Smart Household Research Articles

Multifunctional Energy Storage and Conversion Devices

Multifunctional energy storage and conversion devices that incorporate novel features and functions in intelligent and interactive modes, represent a radical advance in consumer products, such as wearable electronics, healthcare devices, artificial intelligence, electric vehicles, smart household, and space satellites, etc. Here, smart energy devices are defined to be energy devices that are responsive to changes in configurational integrity, voltage, mechanical deformation, light, and temperature, called self-healability, electrochromism, shape memory, photodetection, and thermal responsivity. Advisable materials, device designs, and performances are crucial for the development of energy electronics endowed with these smart functions. Integrating these smart functions in energy storage and conversion devices gives rise to great challenges from the viewpoint of both understanding the fundamental mechanisms and practical implementation. Current state-of-art examples of these smart multifunctional energy devices, pertinent to materials, fabrication strategies, and performances, are highlighted. In addition, current challenges and potential solutions from materials synthesis to device performances are discussed. Finally, some important directions in this fast developing field are considered to further expand their application.

전기자동차 침투율을 고려한 피크 부하 저감용 스마트 기기의 적응적 제어

Electric utilities may face new threats with increase in electric vehicles (EVs) in the personal automobile market. The peak demand will increase which may stress the distribution network equipment. The focus of this paper is on an adaptive control of smart household appliances by using an intelligent load management system (ILMS). The main objectives are to accomplish consumer needs and prevent overloading of power grid. The stress from the network is released by limiting the peak demand of a house when it exceeds a certain point. In the proposed strategy, for each smart appliance, the customers will set its order/rank according to their own preferences and then system will control the household loads intelligently for consumer reliability. The load order can be changed at any time by the customer. The difference between the set and actual value for each load’s specific parameter will help the utility to estimate the acceptance of this intelligent load management system by the customers.

Optimal Household Appliances Scheduling Under Day-Ahead Pricing and Load-Shaping Demand Response Strategies

In this paper, a detailed home energy management system structure is developed to determine the optimal day-ahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets have been explicitly modeled, including thermostatically controllable (air conditioners and water heaters) and nonthermostatically controllable (washing machines and dishwashers) appliances, together with electric vehicles (EVs). Furthermore, an energy storage system (ESS) and distributed generation at the end-user premises are taken into account. Bidirectional energy flow is also considered through advanced options for EV and ESS operation. Finally, a realistic test-case is presented with a sufficiently reduced time granularity being thoroughly discussed to investigate the effectiveness of the model. Stringent simulation results are provided using data gathered from real appliances and real measurements.

Smart Household Environment Illumination Dimming and Control

This paper presents the design of a smart household environment illumination dimming-control. The control can be operated using either an Android App or a computer using either Wi-Fi or Zigbee to connect to a Database Management System (DBMS). The DBMS can synchronize with a central controller in order to achieve simple and convenient dimming-control of the user's home illumination. In this paper, a linear dimming scheme was adopted to reduce the light gleaming. In order to achieve suitable variations in the illumination environment, a highly-efficient three-color LED was used as the light source. This paper covers the designs of six environment illumination controls for users who can deliver the control states to the central controller and mobile phone. A 24 V DC power supply was designed in this system and can collocate with the DC/DC converter to form a power module suitable for general home use. The interface of the proposed environment illumination control is clear and simple; one can verify that the design presented in this paper possesses very high practicability from the experimental results.

Design and Realization of Smart Home Terminal Applications Based on IOT Technology

With the development of IoT technology, more and more smart household devices, such as sensors and smart mobile terminals, have appeared in our daily life. Users can remotely control almost all the devices in the smart home system and understand their information, thus effectively improving the user life quality. For background, this paper designs and develops two smart mobile terminal applications based on smart home technologies research: one is the smart remote control application based on infrared technology, which realizes remote controlling on infrared smart devices based on infrared transmission technology, WiFi and Socket technology; the other is remote control and monitor application based on PhoneGap, which realizes remote controlling and monitoring on the devices directly connected to the gateway based on PhoneGap, HTTP request and HTML5 cache technology. Research on the mobile applications in the smart home system and their realization laid a solid foundation for the future research and function expansion of smart home and even smart city system.

Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR

As the smart grid solutions enable active consumer participation, demand response (DR) strategies have drawn much interest in the literature recently, especially for residential areas. As a new type of consumer load in the electric power system, electric vehicles (EVs) also provide different opportunities, including the capability of utilizing EVs as a storage unit via vehicle-to-home (V2H) and vehicle-to-grid (V2G) options instead of peak power procurement from the grid. In this paper, as the main contribution to the literature, a collaborative evaluation of dynamic-pricing and peak power limiting-based DR strategies with a bi-directional utilization possibility for EV and energy storage system (ESS) is realized. A mixed-integer linear programming (MILP) framework-based modeling of a home energy management (HEM) structure is provided for this purpose. A distributed small-scale renewable energy generation system, the V2H and V2G capabilities of an EV together with two-way energy trading of ESS, and different DR strategies are all combined in a single HEM system for the first time in the literature. The impacts of different EV owner consumer preferences together with the availability of ESS and two-way energy trading capabilities on the reduction of total electricity prices are examined with case studies.

