The user side of sustainability: Modeling behavior and energy usage in the home

Society is becoming increasingly aware of the impact that our lifestyle choices make on energy usage and the environment. As a result, research attention is being directed toward green technology, environmentally-friendly building designs, and smart grids. This paper looks at the user side of sustainability. In particular, it looks at energy consumption in everyday home environments to examine the relationship between behavioral patterns and energy consumption. It first demonstrates how data mining techniques may be used to find patterns and anomalies in smart home-based energy data. Next, it describes a method to correlate home-based activities with electricity usage. Finally, it describes how this information could inform users about their personal energy consumption and to support activities in a more energy-efficient manner. These approaches are validated by using real energy data collected in a set of smart home testbeds.     

基于数据分析的楼宇智能节电管理系统

城市中高层楼宇增加是城市内用电量上升的重要因素之一。使用计算机系统对建筑执行能耗量化管理从而控制降低建筑运营过程中所消耗的能量,降低建筑的运营成本,提高能源使用效率,已经成为用户最为关注的问题。已有的楼宇节电管理系统收集建筑内部的信息并通过启发式规则对楼宇的照明、动力、通风、空调、安防等系统进行协调控制及整合,以期达到节能的目的。这类型系统的缺点在于（1）大部分楼宇缺少专职的节电管理机构,没有相关的电能使用及管理的方法。在各个楼宇与电力公司之间还没有形成一个有效的信息共享链,内外信息共享能力差,存在信息孤岛现象（2）系统中的节电模型没有学习过程,不能根据建筑情况的变化,自动调整节电模式。面对这样的情况,该文提出一个基于数据分析的建筑楼宇智能节电系统,该系统（1）使用正态分布拟合用户用能习惯,分析得到用户能耗较高的关键设备,发现设备的耗能过高原因;（2）建立双向交换子系统实现楼宇与电力公司之间的信息交换,并根据电力公司生产计划及时调整楼宇用能策略。在天津动漫大厦实际运行结果显示,该文设计的智能节电系统可以有效的节省楼宇中的电力损耗。     

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.     

建筑中能耗拆分方法

提出能耗拆分的基本方法。现存的建筑配电系统支路中往往包含多种能耗设备,而计量装置只能统计某户或某层的总能耗量,通过能耗拆分能够计算出各类用电设备的能耗量,让各管理体系内的节能工作能够有的放矢,使节能工作建立在定量化的基础上,为节能运行管理、节能改造和各节能措施的节能效果后评估等工作提供数据支持。     

Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method

In the research domain of intelligent buildings and smart home, modeling and optimization of the thermal comfort and energy consumption are important issues. This paper presents a type-2 fuzzy method based data-driven strategy for the modeling and optimization of thermal comfort words and energy consumption. First, we propose a methodology to convert the interval survey data on thermal comfort words to the interval type-2 fuzzy sets (IT2 FSs) which can reflect the inter-personal and intra-personal uncertainties contained in the intervals. This data-driven strategy includes three steps: survey data collection and pre-processing, ambiguity-preserved conversion of the survey intervals to their representative type-1 fuzzy sets (T1 FSs), IT2 FS modeling. Then, using the IT2 FS models of thermal comfort words as antecedent parts, an evolving type-2 fuzzy model is constructed to reflect the online observed energy consumption data. Finally, a multiobjective optimization model is presented to recommend a reasonable temperature range that can give comfortable feeling while reducing energy consumption. The proposed method can be used to realize comfortable but energy-saving environment in smart home or intelligent buildings.     

PowerPedia: changing energy usage with the help of a community-based smartphone application

When it comes to conserving electricity, it is crucial for users to know how much energy is consumed by individual appliances. However, the technical feedback provided by existing energy consumption feedback systems in the form of dry numbers and intangible units is not appropriate for most users. To address this shortcoming, we developed PowerPedia, a system that provides behavior-influencing feedback over and above pure consumption values. By integrating a community platform—a Wikipedia for electrical appliances—PowerPedia enables users to identify and compare the consumption of their domestic appliances with that of others. It thus helps users to better understand their electricity consumption and take effective action to save electricity.     

