron microscopy were prepared by coating standard EM grids with evaporated films floated off mica, and characterized by electron imaging and electron diffraction. At room temperature, the specific resistance of a thin TiSi film was 10(6) times lower than that of an amorphous carbon film. At 77K, the specific resistance of TiSi films decreased, whereas that of carbon became immeasurably high. The effective scattering cross-section of TiSi and amorphous carbon for 120 kV electrons is roughly equal, but TiSi films for routine use can be approximately 10 times thinner due to their high mechanical strength, so that they would contribute less background noise to the image. Electron diffraction of purple membrane on a TiSi substrate confirmed that the support film was amorphous, and indicated that the high-resolution order of the biological sample was preserved. Electron micrographs of TiSi films tilted by 45 degrees relative to the electron beam recorded at approximately 4 K indicated that the incidence of beam-induced movements was reduced by 50% compared to amorphous carbon film under the same conditions. The success rate of recording high-resolution images of purple membranes on TiSi films was close to 100%. We conclude that TiSi support films are ideal for high-resolution electron cryo-microscopy (cryo-EM) of biological specimens, as they reduce beam-induced movement significantly, due to their high electrical conductivity at low temperature and their favorable mechanical properties.     

考虑EV充放电意愿的园区综合能源系统双层优化调度

随着电动汽车的普及度越来越高,工业园区的电动汽车用户日益增多,其充放电行为对园区综合能源系统规划和运行带来极大挑战。本文提出了考虑电动汽车充放电意愿的园区综合能源系统双层优化调度。首先基于动态实时电价、电池荷电量、电池损耗补偿、额外参与激励等因素建立充放电意愿模型,在此基础上得到改进的电动汽车充放电模型;然后,以园区综合能源系统总成本最小和电动汽车充电费用最小为目标建立双层优化调度模型,通过KKT条件将内层模型转化为外层模型的约束条件,从而快速稳定的实现单层模型的求解;最后,进行仿真求解,设置3种不同场景,对比了所提模型与一般充放电意愿模型,验证了文中所提引入EV充放电意愿模型的园区综合能源系统双层优化调度的有效性和可行性,具有一定的经济效益。     

基于“损耗-时间”最优的超级电容器充电策略

提出一种基于充电损耗与时间综合目标函数的超级电容器最优充电策略,根据预先提取的电容器“阻-流”特性在线确定不同运行条件下的最优充电电流。对Maxwell 2.7 V/10 F超级电容器单体进行测试,以验证所提策略的可行性。在此基础上,以1 kV/6.7 kW·h的超级电容器为例,通过MATLAB仿真定量分析了充电模式、荷电状态区间以及电容器老化对最优充电性能的影响。研究结果表明：所提策略可在超级电容器不同充电模式、荷电状态区间及老化状态下有效提升系统充电效能。     

基于空充暂态电流的线路保护CT极性校验方法

线路保护电流互感器(current transformer, CT)二次采样回路接线正确是保护正确动作的前提。针对线路投运启动过程中保护CT极性校验困难的问题,首先分析了在有限负荷和无负荷下利用线路稳态电流进行极性校验的边界限制条件。进而针对不满足限制条件下无负荷极性校验困难的问题,提出了一种基于空充暂态电流的线路保护CT极性校验方法。该方法先利用幅值较大的本端暂态电流对三相CT相对极性进行初判,再通过线路本端暂态电流和测量电压基于线路结构计算对端暂态电流来实现本端保护CT极性错误相识别,CT极性正确时对端计算电流理论上为零,CT极性错误时会呈现较大的幅值。该方法有效解决了传统极性校验方法在负荷不足时无法校验的问题。仿真和录波验证了该方法的有效性,并已纳入工程应用方案。     

Genetic algorithm-based partial charging schedule of rechargeable sensor networks

The use of rechargeable sensors is a promising solution for wireless sensor networks. On this type of network, mobile charging vehicles (MC) are used for charging sensors using wireless energy transfer (WET) technology. In on-demand charging, a sensor transmits a charging request to the service station, and the MC visits the sensor to transfer energy. The key disadvantages of utilizing MC-based WET are its high energy expenditure rate due to mobility, long service time, and slow charging rate. Because of these reasons, sensors deplete their energy and become dead before the MC reaches the requesting nodes to recharge. We have adapted a genetic algorithm-based partial charging scheme to serve the charging requests. Our objective is to improve the survival ratio of the network. Using comprehensive simulations, we analyze the performance of our proposed method and compare it to two other existing approaches. The simulation results demonstrate that our proposed algorithm improves the survival ratio by up to 20 % by developing a dynamic energy threshold function for transmitting charging requests from the sensors and a partial charging schedule using a genetic algorithm.     

