一种费用敏感型家电能量优化动态调度算法

本文提出了一种应用于家庭能量管理系统（Home Energy Management System,简称HEMS）中的能量优化动态调度算法。该算法在满足用户满意度的情况下,最大可能的节省用户用电费用。本文提出的费用敏感家庭能量动态管理（expense-aware Home Energy Dynamic Management, eHEDM）算法,选择家庭中耗能较大的四种电器,综合考虑用户用电的满意度和用电费用节省,以及家庭中总能量消耗的限制来调度家用电器。仿真结果验证了本文提出的eHEDM算法可以在满足用户满意度的条件下,节省较多的用电费用。     

一种基于实时电价的HEMS家电最优调度方法

提出了一种应用于家庭能量管理系统(HEMS)的基于实时电价的家电最优调度模型。该模型采用线性整数规划方法建模,分别以用电费用最省、用电费用和满意度兼顾、二氧化碳排放最少为优化目标,以用户指定的运行时间要求以及电力公司的需求响应为约束条件。该模型将家庭中可以进行调度的可中断运行电器和不可中断运行电器,以及不可调度而必须运行的电器统一考虑,同时考虑使用家庭光伏(photovoltaic,PV)发电系统并允许剩余电力上网出售。提出的调度模型不仅考虑了家庭用电的各种实际情况,而且考虑了将来电网中可再生新能源的使用以及需求响应等新技术的应用,具有重要的实际意义。最后通过仿真实验验证了提出方法的有效性。     

家庭能源管理系统(HEMS)的设计研究

随着新技术的快速发展,家庭区域网络(HAN)在电力消费领域的各个领域都发生了革命性的变化,如用电模式等。在强大的智能电网范例下,配备家庭能源管理系统(HEMS)的现代家庭对提高效率、节约能源使用、可靠性以及为分布式系统节约能源做出了重大贡献。本文的目的是对HEMS在家庭的应用进行设计。本文提出了一种设计方法,通过结合绿色建筑的概念,即兴设计住宅建筑,以减少居民在家中的能耗。HEM系统的概念不仅是提出新的节能模式、电力管理或制造节能家电,除此以外,还需在消费者中建立意识,并激励他们积极参与与节能相关的活动。     

一种改进的HEMS家电最优调度方法

在现有的家庭能量管理系统(Home Energy Management System,简称HEMS)的基础上增加分布式储能模块组成新的HEMS,并在此基础上提出了一种改进的基于0-1线性整数规划方法的家电最优调度模型。通过此调度模型,用户可以根据各自需求分别实现用电费用最省、用电费用最省同时兼顾满意度,或者二氧化碳排放最小的目标。该调度模型无论是在目标函数还是在约束条件上都采用线性化表示的方法,在使用极短的调度时间的同时能够保证调度结果是最优结果。最后通过仿真实验验证了提出方法的有效性以及验证了所提方法能够很好的应对电力公司的削峰填谷要求,具有重要的实际应用价值。实验结果表明,所提方法能够比以往相关研究取得更好地节约费用、减少二氧化碳排放的效果。     

基于分时电价和多目标优化的家庭电能管理系统的设计与实现

现如今，分时电价的盛行改变了原来的用电模式，不仅要保证用电费用降低，更要保证用户用电的舒适度。因此提出了基于分时电价和多目标优化的家庭电能管理系统。首先，将常用的家用设备按照家用设备的用电特性进行了分类。然后，家庭电能管理系统优化调度模型的建立以家庭用电成本的优化、用户舒适度的提升和碳排放量的追踪为目标。最后，对家庭电能管理系统模型使用改进的粒子群算法进行优化验证。通过使用Matlab进行仿真实验，验证该方法在降低用电成本、提高用户舒适度和追踪碳排放量方面有显著的优化效果。     

家庭智能用电管理系统用电优化算法研究

为降低居民用户用电费用和提高用电效率,考虑分时电价价格激励的作用,对家庭智能用电进行了研究。构建了由智能家用电器、传统家用电器、电动汽车及其充放电设备、智能开关/插座、智能交互终端、智能手机、分布式能源和智能电表等组成的家庭智能用电管理系统。以一般家庭常用家用电器为优化对象,以用户用电费用最低为优化目标,采用遗传算法,根据用户设定的各家用电器的工作时间范围,提出了基于分时电价的家庭智能用电管理系统智能用电优化算法。以兼顾用户用电费用和负荷消耗功率均匀分布为优化目标,设定功率阈值,引入惩罚机制,提出了基于分时电价的改进智能用电优化算法。仿真结果表明,所提出的智能用电优化算法可为用户最大限度节省用电费用;所提出的改进智能用电优化算法可为用户适当节省用电费用,并可避免引入新的用电高峰。因此,该智能用电优化算法能实现既定优化目标,是有效、可行的。用户可根据实际需要确定优化目标,选用相应算法。     

