Blockchain-empowered security and privacy protection technologies for smart grid

With the rapid development in society of the economy and of computational technologies, it is particularly important to build a secure, efficient and reliable smart grid architecture to provide users with high-quality electricity services. However, data collection and energy trading in public networks creates security and privacy challenges in smart grids. Blockchain technologies have the excellent characteristics of decentralization, immutability and traceability, which can resolve the security, integration and coordination problems faced by the traditional centralized networks for smart grids. The goal of this paper is to introduce and compare blockchain-based technologies in addressing the problems of privacy protection, identity authentication, data aggregation and electricity pricing for the data collection and power energy trading processes in smart grids. In addition, the existing challenges and future research directions of smart grids are discussed.     

基于双联盟链的智能电网数据共享模型

针对区块链的电网云服务器数据存在数据共享困难和隐私泄露风险,提出一种基于双联盟链的智能电网数据共享模型（DSDCB）。首先,基于星际文件系统（IPFS）在链下存储电力大数据,在链上存储IPFS文件指纹,并使用多重签名公证人将电力数据共享给其他联盟链;然后,在保证隐私不被泄露的情况下,使用代理重加密结合安全多方计算来进行单节点或多节点安全数据共享;最后,利用全同态加密算法在无需解密电力数据的情况下对密文数据进行合理整合。DSDCB的单节点跨链数据共享模型能抵抗51%攻击、女巫攻击、重放攻击和中间人攻击。经证明当恶意参与方少于k个、诚实参与方超过1个时,DSDCB的安全多方跨链数据共享模型能保证数据的安全性与隐私性。仿真对比表明,DSDCB的计算成本低于代理广播再加密（PBRE）和用于安全云存储的加密数据共享方案（CPBRE-DS）,比一轮通信可验证全同态秘密共享（FHNVSS）方案更具有可行性。     

智能电网中基于MQTT协议的ABAC访问控制方案

在智能电网环境中,电力运营商和消费者通过智能电表进行大量高精度的用电数据的实时监测,用户机密数据持续暴露于未经授权的访问,在这种传统通信模式下,智能电表对家庭用户能源消耗的细粒度测量造成了严重的隐私安全问题,而现有的静态访问控制方法并不满足智能电网环境基于上下文的动态访问特性。针对此问题,提出一种基于物联网通信协议（MQTT协议）的访问控制方案,通过在MQTT协议中对树型结构的主题列表设计基于ABAC访问控制模型的动态上下文授权策略,并在WSO2系统使用XACML策略语言实现了提出的访问控制方案。性能评估结果表明,该方案能在较低的通信开销内支持动态的访问控制,以解决智能电网中用户的用电信息未经授权而泄露的隐私安全问题。     

基于贝叶斯序贯博弈模型的智能电网信息物理安全分析

智能电网是利用信息技术优化从供应者到消费者的电力传输和配电网络.作为一种信息物理系统（Cyber-physical system，CPS），智能电网由物理设备和负责数据计算与通信的网络组成.智能电网的诸多安全问题会出现在通信网络和物理设备这两个层面，例如注入坏数据和收集客户隐私信息的网络攻击，攻击电网物理设备的物理攻击等.本文主要研究了智能电网的系统管理员（防护者）如何确定攻击者类型，从而选择最优防护策略的问题.提出了一种贝叶斯序贯博弈模型以确定攻击者的类型，根据序贯博弈树得到博弈双方的均衡策略.首先，对类型不确定的攻击者和防护者构建静态贝叶斯博弈模型，通过海萨尼转换将不完全信息博弈转换成完全信息博弈，得到贝叶斯纳什均衡解，进而确定攻击者的类型.其次，考虑攻击者和防护者之间的序贯博弈模型，它能够有效地帮助防护者进行决策分析.通过逆向归纳法分别对两种类型的攻击者和防护者之间的博弈树进行分析，得到博弈树的均衡路径，进而得到攻击者的最优攻击策略和防护者的最优防护策略.分析表明，贝叶斯序贯博弈模型能够使防护者确定攻击者的类型，并且选择最优防护策略，从而为涉及智能电网信息安全的相关研究提供参考.     

