Intelligent Energy Utilization Analysis Using IUA-SMD Model Based Optimization Technique for Smart Metering Data

Smart metering has gained considerable attention as a research focus due to its reliability and energy-efficient nature compared to traditional electromechanical metering systems. Existing methods primarily focus on data management,rather than emphasizing efficiency. Accurate prediction of electricity consumption is crucial for enabling intelligent grid operations,including resource planning and demandsupply balancing. Smart metering solutions offer users the benefits of effectively interpreting their energy utilization and optimizing costs. Motivated by this,this paper presents an Intelligent Energy Utilization Analysis using Smart Metering Data(IUA-SMD)model to determine energy consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing,feature extraction,and classification,with parameter optimization. We employ the extreme learning machine(ELM)based classification approach within the IUA-SMD model to derive optimal energy utilization labels. Additionally,we apply the shell game optimization(SGO)algorithm to enhance the classification efficiency of the ELM by optimizing its parameters. The effectiveness of the IUA-SMD model is evaluated using an extensive dataset of smart metering data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving a maximum accuracy of65.917% and a minimum MSE of0.096. These results highlight the potential of the IUA-SMD model for enabling efficient energy utilization through intelligent analysis of smart metering data.

Design of Real-time Electricity Prices and Wireless Communication Smart Meter

Under the background of smart grid’s real-time electricity prices theory, a real-time electricity prices and wireless communication smart meter was designed. The metering chip collects power consumption information. The real-time clock chip records current time. The communication between smart meter and system master station is achieved by the wireless communication module. The “freescale” micro controller unit displays power consumption information on screen. And the meter feedbacks the power consumption information to the system master station with time-scale and real-time electricity prices. It results that the information exchange between users and suppers can be realized by the smart meter. It fully reflects the demanding for communication of smart grid.

A Prepaid Smart Metering Scheme Based on WiMAX Prepaid Accounting Model

Prepaid energy meters have been widely adopted by utilities in different countries across the world as an innovative solution to the problem of affordability and consumption management. However, the present smart card based systems have some inherent problems like added cost, low availability and lack of security. In the future Smart Grid paradigm, use of smart meters can completely overhaul these prepaid systems by introducing centralized accounting, monitoring and credit-control functions using state-of-the-art telecommunication technologies like WiMAX. In this paper we pro-pose a prepaid smart metering scheme for Smart Grid application based on centralized authentication and charging using the WiMAX prepaid accounting model. We then discuss its specific application to Demand Response and Roam-ing of Electrical Vehicles.

Technologies Behind the Smart Grid and Internet of Things: A System Survey

Electric smart grids enable a bidirectional flow of electricity and information among power system assets.For proper monitoring and con-trolling of power quality,reliability,scalability and flexibility,there is a need for an environmentally friendly system that is transparent,sustainable,cost-saving,energy-efficient,agile and secure.This paper provides an overview of the emerging technologies behind smart grids and the internet of things.The dependent variables are identified by analyzing the electricity consumption patterns for optimal utilization and planning preventive maintenance of their legacy assets like power distribution transformers with real-time parameters to ensure an uninterrupted and reliable power supply.In addition,the paper sorts out challenges in the traditional or legacy electricity grid,power generation,transmission,distribution,and revenue management challenges such as reduc-ing aggregate technical and commercial loss by reforming the existing manual or semi-automatic techniques to fully smart or automatic systems.This article represents a concise review of research works in creating components of the smart grid like smart metering infrastructure for postpaid as well as in prepaid mode,internal structure comparison of advanced metering methods in present scenarios,and communication systems.

Clustering residential electricity load curve via community detection in network

Performing analytics on the load curve(LC)of customers is the foundation for demand response which requires a better understanding of customers'consumption pattern(CP)by analyzing the load curve.However,the performances of previous widely-used LC clustering methods are poor in two folds:larger number of clusters,huge variances within a cluster(a CP is extracted from a cluster),bringing huge difficulty to understand the electricity consumption pattern of customers.In this paper,to improve the performance of LC clustering,a clustering framework incorporated with community detection is proposed.The framework includes three parts:network construction,community detection,and CP extraction.According to the cluster validity index(CVI),the integrated approach outperforms the previous state-of-the-art method with the same amount of clusters.And the approach needs fewer clusters to achieve the same performance measured by CVI.

Smart Meters and Under-Frequency Load Shedding

In some countries, there exists a risk of power deficit in the EPS （electrical power system）. This is a very serious problem and there are various solutions to deal with it. A power deficit in the EPS leads to frequency decrease in the power system. A dedicated automation to load shedding is used to maintain proper EPS operation. For some time, it has applied a mechanism called demand-side response, which in case of an emergency situation allows for a ＂more civilized＂ rationing of electricity to customers, with their consent. Such programs require that the utilities pay the customers for their agreement. The author proposes a new solution, intermediate between strict ALS （acting relieving automation） and demand-side response programs, where the companies have to send information about the price of energy or control signals to households.

