面向智能电网双向互动信息服务的通信组网方案设计

以建设智能电网对于智能用电的需求为出发点,研究了智能用电的关键技术以及智能用电新型服务,针对不同的用户设计了面向智能电网的双向互动信息服务系统以及通信组网方案。采用先进的双向互动通信技术、智能交互终端技术以及智能表计技术,为电网和用户之间的互动提供可靠的信息通道和网络支撑,并对应用层信息互动平台提出建设方案,构建了电网...     

Achieving privacy-preserving big data aggregation with fault tolerance in smart grid

In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching strategy. However, these big energy data in terms of volume, velocity and variety raise concern over consumers’ privacy. For instance, in order to optimize energy utilization and support demand response, numerous smart meters are installed at a consumer's home to collect energy consumption data at a fine granularity, but these fine-grained data may contain information on the appliances and thus the consumer's behaviors at home. In this paper, we propose a privacy-preserving data aggregation scheme based on secret sharing with fault tolerance in a smart grid, which ensures that the control center obtains the integrated data without compromising privacy. Meanwhile, we also consider fault tolerance and resistance to differential attack during the data aggregation. Finally, we perform a security analysis and performance evaluation of our scheme in comparison with the other similar schemes. The analysis shows that our scheme can meet the security requirement, and it also shows better performance than other popular methods.     

Bargaining‐Based Smart Grid Pricing Model for Demand Side Management Scheduling

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day‐ahead pricing strategy. Based on the Rubinstein–Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak‐to‐average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.     

Analysis of the Stakeholder Engagement in the Deployment of Renewables and Smart Grid Technologies

The implementation of higher shares of renewables in a global energy mix has to be accompanied by simultaneous deployment of enabling smart grid technologies (SGTs). This combination will inevitably lead to a revolutionary change in a conventional energy system, particularly, the shifting role of consumers to prosumers. But resistance may arise from such a dramatic shift, since it is associated with high uncertainty in conjunction with increasing responsibilities of all stakeholders, the urgent need of effective control, and the development of a process. To ensure the positive influence, coherent actions of all players, and appropriate treatment of the spots of resistance, the analysis of the interplay between key stakeholders has been done. The paper introduces the framework for stakeholders' analysis, applies it on the European Union (EU) example, and provides recommendations to reduce the resistance of SGTs deployment.     

微电网技术应用分析

目前,微电网技术已成为智能化电网建设中最关键的技术之一.该技术在我国的发展受智能电网能源需求的影响深远,且与分布式发电技术密切相连.文章对微电网关键性技术及其应用进行了研究.     

Adaptive algorithm for optimal real‐time pricing in cognitive radio enabled smart grid network

Integration of multiple communication technologies in a smart grid (SG) enables employing cognitive radio (CR) technology for improving reliability and security with low latency by adaptively and effectively allocating spectral resources. The versatile features of the CR enable the smart meter to select either the unlicensed or the licensed band for transmitting data to the utility company, thus reducing communication outage. Demand response management is regarded as the control unit of the SG that balances the load by regulating the real‐time price that benefits both the utility company and consumers. In this study, joint allocation of the transmission power to the smart meter and consumer's demand is formulated as a two stage multi‐armed bandit game in which the players select their optimal strategies noncooperatively without having any prior information about the media. Furthermore, based on historical rewards of the player, a real‐time pricing adaptation method is proposed. The latter is validated through numerical results.     

Density Based Fuzzy C Means Clustering to prolong Network Lifetime in Smart Grids

Wireless sensor networks (WSN's) are preferred for industrial applications due to progressive increase of sensor electronics. One such application is deployment of WSN's in smart grids. Smart Grid integrates information and communication techniques with electricity network. Smart grids utilize sophisticated control and monitoring devices for improving the efficiency of the grid. For energy efficient, low cost monitoring and control in smart grid WSN's is treated as a promising technology. Advanced Metering Infrastructure (AMI) is the key technology in the distribution networks of Smart Grid. The AMI is composed of various sensors for metering purpose. The meter data is also useful for the distribution operators to manage the demand response. The network involves smart meters, smart electric gas and water meters along with digital network management appliances for optimizing the electric network with real time data management. The smart sensors are limited in terms of battery, operational power and memory. These sensors communicate with the base station in restricted range. The communication between smart grid nodes and base station (sink) is multi-hop in nature. The communication takes place within limited range of communication so the security concerns that are involved in the network are to be handled by the routing protocols. So as to make the bidirectional communication efficient between the smart sensors and utility an effective routing scheme is required for these energy limited devices to handle the heavy network traffic in smart grids. Here energy efficient routing for WSN's in NAN networks to attain load balancing is proposed through density based Fuzzy C means clustering (DFCM). The obtained simulation results show that DFCM can provide a satisfactory performance for enhancing the network life span.