基于时空耦合特性的充电站运行状态预测

提出一种基于时空耦合特性和深度学习模型的充电站运行状态预测方法。首先,基于充电站历史运行数据和所在区域的交通通行速度数据集,利用k-means聚类方法将充电站划分为不同类型,分析充电站运行状态在时间上的特性;建立单个充电站的"偏移量-交通-时间"三维矩阵模型,深度挖掘充电站运行状态与周边交通状况在时间和空间上的耦合相关性。其次,将充电站状态与交通状况的时间滞后相关特性进行空间重构,利用卷积神经网络进行特征提取,通过长短期记忆网络进行时间序列预测,构建基于Keras深度学习框架的充电站运行状态多步预测模型。最后,以20个充电站的真实运行数据进行验证,并与多种预测算法进行对比,结果表明,所提方法具有较高的预测精度。     

Power supply to electric vehicle charging stations in India:Justification of a framework for a dynamic and adaptive electricity tariff policy

Given the steady growth in the use of electric vehicles in India, and the need to locate charging stations in various places to fulfill the corresponding demand, this paper focuses on an applicable Electricity Tariff Policy Framework in the context of power supply to Electric Vehicle Charging Stations(EVCSs). The framework is conceptualized by a theoretical foundation, an operational/functional foundation, and a transactional foundation. The theoretical foundation incorporates justice risk across the Energy Lifecycle stages by classifying the relevant international, regional, and national issues within the legal layers of Energy Law while examining the core ideas of the 'Energy Trilemma'. The paper identifies two basic dimensions, (a) the target sets of end-users, and (b) EVCSs settings and the applicable tariff schemes, as the foundation of the framework. The operational/functional foundation consists of techno-economic and social criteria, and the transactional foundation involves the consideration of different target sets of end-users. The proposed framework will benefit policymakers in general and those, especially in India. Adaptation and use of the framework in other countries should consider their basic economic, geographic and political structures.     

基于CNN和LSTM混合网络的电动汽车充电桩运行状态预测方法

随着电动汽车的大规模发展,公共充电桩运行数量和充电量逐年增长。然而,充电桩运行始终存在故障频发、运维难度大和维修成本高等问题,并且传统故障检测方法效率低下。因此提出了一种基于卷积神经网络(CNN)和长短期记忆(LSTM)网络的混合网络电动汽车充电桩运行状态预测方法,可以实现对电动汽车充电桩运行状况的综合评估。在特征数据输入阶段,对充电桩运行状态的关键指标进行分析,通过CNN提取运行状态影响因素的特征量,再利用LSTM判断和预测充电桩运行状态,从而实现对充电桩潜在故障的预警。试验结果表明,该方法预测准确率高、实用性强,能较准确地反映和预测充电桩的运作状态,可实际用于充电桩故障预测与运维检修。     

考虑车辆充电调度机制的电动公交车充电站规划

针对电动公交车充电站的最佳充电容量难以确定及其充电效率低的问题,提出了一种在站址既定情况下考虑车辆充电调度机制的电动公交车充电站优化规划方法。首先,根据电动公交车的发车状态模拟电动公交车日常运行中的电能消耗,生成电动公交车的总运行负荷时序曲线;然后,基于生成的运行负荷时序曲线,构建充电需求度指标,制定电动公交车的充电调度机制;最后,在满足电动公交车充电需求的同时兼顾充电站精细化规划的要求,建立以充电能力最强、投资运行成本最小、光伏能源综合利用指标最大为优化目标的充电站多目标优化规划模型,并采用小生境多目标粒子群优化算法对该模型进行求解,以确定电动公交车充电站的充电桩数量以及光伏发电系统和配电变压器的容量。工程实例分析结果验证了所提方法的正确性和有效性。