ZigBee协议的物联网研究及应用

0前言随着如今移动互联网络和智能可穿戴设备的不断应用和发展,不断降低传感器的能耗、不断提高芯片的连通性和兼容性就显得极为迫切。为此,ZigBee联盟推出新协议920IP具有现实意义,它不仅可以提高家庭能源管理系统(HEMS)的智能性,还有利于促进ZigBee协议物联网在科技研发、国防保卫、医疗保健、工业生产、零售行业、物流行业、现代化农业等行业的应用,实现全世界网络化。1 ZigBee协议的要求     

基于CS5460芯片的智能家居用电监控装置设计

随着近年智能电网与阶梯电价理念的提出,科学用电已经越来越受到居民的重视。电力系统中实时监控、采集电力参数是实现智能家居的重要环节,快速准确地采集用电系统中各用电设备的电参数(电压,电流,功率,功率因数等)是实现智能家居不可或缺的重要因素。提出了一种基于SOC系统的用电监控装置,可对用户用电量进行实时监控,同时,利用wifi技术传入网络平台上,该平台上可以将所有电器的耗电数据收集到服务器中,进行监控。而后,通过wifi无线网络控制电器,从而达到节省家庭电费的效果,同时,网络平台也可以将数据传给电力系统中,对数据进行分析,得到各个用户家庭用电情况,采取相应措施,最终达到节能效果。     

基于实时电价的家庭能量管理系统最优调度研究

家庭能量管理系统作为智能电网在居民家庭中的智能体现,需建立在家庭安全用电的基础上。家庭中的电气故障多为线路过载故障。在对家庭智能电器的优化运行中,将线路负载率作为约束条件,可保障家庭的用电安全。在实时电价环境下,提出了一种考虑家庭线路负载率约束的家庭能量调度策略,分别建立了以用电费用最小和碳排放最小为目标的优化模型,针对建立的0-1整数规划模型,将遗传算法进行了改进,以求得家庭最优用电方式。通过仿真验证,比较用户在不同用电模式下的线路负载率、用电费用和碳排放量,验证了该策略可为家庭用电提供安全可靠的最优用电方式。     

基于SOPC的家庭智能用电控制器

智能电网鼓励用户与电网双向互动,针对当前家庭用电设备智能化程度无法满足智能用电要求的问题,基于SOPC技术设计一款适用于家庭用电的智能控制器。以FPGA为硬件核心实现,包含电能计量、无线通信、继电器控制等多个功能电路,并完成了相关应用程序设计和开发,使控制器具有采集负荷用电信息、与用户手机终端交互、控制电器电源通断的能力。经实验验证,本文设计电路功能全面、结构简单,能实现对家用电器的智能化改造的目标,可获取家庭内负荷用电信息,促进科学、合理用电和节能。     

Implementing home energy management system with UPnP and mobile applications

The power grid is undergoing a revolution and modernization through integrating information and communication technologies with the power system and also installing new electricity system technologies. Distributed controls in a certain self-reliant power-service area are critical means to modernize the power system to be the Smart Grid. Since the self-reliant area is assumed to perform physical and/or expert-engineered operations that should be integrated, monitored and controlled by a computational cyber system, the area is one area where the cyber and physical systems interact together, and home in the Smart Grid is one example for the area. In this paper, we propose a home energy management system (HEMS) to realize full automation combining computational and physical systems in a home area, which excludes operator-based control and management. The proposed system is designed to be built on the Universal Plug-and-Play architecture, and it can be accessed remotely over the Internet via mobile applications that work in Apple iPhone. Based on the design, we actually implemented the HEMS and constructed an empirical testbed that consists of networked personal computers, home appliances, and portable wireless devices. With the empirical testbed, we verified the monitoring and controlling functions of the HEMS. Additionally we carried out an extensive simulation study with the measured data of power consumption and the collected data of power price in order to see the effectiveness of the proposed HEMS. We also discuss about some limitations and challenges that we have encountered in designing and implementing the HEMS.     