     

基于动态优先级的智能家居户间能源调度算法

针对智能家居中单用户能源调度所忽略的电网侧稳定性的要求,以及多用户能源调度中用户舒适度考虑不足的问题,通过分析家电设备运行特性以及用户需求,对用户用电时间以及家居设备类型进行了分类,并提出家居设备二维动态优先级,在此基础上设计了智能家居户间能源调度算法,旨在保障用户舒适度,降低户内电费支出的同时,保障电网侧的稳定性。最后通过仿真,验证了算法的可行性与有效性。     

Towards Privacy Protection in Smart Grid

The smart grid is an electronically controlled electrical grid that connects power generation, transmission, distribution, and consumers using information communication technologies. One of the key characteristics of the smart grid is its support for bi-directional information flow between the consumer of electricity and the utility provider. This two-way interaction allows electricity to be generated in real-time based on consumers’ demands and power requests. As a result, consumer privacy becomes an important concern when collecting energy usage data with the deployment and adoption of smart grid technologies. To protect such sensitive information it is imperative that privacy protection mechanisms be used to protect the privacy of smart grid users. We present an analysis of recently proposed smart grid privacy solutions and identify their strengths and weaknesses in terms of their implementation complexity, efficiency, robustness, and simplicity.     

The Crowd Energy Concept

After the Fukushima disaster, European politicians began to reassess the energy strategy for their countries. The focus is now on renewable energy sources and as a result on decentralization. The decentralized generation, storage, and of course the consumption of energy is the central point. Now with the new developments under the roof of energy turnaround the way back from the centralized architecture of our energy system to a more decentralized one is predetermined. Decentralization implies the change in the role of today's consumers. They become energy prosumers. This is the basis for the crowd energy concept. In this position paper the crowd energy concept is introduced and necessary research fields are identified.     

探讨配电路线施工管理技术

在世界能源发展的大趋势下,全球各国都把发展智能电网提上了重要日程,而配电环节直接与客户相连,在整个电力生产过程中占有不容忽视的地位,所以基于配电自动化的智能配电网络的概念应运而生.本文就配电线路施工管理技术进行探究,提出相应的改进措施,促进我国电力行业的快速发展.     

基于异构数据的电力短期负荷大数据预测方案

随着多种可再生能源电力的接入,电力系统正在向更智能、更灵活、交互性更高的系统过渡。负荷预测,特别是针对单个电力客户的短期负荷预测在未来电网规划和运行中发挥着越来越重要的作用。提出了一个基于异构数据的电力短期负荷大数据预测方案,该方案收集来自智能电表和天气预报的数据,预处理后将其加载到非关系型数据库中进行存储并做进一步的异构数据处理;设计并实现了一个长短期记忆递归神经网络模型,用于确定负荷分布并预测未来24 h的住宅小区用电量;最后利用一个住宅小区的智能电表数据集对提出的短期负荷预测框架进行了测试,并使用均方根误差和平均绝对百分比误差两个指标,对比了预测模型与两种经典算法的性能,验证了所提模型的有效性。     

A Business Model Guideline of Electricity Utility Systems Based on Blockchain Technology in Thailand: A Case Study of Consumers,Prosumers and SMEs

This paper presents a business model guideline of electricity utility systems based on blockchain technology in Thailand: a case study of consumers, prosumers and SMEs. Because the resource management of electricity utility systems in Thailand presently are based on enhanced single buyer or a centralized system. However, a free-trade energy market is likely to open or occur in the near future. Thus, a preparation of changing or adapting such a free-trade energy market using disruptive technology is an important point to study the aforementioned disruptive technology (i.e. blockchain technology). The future business of the free-trade energy market is related to the policy of the government (Thailand 4.0). It will support technology development and innovation to encourage the potential and readiness and to compete for foreign countries. In this scoping study, the business model guideline of electricity trading with peer to peer (P2P) is proposed to utilize the case study of consumers and prosumers/SMEs in Thailand based on a decentralized system. The P2P trading is directly the buying and selling of electricity between both consumers and prosumers. It is not a passed intermediary; otherwise, an intermediate process can be cut by this trading in order to save and reduce electricity costs. Preliminary expected impacts of cost structure analysis are summarized in terms of comparisons between the existing electricity trading and the blockchain technology. The results of such preliminary expected impacts show that costs to consumers, prosumers and SMEs obtained from the use of blockchain technology are possibly lower than those of EGAT, PEA, and MEA in the future. In addition, the business model guideline is completely discussed by theory in disruptive innovation.