对有关电能计量若干问题的思考

文中基于论证和较全面分析,就不同场景下电能计量所关注的截然不同的问题、更好利用大数据去构建电能表检验新方法、动态电能计量研究面临新挑战、关注超谐波电能计量、不宜将电能计量装置与电能表简单划等号,以及测量准确度不同于测量精度等六个问题,阐述了作者的观点和认识,旨在对开展相关研究,以及更清楚理解相关测量方法及概念等起到促进作用。

Power ＂Smart Pricing＂ with and without Smart Meters

Over the past several years, the Taiwan Power Company has launched two smart pricing programs to assess the demand response of residential customers： the TOU （time-of-use） rate scheme and the DRI （demand reduction incentive） scheme. This paper discusses these two programs and evaluates their respective performances. We develop an efficient approach based on marginal cost pricing to redesign the TOU rate scheme. In our finding, the TOU price levels could be revised to encourage more customers to participate by enlarging the price gap. Moreover, the DRI scheme can be further improved in order to reach an efficient win-win solution among customers, the utility and society. This can be achieved via a careful design of incentive tariff discounts to take account of the time-of-use or location-specific features of the power supply/demand condition.

基于稳健回归和卷积神经网络的中压窃电类型检测方法

目前传统的窃电检测方法只能识别用户是否存在窃电,而无法针对各类型窃电用户进行快速准确稽查。针对中压用户具有用电量大、用电较为规律的特点,该文提出一种基于稳健回归和卷积神经网络的中压配电线路窃电类型检测方法。首先,考虑到受通信延迟中断等因素影响存在非正常数据的情况,采用稳健回归算法减小其影响,提高回归分析精度;其次,将回归所得的各用户修正系数及误差项作为用户窃电特征,输入卷积神经网络模型进行训练,以完成窃电类型识别;最后,通过仿真和实测数据进行该文方法的验证。结果表明,在不同扰动条件下,该文方法能准确识别不同类型窃电行为,能够更好地辅助现场排查,缩小排查范围,提高查实率。

高干热现场环境下智能电能表可靠性验证方法

智能电能表通用技术规范要求电能表可靠寿命不低于16年,如何验证智能电能表可靠性不仅是行业亟需解决的现实问题,也是学术界面临的难点问题。文章在Weibull分布场合下给出了针对可靠寿命、平均寿命和失效率三项指标的可靠性验证抽样特性函数。结合高干热环境的加速效应,借助加速因子构建基于加速试验的电能表抽样特性函数,进而针对智能电能表的工程背景确定二参数抽样方案。在实验验证与分析中给出了高干热环境下智能电能表可靠性验证方案,在不同使用方风险、可接受的故障数条件下计算了试验样本容量与试验时间的组合,给出了表格和绘图,方便工程应用。对电力行业量测设备在高干热环境下开展可靠性验证具有示范作用。

基于碳化硅电源的双芯智能电能表的可靠性测试研究

基于碳化硅电源的双芯智能电能表是新技术在工程领域特别是电力行业的重要尝试。针对其缺少可靠性检测标准的问题,文中根据现有智能电能表运行环境,同时结合碳化硅开关电源和双芯智能电能表特点,通过对电能表各项应力分析,提出了其可靠性检测方案及相应具体方法。提出的检测方案对于确定基于碳化硅开关电源的双芯智能电能表整机的可靠性指标具有十分重要的指导意义,从而实现提升智能电网技术水平,保障电网安全稳定运行的目的。

基于voting集成的智能电能表故障多分类方法

为提升智能电能表故障准确分类能力,助力维护人员迅速排除故障,提出基于投票法voting集成的智能电能表故障多分类方法。针对实际智能电能表故障数据进行编码预处理,基于皮尔逊系数法筛选智能电能表故障分类关键影响因素,结合合成少数类过采样技术(synthetic minority oversampling technique, SMOTE)算法解决数据类别不平衡问题,由此建立模型所需数据集,再通过投票法进行模型融合,结合粒子群PSO(particle swarm optimization)确定各基模型的权重,据此构建基于极限梯度提升树(extreme gradient boosting trees, XGBT)、K近邻(k-nearest neighbor, KNN)和朴素贝叶斯(naive bayes, NB)模型的智能电能表故障多分类方法。实测实验结果表明:所提出方法能有效实现智能电能表的故障快速准确分类,与现有方法相比,在智能电能表的故障分类精确率、召回率及F1-Score均有明显提升。

基于混合威布尔模型的智能电能表可靠性评价方法

针对当前智能电能表故障类型多样、可靠性评价单一的问题,提出基于混合威布尔模型的可靠性评价方法。论文基于智能电能表各单元串联关系和故障事件进行故障类型分类,利用最小二乘法推算各单元故障类型的尺度与形状参数,结合中位秩与平均秩次计算智能电能表累计失效概率提高模型准确度,并通过熵权法计算各故障类型对整表可靠度影响的权重系数,据此建立基于混合威布尔模型的智能电能表可靠性评价方法。实例结果表明,提出的方法在各类故障类型下均能准确得到智能电能表可靠度评估,并能准确获得智能电能表单元模块的可靠度,与现有方法相比,文中方法不需大量先验知识,且实现简单、准确度更高。