智能电网互补能源供用电实时定价算法研究

在智能电网背景下,针对化石能源短缺、峰时供电压力大的现状,提出了由光伏和化石燃料互补供电的方式,并建立了社会福利最大化用户侧微电网实时定价模型。该模型中,电力供应商通过制定实时电价来协调用户对两种类型能源所发电能的使用量,并设计了实时定价算法来求解模型。仿真结果表明,相比仅靠化石能源供电的大电网,互补供电方式能有效降低化石能源峰时供电量和价格,提升社会福利,这为以后智能电网的有效管理提供了参考。     

Integrated smart grid systems security threat model

The smart grid (SG) integrates the power grid and the Information and Communication Technology (ICT) with the aim of achieving more reliable and safe power transmission and distribution to the customers. Integrating the power grid with the ICT exposes the SG to systems security threats and vulnerabilities that could be compromised by malicious users and attackers. This paper presents a SG systems threats analysis and integrated SG Systems Security Threat Model (SSTM). The reference architecture of the SG, with its components and communication interfaces used to exchange the energy-related information, is integrated with the results of SG systems security threat analysis to produce a comprehensive, integrated SG SSTM. The SG SSTM in this paper helps better depict and understand the vulnerabilities exploited by attackers to compromise the components and communication links of the SG. The SG SSTM provides a reference of the systems security threats for industrial security practitioners, and can be used for design and implementation of SG systems security controls and countermeasures.     

支持大规模智能电网的数据存储方法

针对大规模智能电网中的监测数据具有海量性、实时性、动态性等特点,提出一种以数据为中心的支持大规模智能电网的数据存储方法:海量动态数据的分层扩展存储机制。首先,采用扩展哈希编码方法动态增加存储节点,避免突发、频发事件数据的丢失,增强系统的可用性;然后,采用多阈值级别方法将数据分散到多个存储节点上,避免出现存储热点问题,实现负载均衡。实验结果表明,分层扩展存储机制能够最大限度地满足海量数据的存储需求,获得较好的负载均衡,并且使总能耗最低,有效地延长了网络的生命周期。     

宽带PLC网络设计在智能电网通信中的应用

分析电力线载波通信(PLC)在电力通信中的应用及发展现状,重点介绍了智能电网的通信需求,并以远程抄表为切入点,针对传统窄带PLC抄表系统存在的问题,提出将宽带PLC家庭网络作为抄表终端网络的构想。为适应智能电网的通信需求,设计了基于家庭宽带PLC网络和Internet的远程电力抄表方案,并在实验网络中得以实现。     

物联网在智能电网中的应用

随着通信技术、网络技术、信息技术、数据库技术以及计算机技术的快速发展,物联网的产生是必然的,同时智能电网的发展是现代电网发展的主要方向,引领以信息化、自动化、互动化为基本特征的新一代电力工业革命。物联网应用在智能电网中将显著提高电力系统信息化水平、安全性与稳定性,改善现有电力系统基础设施的利用效率,满足节能环保的效果。介绍了物联网和智能电网的相关概念以及发展现状．并提出了物联网在智能电网中的具体应用。     

Supply chain intelligence for electricity markets: A smart grid perspective

Smart grid technologies are bringing innovations in electrical power industries, affecting all parts of the electricity supply chain, and leading to changes in market structure, business models and services. In this paper we introduce a model of business intelligence for a smart grid supply chain. The model is developed in order to provide electricity markets with the necessary data flows and information important for the decision making process. The proposed model offers a way to efficiently leverage the new metering architecture and the new capabilities of the grid to reap immediate business value from the huge amounts of disparate data in emerging smart grids. The model was evaluated for the Serbian electricity market in the electric power transmission company Public Enterprise “Elektromre?a Srbije”. The results show that business intelligence solutions can contribute to a more effective management of smart grids, in order to ensure that companies achieve sustainability in the increasingly competitive electricity markets, while still providing the high quality services to end users.     