Distributed artificial bee colony approach for connected appliances in smart home energy management system

In this study, we propose a computational intelligence model for the Internet of Things applications by applying the concept of swarm intelligence (SI) into connected devices. Particularly, decentralized management of smart home energy management system (HEMS) is taken into account in which connected appliances, by sharing information with each other, make the individual decisions for optimizing electricity prices of smart HEMS. Specifically, the study includes two main issues: (a) We propose a framework for decentralized management in smart HEMS; and (b) artificial bee colony (ABC) algorithm, a typical algorithm of SI techniques, has been applied for connected appliances in terms of communication and collaboration with each other to optimize the performance of the energy management system. Moreover, regarding the implementation, we develop and simulate a connected environment of smart home systems to evaluate the proposed approach. The simulation indicates the promising results in terms of optimizing the load balancing problem comparing with the conventional approach of the decentralized management system in smart home applications.     

Privacy-aware electricity scheduling for home energy management system

In the context of smart grid, home energy management system (HEMS) needs to collect the fine-grained energy consumption data through smart meters. However, the fine-grained data contain the electricity consumption patterns of consumers, which can induce serious privacy issues. In order to protect the electric privacy of consumers, a privacy-aware electricity scheduling strategy for HEMS is proposed in this paper. Firstly, the basic scheduling model of HEMS is presented, and the basic scheduling objective is to minimize the electricity payment while satisfy the daily power demands of consumers. On this basis, a privacy-aware optimal scheduling model adopting rechargeable batteries is established, and the introduction of preference factor enables consumers to make a tradeoff between the total operation cost and privacy security. The electric privacy protection performance is measured by coefficient of determination and the number of features. Besides, the operation cost of batteries is also considered in the modeling process, and the influence battery capacity has on the performance of privacy protection is discussed. Simulation results show that the proposed method is effective and has strong practical application value.     

A novel approach for generic home emergency management and remote monitoring

This paper presents a novel home emergency management system (HEMS) for managing home emergency situations. The proposed solution is a generic and based on normalized technologies. First, we have identified a set of requirements that a robust HEMS should satisfy (interoperability, security, mobility, etc). Then, we have opted for an extended finite‐state machine to detect and manage emergency situations. We also adopted WebRTC to enable communication in an interoperable manner. For securing our HEMS, we have used HTTPS, password, contextual role–based access control, and we have finally installed all the public servers into a protected area. The result obtained from the test‐bed demonstrates that the proposed HEMS fills all the listed requirements. Furthermore, it gives very interesting results in terms of round‐trip delay time and scalability.     

一种智能家电控制系统设计与实现

针对目前家用电器数量与种类多,人机接口单一,智能化程度低,控制复杂等问题,设计了一种基于动作传感器和SimpliciTI网络协议的智能家电控制系统[1]。该系统在基本不改变原有家电硬件的基础上,把所有的家电纳入一个统一的无线网络,并且通过按键与人体动作[2]对家电进行统一的控制,使人与家电的交流变得更加高效,简单和自然。经实验验证,该系统具有较高的稳定性与可靠性,有较高的实用价值。     

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.     

Low computational cost technique for predictive management of thermal comfort in non-residential buildings

In France, non-residential buildings account for a significant part of energy consumption. A large part of this consumption is due to HVAC (Heating, Ventilation and Air-Conditioning) systems, which are in most cases poorly handled. The present work deals with an efficient approach allowing energy consumption to be minimized while still ensuring thermal comfort. We propose a predictive control strategy for existing zoned HVAC systems and consider the PMV (Predicted Mean Vote) index as a thermal comfort indicator. In order to test this strategy, we modelled a non-residential building located in Perpignan (south of France) using the EnergyPlus software. The twofold aim is to limit the times during which the HVAC sub-systems are turned on and to ensure a satisfactory thermal comfort when people are working in the considered building. This predictive approach, computationally tractable, allows thermal comfort requirements to be met without wasting energy.     

基于PMV和视觉舒适度的家庭能耗管理

以PMV和韦伯-费昔勒定律为基础,建立热舒适度和视觉舒适度的模型,得到各种场景下热舒适度和视觉舒适度的公式和曲线,并以此为依据,用于家庭温控和光控系统能耗管理系统研究,设计了基于PMV控制和视觉舒适度控制的家居节能系统。结果表明,这种以家庭成员的热感觉和视觉舒适为目标的控制系统,兼具节约能源和有益健康的两重收益。     

智能家电远程控制的研究

研制了智能家电的手机控制系统,能通过手机短消息控制家庭内的各种家电的开关.在控制系统中植入手机SIM卡,并在PC机中设置可接收手机号码以及短消息的形式.在SIM卡收到消息后,将消息串行送入单片机中,单片机内根据收到消息通过红外传输将电开关控制指令传送至另一单片机,该单片机控制着家电继电器开关,通过继电器的控制实现家电的断开与闭合.