智能电能表数据安全隐患多层次分析与系统设计

智能电能表数据在智能电网中占有重要地位,传统智能电能表数据安全问题较为严重。为提高智能电能表数据安全等级,提出一种安全隐患多层次分析与系统设计方案。所设计系统包含功能有:用户获取用电信息,自主识别用电高峰;采用安全文件传输协议(SFTP)将用电数据从智能电能表传递至电力企业服务器,提高数据传输安全性;系统增加加密技术,通过磁盘加密确保用户数据的完整性和机密性,通过传输层安全(TLS)/加密套接字协议层(SSL)来保护用户与Web门户之间的通信。结果表明所设计智能电能表数据系统与同类系统相比,安全等级得到提高。

基于防盗算法的多功能智能电力计量系统

针对市场上传统数字电表的局限性,提出一种多功能智能电力计量系统。该系统通过集成物联网,实现智能电表的实时监控、波形谐波消除、防盗检测和负荷预测等功能。采用傅里叶分析对谐波进行分解,并使用电感器将失真降低30%,以满足IEEE 519标准。采用防盗算法,通过比较总用电量和单个电表用电量来识别异常情况。采用长短期记忆(LSTM)神经网络进行下一天的负荷预测,平均绝对百分误差为7.56%。实验结果表明,该系统在增强供电质量、安全性、实时监控以及合理的短期预测方面都较好地满足了市场的需求。

计及电力数据安全的智能合约上链方法及防篡改技术研究

随着“大云物移智链”等数字化技术在能源电力领域迅猛发展,大量新兴技术快速地在电网业务系统中进行创新应用,导致用电信息采集系统中数据交互更加频繁,从而出现数据经过流转后发生缺失、损坏等问题,进而导致业务数据公信力下降,且流转过程不清晰不透明,难以进行数据追溯溯源。针对用电信息采集系统数据可信度低、溯源难等问题,分析了区块链技术在用电信息采集系统应用情况,设计了区块链-用电信息采集系统三元结构模型,提出了一种采用区块链-用电信息采集系统三元结构的基于改进模型的实用型哈希算法的结构防篡改加密算法。仿真结果表明,区块链-用电信息采集系统三元结构的防篡改加密算法可提升数据质量进而提升业务数据公信力,同时通过该结构增强了数据的溯源能力,极大提升了用电信息采集系统数据在交互和使用过程的安全性。

单相智能物联电能表计量精度一致性评价方法研究

单相智能物联电能表是“泛在电力物联网”建设的重要载体,电能计量作为电能表最基本的功能,其精度一致性尤为重要。文中以某款主流单相智能物联电能表为例,通过对设计方案的分析,建立了基于Simscape的计量单元电路仿真分析模型,根据蒙特卡洛思想提出一种单相智能物联电能表计量精度一致性的评价方法,并提出了一种考虑元器件参数容差的计量精度一致性优化思路。结果表明,通过提升关键原器件参数的精度水平,可以使批次单相智能物联电能表的计量精度一致性有所改善。

智能物联电能表扩展功能模组设计

在能源转型和数字化革命的大背景之下,仅具备传统计量、收费、通信功能的智能电能表,已经无法支撑能源互联网快速发展带来的迫切需求。文中设计了一款具备硬件扩展功能的智能物联电能表,通过采用多芯、模组化的理念,设计各类模组的标准化接口,为扩展功能模组提供电源、通信接口以及原始采样数据,可满足电力用户多样化的应用需求。以需要开展电能质量分析的应用场景为例,设计了智能物联电能表用电能质量监测模组,并通过试验验证了扩展功能模组的功能及数据监测的准确性。

基于线损等效的视在功率和功率因数计算方法研究

分析了三相严重不平衡条件下现有功率因数的计算结果,指出了现有计算方法在反映实际线路利用率情况存在的不足。基于线路功率损耗等效原理,提出了一种能够准确反映实际线路利用率的功率因数和视在功率计算新方法。给出了现有智能电能表实现等效功率因数和视在功率计算的升级方案,同时以高准确度智能电能表作为测试平台,与现有功率因数进行三相非正弦不平衡试验条件下的对比测试。数据分析表明,与现有功率因数和视在功率相比,所提出的功率因数和视在功率新方法能够如实反映实际线路利用率情况,能够为功率因数的改善提供合理依据。

电能表退化模型建立与步进应力试验设计

目前智能电能表可靠性试验面临样本需求大、试验时间漫长等问题。本文分析了电能表敏感应力并建立电能表温湿度应力加速退化模型,设计预实验,得到了电能表在高温高湿环境下的工作极限,并据此设计电能表步进应力试验方案,确定了试验电能表数量、应力施加时间和步长,有效减少了样本量与试验时间,为后续电能表寿命预测和可靠性评估奠定基础。