The prediction of network efficiency in the smart grid

AMI is the core infrastructure of a smart grid and it is expected to be used for many industrial fields. The components of AMI generally include a smart meter, DCU, and MDMS. In such a system, the smart meter measures power consumption and DCU collects information from smart meters and send their data to MDMS. The MDMS is an end server to get information of the power usage and store its log and data. Since there are a lot of devices such as smart meters and DCUs in AMI, it is important to maintain the suitable number of them. In particular, it is necessary to calculate the proper number of DCUs for efficient management of AMI. In this paper, we suggest a way to predict the proper number of DCUs and this proposed method is useful to predict the total performance of heterogeneous AMI. The simulation results show that AMI is greatly influenced by the difference of performance between DCUs in the heterogeneous AMI.     

A fine-grained privacy protection data aggregation scheme for outsourcing smart grid

Compared with the traditional power grid, smart grid involves many advanced technologies and applications. However, due to the rapid development of various network technologies, smart grid is facing the challenges of balancing privacy, security, efficiency, and functionality. In the proposed scheme, we design a privacy protection scheme for outsourcing smart grid aided by fog computing, which supports fine-grained privacy-protected data aggregation based on user characteristics. The fog server matches the encrypted characteristics in the received message with the encrypted aggregation rules issued by the service provider. Therefore, the service provider can get more fine-grained analysis data based on user characteristics. Different from the existing outsourcing smart grid schemes, the proposed scheme can achieve real-time pricing on the premise of protecting user privacy and achieving system fault tolerance. Finally, experiment analyses demonstrate that the proposed scheme has less computation overhead and lower transmission delay than existing schemes.     

An adaptive agent-based system for deregulated smart grids

The power grid is undergoing a major change due mainly to the increased penetration of renewables and novel digital instruments in the hands of the end users that help to monitor and shift their loads. Such transformation is only possible with the coupling of an information and communication technology infrastructure to the existing power distribution grid. Given the scale and the interoperability requirements of such future system, service-oriented architectures (SOAs) are seen as one of the reference models and are considered already in many of the proposed standards for the smart grid (e.g., IEC-62325 and OASIS eMIX). Beyond the technical issues of what the service-oriented architectures of the smart grid will look like, there is a pressing question about what the added value for the end user could be. Clearly, the operators need to guarantee availability and security of supply, but why should the end users care? In this paper, we explore a scenario in which the end users can both consume and produce small quantities of energy and can trade these quantities in an open and deregulated market. For the trading, they delegate software agents that can fully interoperate and interact with one another thus taking advantage of the SOA. In particular, the agents have strategies, inspired from game theory, to take advantage of a service-oriented smart grid market and give profit to their delegators, while implicitly helping balancing the power grid. The proposal is implemented with simulated agents and interaction with existing Web services. To show the advantage of the agent with strategies, we compare our approach with the “base” agent one by means of simulations, highlighting the advantages of the proposal.     

Scheduling for electricity cost in a smart grid

We study an offline scheduling problem arising in demand response management in a smart grid. Consumers send in power requests with a flexible set of timeslots during which their requests can be served. For example, a consumer may request the dishwasher to operate for 1 h during the periods 8am to 11am or 2pm to 4pm. The grid controller, upon receiving power requests, schedules each request within the specified duration. The electricity cost is measured by a convex function of the load in each timeslot. The objective of the problem is to schedule all requests with the minimum total electricity cost. As a first attempt, we consider a special case in which the power requirement and the duration a for which a request needs service are both unit-size. For this problem, we present a polynomial time offline algorithm that gives an optimal solution and shows that the time complexity can be further improved if the given set of timeslots forms a contiguous interval.     

