基于等效模型和多时间尺度扩展卡尔曼滤波的锂离子电池SOC预测

荷电状态(SOC)和最大可用电量估计是锂离子电池寿命预测中的两个最重要部分;然而与快速时变的SOC比较,最大可用电量的参数变化缓慢;文章提出了一个基于等效模型和多时间尺度的扩展卡尔曼滤波(EKF)预测算法对SOC和最大可用容量分别在不同时间尺度上进行估计,在宏观尺度上利用了SOC估计值作为观测量,更新最大可用电量;针对NCA/C卫星锂离子电池实验数据的仿真结果表明,提出的多时间尺度EKF预测算法与EKF联合估计算法相比,SOC和最大可用电量估计准确度更高,同时提高了计算效率。     

智能电网下考虑风险的供电企业购电优化模型

针对智能电网带给供电企业购电决策的影响,提出了一种考虑风险的购电优化决策方法。智能电网建设并开展运营,发电侧考虑接纳更多的可再生能源发电,用电侧智能用电设备的使用导致主动负荷的出现等,这一系列变化给智能电网环境下供电企业购电决策带来一定程度的风险。首先,考虑了智能电网下负荷与风电出力不确定性给供电企业经营带来的风险,采用风险元传递理论与多目标规划理论,建立智能电网购电优化模型。然后,提出采用约束多目标粒子群优化算法(CMOPSO)对模型进行求解思路;最后,算例说明该模型的可行性,研究成果为我国智能电网运营风险管理提供新方法、新思路。     

A Goal Programming Model for Rescheduling of Generation Power in Deregulated Markets

In deregulated electrical systems, production schedule for power plants is the result of an auction process. In the Spanish case, this schedule includes two main concepts: energy production (to be actually produced) and secondary reserve (to maintain available). The generation company faces the problem of converting energy schedule into a power schedule, respecting the reserve schedule as well as technical constraints, and trying to accomplish different goals: to minimise the production costs, to obtain smooth shapes for the power schedules and to optimise eventual compensation in schedules. A weighted goal mixed integer programming model with a real-size application to deal with this problem is presented.     

Testing new graphene oxide-coated glazing for papyrus manuscripts in museums: Part I

The display of papyrus and paper (as cellulosic materials) in the Egyptian museums is always critical due to the traditional placement of display of sensitive materials between two plates of glass, acrylic, or other types of glazing materials. The sensitivity of the glazing materials to abrasion, ultraviolet rays, dust adhesion, and high light reflectivity are considered concerning issues to conservators, curators, and visitors. In this paper, thin protective coatings of graphene oxide (GO) were synthesized by modified Hummers' method and deposited on selected museums' glazing materials (glass and acrylic) using spin coating. Multi-analytical techniques were employed to assess the applicability of GO-coated glazing including scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FTIR), microhardness testing, NIR VIS, and UV spectrophotometer and static potential measurements. The results showed that the glass glazing hardness was increased by ~10% due to the deposition of the GO coating. Moreover, according to glazing type, the reflectance values of the GO-coated glazing samples, compared with the uncoated samples, confirmed that the thin film of GO improved the UV rays blocking. As is evident in the GO-coated glass where approximately 27% of UV rays have been blocked, likewise, 19% of UV rays were blocked in GO-coated acrylic (TRU VUE). Considering VIS and NIR reflection spectra of GO-coated plexiglass, a higher reflectance is presented by 29%. Furthermore, the static potential measurements showed an energy decline in GO-coated glazing compared with the uncoated samples.     

周郇和《电学纲目》

本文根据新发现的资料,对首次将经典电磁学较为系统地介绍进我国的周郇及其译著《电学纲目》作了述评.     

Electricity,Heat, and Gas Load Forecasting Based on Deep Multitask Learning in Industrial-Park Integrated Energy System

Different energy systems are closely connected with each other in industrial-park integrated energy system (IES). The energy demand forecasting has important impact on IES dispatching and planning. This paper proposes an approach of short-term energy forecasting for electricity, heat, and gas by employing deep multitask learning whose structure is constructed by deep belief network (DBN) and multitask regression layer. The DBN can extract abstract and effective characteristics in an unsupervised fashion, and the multitask regression layer above the DBN is used for supervised prediction. Then, subject to condition of practical demand and model integrity, the whole energy forecasting model is introduced, including preprocessing, normalization, input properties, training stage, and evaluating indicator. Finally, the validity of the algorithm and the accuracy of the energy forecasts for an industrial-park IES system are verified through the simulations using actual operating data from load system. The positive results turn out that the deep multitask learning has great prospects for load forecast.     

低功率因数电功率表在使用中应注意的问题

通过分析电功率表的测量原理、接线方式和读数方法,详细介绍低功率因数电功率表在使用中应该注意的问题。     

输电装置的传输特性

输电装置在航空、航天、航海及精密仪器中获得了广泛地应用,籍以实现两个相对转动部件间的讯号传输。输电装置作为惯性平台中一个关键的部件,其性能、外形的指标可直接影响整个惯性系统的优劣。针对惯性平台所采用的输电装置,经过反复大量地试验研究,对其传输特性进行了全面分析,应用电接触学理论,提出了电刷材料与接触电阻之间的对应关系,并提出了一种全新的测试接触电阻的较为精密的方法。理论分析和实验结果表明,提出的方法是切实可行的,适用于惯性平台所采用的所有型号的输电装置。     

基于因素影响的电力消费预测研究

深入研究了国内生产总值、人口及电力价格指数等因素对电力消费的影响,建立了因素影响的电力消费预测模型,确定了算法,以新加坡电力消费及其影响因素的实际数据为背景进行了实证研究,说明了该方法的有效性。     

有功与无功功率最优实时定价新方法

本文给出了一种基于社会收益最大化的有功与无功功率最优实时定价新方法 .传统的研究仅仅考虑了电力系统运行成本最小这一目标 .本文则把有功运行成本、无功运行成本与消费者的收益结合起来 ,利用把消费者的反映表示为需求函数的逆形式的手段 ,使最大化电力市场参与者的社会收益目标变为可能 ,每条母线上的有功与无功功率定价结果也可相应求出 .