     

An Overview to the Concept of Smart Coupling and Battery Management for Grid Connected Photovoltaic Battery System

The paper gives an overview on the need for smart coupling for battery management in grid integrated renewable energy system (RES). Grid integrated photovoltaic (PV) battery system, as being popular and extensively used has been discussed in the paper. Smart coupling refers to intelligent grid integration such that it can foresee local network conditions and issue battery power flow management strategy accordingly to shave the peak PV and peak load. Therefore, a need for predictive energy management arises for smart integration to the grid and supervision of the power flow in accordance to the grid conditions. This is also a running project at the Institute of Energy Systems (INES), Offenburg University of Applied Science, Germany since January, 2015. The paper should provide insights to the motivation, need and gives an outlook to the features of desired predictive energy management system (PEMS).     

面向智慧能源的供需平衡数据可视化挖掘方法

为满足能源数据监测和综合分析领域的业务需要,提出面向智慧能源的供需平衡数据可视化挖掘方法。构造数据迁移与分类视图,确定每个供需平衡数据点位置坐标,并采用正交投影可视化技术将数据挖掘算法核心结构展示在视图中(支持用户对其进行相应调整);引入数据挖掘算法,提取数据可视化挖掘结果参数,实现面向智慧能源供需平衡数据的可视化挖掘。实验结果显示:智慧能源供需数据可视化挖掘结果综合评分数值范围为64.70~82.04分,充分说明该方法具备较好的可视化挖掘性能,可应用在多维典型用能场景中。     

新能源接入对继电保护及安自装置的影响浅析

随着我国时代发展和经济繁荣,电网的未来趋势已经走向智能电网,但同时世界的能源危机问题也越来越严峻,而风电、光伏等新型能源作为电源网络的重要组成部分,获得了大力开发和广泛应用.需要注意的是,新能源大规模的接入已经改变了我国传统电力系统运行过程产生的特征,对我国传统的继电保护及安自装置带来更高的要求标准和挑战.本文简单分析了"新能源接入对继电保护及安自装置的影响"有关内容.     

智能电网环境下的继电保护

随着我国经济与科学技术的迅速发展,现代化智能电网已经逐步取代传统电网,传统的继电保护技术已经无法满足智能电网继电保护发展的需求.因此为保障智能电网的运行环境,需采取继电保护的措施,改善电网的运行状态,维持安全、可靠的电网环境.因此本文从智能电网环境下的保护问题入手,分析智能电网环境下继电保护发展趋势,并提出针对性的建设策略.     

Enhancing energy-efficient sleep scheduling for Narrowband Internet of Things devices in coordinated 5G networks within smart environments

This research project takes on a crucial role in the quickly changing field of integrated 5G networks inside smart environments by concentrating on the creation of an extremely effective sleep scheduling system designed especially for Narrowband Internet of Things (NB-IoT) devices. This work introduces a unique method for precisely controlling the nodes' sleep schedules through the use of convolutional neural network (CNN) architecture, which optimizes both energy usage and operating patterns. The principal goal still stands to guarantee the extended lifetime of operation and dependability of NB-IoT devices in the larger framework of intelligent ecosystems driven by synchronized 5G networks. To achieve its objectives, the research explores a number of complex domains and employs cutting-edge technologies and techniques, such as CNN-based pattern recognition. This method's real-time component is essential since it allows for prompt modifications to sleep schedules in order to optimize energy savings. Further boosting the devices' effectiveness and flexibility is continuous contact with a central server, which guarantees that the devices are updated with the most recent data and instructions. Essentially, the main objective of this study is to greatly increase the energy economy and operational lifetime of NB-IoT devices, which will allow for stable and long-lasting IoT deployments in the context of 5G networks in intelligent settings. This advancement is not only a boon for businesses and industries leveraging IoT technology but also a substantial step toward building smarter, more energy-efficient, and resilient smart ecosystems that benefit society as a whole.     

基于5G的智慧社区应用探讨

随着新一轮科技革命和产业变革的深入,围绕社区全生活链服务需求,以人本化、生态化、数字化为价值导向的智慧社区将成为人类更加向往的居住地。智慧社区采用5G网络技术,以大数据、物联网、人工智能等主要技术手段为支撑,统筹各类服务资源,搭建智能运营管理平台,构建各种智慧应用场景,创建高品质社区生活。以长三角地区某城市智慧社区建设为例,分析了智慧社区建设需求,阐述了设计思路、建设内容与应用场景设计,并对智慧社区的发展提出了针对性建议。     

An Optimal Power Scheduling Method Applied in Home Energy Management System Based on Demand Response

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real‐time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost‐effective way possible. In our research, to avoid the high peak‐to‐average ratio (PAR) of power, we combine the real‐time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.