基于工作流技术的用电信息采集系统设计与实现

智能电网建设要求下,用电信息采集系统适应全球电网技术的发展要求,为开展技术管理提供有效的基础性资料。从目前用电信息采集系统的工作模式来看,普遍存在着业务流程过于固化的问题,导致在需要业务逻辑变化时需要通过程序修改来实现变化需求,工作开发量与维护量较大。因此,基于工作流技术的用电信息采集系统可以对全过程进行管控,按照实现设计好的工作流逻辑进行执行,在工作效率上得到了显著提升,只需要通过适当地调整工作流程的方式来适应其变化情况,在运维成本方面得到节约。出于不同的专业应用系统建设与管理的要求,也需要对信息采集系统进行功能性分析,了解未来工作中的潜在需求。     

存在反向有功电量低压用户的研判方法研究

针对部分低压电力用户存在反向有功电量,影响电量计算,引起台区线损指标异常,造成供电企业经济损失的问题。本文基于用电信息采集系统中的用电量数据,提出了一种反向有功电量低压电力用户的研判方法。通过分析分布式光伏用户、电能表错误接线低压电力用户、含有电磁制动设备低压电力用户以及计量装置故障低压电力用户等四类用户存在反向有功电量时的用电量特性,分别建立对应的识别规则,实现对存在反向电量的低压用户类型的快速研判,进而有针对性地对电能表接线错误的低压用户以及计量装置故障的低压用户重点跟踪、监测,以便及时处理,减少供电企业的损失。经实例验证,该方法符合实际业务且有效可行,可显著提高工作效率,同时为电网公司节省人力、物力资源。     

A user-guided personalization methodology to facilitate new smart home occupancy

Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available. In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system’s design. Later, the user-guided transfer learning approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results.

     

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.     

An automatic energy saving strategy for a water dispenser based on user behavior

Nowadays, numerous public buildings provide water dispensers to supply drinking water which causes more energy consumption. A typical water dispenser periodically heats and cools the water to ensure that hot, warm, and cold water are always available for the user. However, this mechanism is inefficient because the users do not request hot and cool water continuously. Ideally, the boiling and cooling schedule should follow the demand pattern to save electricity consumption. When no demand, a water dispenser can enter a sleep mode.Therefore, this study presents an automatic energy-saving strategy for a water dispenser based on user behavior. The proposed system allows the water dispenser to automatically determine the appropriate time to heat, boil, and enter sleep mode based on user behavior. The proposed control strategy involves several steps. First, it collects historical data, analyzes water consumption behavior. The sensors installed in the water dispenser collect water consumption data. Second, this study applies Recurrent Neural Networks with Long-Short Term Memory to predict future water consumption. Finally, the proposed system utilizes the prediction result to determine heating, cooling, and sleep mode schedule.This study uses a water dispenser on a university campus as a prototype to test the proposed system. The effectiveness of the proposed system is measured by two factors, namely electricity consumption, and customer satisfaction. These two parameters are chosen because the proposed system should reduce electricity consumption while maintaining hot and cold water availability whenever needed. According to the simulation results, the proposed controlling strategy can reduce electricity consumption up to 28% monthly while maintaining a service level of 97%. This result shows that the proposed system is a good control system for water dispensers. By applying this controlling system, public buildings could reduce their energy bills without sacrificing their provision of drinking water.     

基于WSNs和电力载波的教室智能节能系统设计

为了解决无线通信方式在教室控制网络中易受干扰和教室电器能源浪费问题,提出了一种基于无线传感器网络(WSNs)和电力线载波通信技术相结合的智慧教室电器节能设计方案.在总结了智慧教室控制系统研究现状、主要技术难点和挑战的基础上,着重阐述了智慧教室的控制网络拓扑结构和工作流程,详细分析了电力载波智能收发器的内部结构.此外,还实现了一种基于智能照明控制算法的智慧教室控制系统的原型.实验结果表明,该系统能够降低数据包的丢失率,相比普通LED照明系统能耗节省至少40％,并且运行可靠.     

Dueling-DQN在空调节能控制中的应用

针对电信机房空调运行耗电量大,空调自动控制系统设计困难的问题,提出了一种规则约束和Dueling-DQN算法相结合的空调节能控制方法.该方法能根据不同机房环境自适应学习建模,在保证机房室内温度在规定范围的前提下,节省空调耗电量.同时针对实际机房应用场景,设计节能控制算法中的状态,动作和奖励函数,并采用深度强化学习算法Dueling-DQN提高模型表达能力和学习效率.在电信机房实际验证结果表明:该控制方法与空调默认设定参数运行相比节能18.3％,并可以很方便推广到不同环境场景的机房环境中,为电信机房节能减排提供解决方案.     