High-performance simulation of nation-sized smart grids

This paper develops a large scale simulation approach for smart grids with a fine temporal resolution. This permits a detailed simulation of every single smart grid participant facilitating real-time estimates on a realistic scale about load distribution, demand and supply. This is especially interesting when considering the sustainability and efficiency of renewable energy generation. The smart grid model is based on a multi-agent system. Each agent is modelled by an optimisation problem which minimises its costs to meet a prescribed demand. In order to bestow some flexibility to each agent, it can generate energy, by e.g. solar panels, or store energy. All agents participate in a cooperative bargaining game to compute their respective optimal solution. By doing so, the energy prices are dynamically adapted to the agents’ solutions so that an energy market is formed. This bargaining game is designed that a unique Nash equilibrium exists. The computations to obtain the equilibrium point are performed in parallel. To this end, a synchronisation scheme is derived to ensure convergence of the proposed parallel bargaining algorithm. The smart grid structure and capacity limitations are also taken into account. The solutions of the bargaining game are compliant with the smart grid’s capacities by solving a modified network flow problem and forcing the bargaining solution within the capacity limitations in an iterative procedure. The correctness of the presented parallel algorithm is validated in tests along with a parallel performance evaluation. As a proof of concept of the practical applicability of this approach, a smart grid with over 30 million private households and multiple energy types is simulated.     

基于B／／s模式的智能用电服务系统设计与开发

针对智能电网下智能终端的应用,结合现有量测方法和计算机网络技术,提出了一种基于B／S模式的智能用电服务系统的实现方案。该系统以智能电表的应用为硬件基础,通过网络协议编程构建用电自动测量网络,并实现对用户用电数据的实时采集。软件则以2LAMP（Linux＋Apache＋MySQL＋PHP）为开发平台,综合利用AJAX（异步JavaScript和xML,AsynchronousJavaScriptandXML）以及实时数据库技术实现系统的整体设计。该用电智能服务系统以浏览器为用户终端,可以为用户提供综合耗电统计、在线用电付费、智能用电决策以及实时信息交流等便捷而多样化的服务入口,从而为实现用户智能用电提供有力支撑。     

A hierarchical optimization model for energy data flow in smart grid power systems

Environmental concerns and high prices of fossil fuels increase the feasibility of using renewable energy sources in smart grid. Smart grid technologies are currently being developed to provide efficient and clean power systems. Communication in smart grid allows different components to collaborate and exchange information. Traditionally, the utility company uses a central management unit to schedule energy generation, distribution, and consumption. Using centralized management in a very large scale smart grid forms a single point of failure and leads to serious scalability issues in terms of information delivery and processing. In this paper, a three-level hierarchical optimization approach is proposed to solve scalability, computational overhead, and minimize daily electricity cost through maximizing the used percentage of renewable energy. At level one, a single home or a group of homes are combined to form an optimized power entity (OPE) that satisfies its load demand from its own renewable energy sources (RESs). At level two, a group of OPEs satisfies energy requirements of all OPEs within the group. At level three, excess in renewable energy from different groups along with the energy from the grid is used to fulfill unsatisfied demands and the remaining energy are sent to storage devices.     

A privacy-preserving aggregation scheme based on immunological negative surveys for smart meters

The smart meter is a basic device of the smart grid, which improves the efficiency of the power grid and brings a lot of convenience for the industry and people’s daily life. However, real-time power consumption data contain some sensitive information, and could disclose the privacy of users. As an immunological technique, the negative survey is proposed to preserve the privacy of static data. In this paper, firstly, we demonstrate that traditional negative survey might disclose the privacy of users when it is used to collect time-series data. Secondly, we propose an improved negative survey method for collecting the time-series data. Thirdly, for the first time, we apply the negative survey to preserving the privacy of the power consumption data aggregated from smart meters. Theoretical analysis and experimental results demonstrate that the method proposed in this paper could aggregate the power consumption data while preserving the privacy of users. Compared with existing techniques, our method is simple and efficient, and does not need a trusted third party. Moreover, it could tolerate the failure of some users and resist differential attack.     

Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.