基于Zig Bee技术的智能调光开关设计

根据智能家居的发展方向和用户需求,设计了一种基于Zig Bee技术的智能调光开关系统。设计方案采用新一代SOC芯片CC2530作为系统的无线收发模块,使得模块具备成本低、功耗小、高可靠、自组网、超视距通信等能力。采用ARM7嵌入式处理器LPC2132作为系统的微控制器模块,简化设计提高可靠性,使得系统具备分布处理能力。通过检测市电的过零点,开启延时定时器,定时器超时后触发双向可控硅导通的时间点来达到调光的目的。结果表明:本设计能够使家居照明系统更具可控性,更节能,使得家居环境更加舒适。     

基于RFID技术的智能家庭用电信息系统构建

根据中国当前智能电网发展的趋势,为了有效掌控家庭用电信息,构建了一个基于射频身份识别(Radio Frequency Identification,RFID)技术的智能家庭用电信息系统。该系统硬件使用有源RFID标签及超高频读卡器;软件基于B/S架构,根据模块化原则,将系统划分为数据库服务层、逻辑处理层、用户表示层等三层结构。用户可通过浏览器远程实现对电器设备的自动化监控和电能计量管理等功能,系统则可自动把异常报警信息以各种通信方式报告给用户。     

智能电网中家域网安全数据汇聚与调度方法研究

智能电网中通信网络的安全是实施智能电网的一个重要环节。用户信息的隐私保护是智能电网安全服务的一个主要任务。智能电网中用户信息隐私保护主要围绕智能电表数据的机密性和匿名性展开。本文以家域网作为智能电网通信网络的一个基本数据汇聚与调度单元,提出了一种安全的网内数据汇聚与调度方法,从而保证了智能家居设备的用电信息的机密性和匿名性。采用NS-2对本文提出的网内方法进行了仿真研究。仿真结果表明,本文提出的网内数据汇聚与调度方法与传统方法相比具有较高的实用性。     

物联网技术在家用太阳能行业中的应用

随着物联网技术在太阳能领域的广泛应用以及智能家居的逐步推广,太阳能产品已经作为一种独立的系统融入智能家居系统。皇明太阳能推出的MeHoPad微排智慧家居集成解决方案是一种集控制、显示、记录等功能于一体的智能节能管理平台,可对家居中热水、灯光、窗帘、安防等系统进行智能管理,使用户在生活中的各种能耗排放达到微量。文中介绍YMeHoPad系统的硬件架构和应用特点。     

物联网智能家居系统的研究与设计

智能家居有广阔的应用前景.针对传统家居控制上的缺陷,采用B/S架构设计了智能家居管理系统,采用ZigBee无线网络实现对各类家居设备的信息采集和指令控制.用SQL Server 2005数据库管理系统与家庭网关,进行数据的传递与接收.通过Web浏览器,用户可以实现对智能家居系统的管理.     

Characterizing and Detecting Gas-Inefficient Patterns in Smart Contracts

Ethereum blockchain is a new internetware with tens of millions of smart contracts running on it.Different from general programs,smart contracts are decentralized,tamper-resistant and permanently running.Moreover,to avoid resource abuse,Ethereum charges users for deploying and invoking smart contracts according to the size of contract and the operations executed by contracts.It is necessary to optimize smart contracts to save money.However,since developers are not familiar with the operating environment of smart contracts(i.e.,Ethereum virtual machine)or do not pay attention to resource consumption during development,there are many optimization opportunities for smart contracts.To fill this gap,this paper defines six gas-inefficient patterns from more than 25,000 posts and proposes an optimization approach at the source code level to let users know clearly where the contract is optimized.To evaluate the prevalence and economic benefits of gas-inefficient patterns,this paper conducts an empirical study on more than 160,000 real smart contracts.The promising experimental results demonstrate that 52.75%of contracts contain at least one gas-inefficient pattern proposed in this paper.If these patterns are removed from the contract,at least 0.30 can be saved per contract.     

内存云架构的磁盘节能策略

内存云(RAMCloud)的出现改善了在线数据密集型(OLDI)应用的用户体验,但其能耗高于传统的云数据中心。针对该问题,提出一种适用于该架构的磁盘节能策略。首先,引入遗传算法中适应度函数和轮盘赌法,尽量选择更为节能的磁盘进行数据持久化备份;其次,设定合理的服务器内存缓冲区来延长磁盘的平均连续空闲时间,使得部分服务器磁盘在空闲时进入待机状态。仿真实验结果表明,在50台服务器的内存云系统中,该策略能有效节能约12.69%;而缓冲区大小的设定对于节能效果和数据可用性具有双重影响,需权衡考虑。