사물인터넷 보안 문제제기와 대안

Internet of Things(IoT) is electronic devices and household appliances use wireless sensor network in environment of high speed wireless network and LTE mobile service. The combination of the development of Internet and wireless network led to development of new forms of service such as electronic devices and household appliances can connect to the Internet through various sensors and online servers such as a Home Network. Even though Internet of Things is useful, there are problems in Internet of Things. In environment of Internet of Things, information leakage could happens by illegal eavesdropping and spoofing. Also illegal devices of wireless communication interference can cause interfere in Internet of things service, physical damage and denial of service by modulation of data and sensor. In this thesis, it will analyze security threats and security vulnerability in environment of mobile services and smart household appliances, then it will suggest plan. To solve security issues, it is important that IT and RFID sensor related companies realize importance of security environment rather than focus on making profit. It is important to develop the standardized security model that applies to the Internet of Things by security-related packages, standard certification system and strong encrypted authentication

Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving

Meeting time-varying peak demand poses a key challenge to the U.S. electricity system. Building-based electricity storage – to enable demand response (DR) without curtailing actual appliance usage – offers potential benefits of lower electricity production cost, higher grid reliability, and more flexibility to integrate renewables. DR tariffs are currently available in the U.S. but building-based storage is still underutilized due to insufficiently understood cost-effectiveness and dispatch strategies. Whether DR schemes can yield a profit for building operators (i.e., reduction in electricity bill that exceeds levelized storage cost) and which particular storage technology yields the highest profit is yet to be answered. This study aims to evaluate the economics of providing peak shaving DR under a realistic tariff (Con Edison, New York), using a range of storage technologies (conventional and advanced batteries, flywheel, magnetic storage, pumped hydro, compressed air, and capacitors). An agent-based stochastic model is used to randomly generate appliance-level demand profiles for an average U.S. household. We first introduce a levelized storage cost model which is based on a total-energy-throughput lifetime. We then develop a storage dispatch strategy which optimizes the storage capacity and the demand limit on the grid. We find that (i) several storage technologies provide profitable DR; (ii) annual profit from such DR can range from 1% to 39% of the household’s non-DR electricity bill; (iii) allowing occasional breaches of the intended demand limit increases profit; and (iv) a dispatch strategy that accounts for demand variations across seasons increases profit further. We expect that a more advanced dispatch strategy with embedded weather forecasting capability could yield even higher profit.

A new perspective for sizing of distributed generation and energy storage for smart households under demand response

As a recently increasing trend among different applications of smart grid vision, smart households as a new implementation area of demand response (DR) strategies have drawn more attention both in research and in engineering practice. On the other hand, optimum sizing of renewable energy based small scale hybrid systems is also a topic that is widely covered by the existing literature. In this study, the sizing of additional distributed generation (DG) and energy storage systems (ESSs) to be applied in smart households, that due to DR activities have a different daily demand profile compared with normal household profiles, is investigated. To the best knowledge of the authors this is the first attempt in the literature to investigate this issue, also including step-wise decreasing cost functions for DG and ESS, varying load and DG production profiles seasonally, and weekday–weekend horizons for a long-term analysis period. The study is conducted using a mixed-integer linear programming (MILP) framework for home energy management system (HEM) modeling and techno-economical sizing. Also, different sensitivity analyses considering the impacts of variation of economic inputs on the provided model are realized.

Design and Implementation of an Intelligent Home Control System

With the development of computer technology, networking and information technology, and the requirements for the continuous improvement of living, enjoying smart household life has become possible, and become the inevitable tendency. This paper introduces a kind of smart home control system which based on 32-bit embedded processor ARM platform and the ZigBee wireless network communication technology. This system was designed to aim at the ordinary residential district family user, which can realize the concentration supervisory control and management to the housing safe condition, and achieve the household electrical appliances' remote control.

Design of Smart Household Monitoring Platform Based on Internet of Things

In order to popularize the intelligent monitoring in households, this thesis is aimed to conduct researches on“Household Monitoring System based on the Internet of Things (IOT)”and starts with the design of this system. General technology concerning household video monitoring and home appliance controlling in computers, mobile phones, etc. is explored in this thesis and a household monitoring system based on IOT is set up. According to experiments, the household monitoring system has various functions such as operating once plugged, ad hoc network, various and interactive controlling methods and friendly serial ports.

Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households

With the increasing importance given to smart grid solutions in end-user premises, demand response (DR) strategies applied to smart households are important topics from both real time application and academic theoretic analysis perspectives, recently. In this study, a mixed-integer linear programming (MILP) framework based evaluation of such a smart household is provided. Electric vehicles (EVs) with bi-directional power flow capability via charging and V2H operating modes, energy storage systems (ESSs) with peak clipping and valley filling opportunity and a small scale distributed generation (DG) unit enabling energy sell back to grid are all considered in the evaluated smart household structure. Different case studies including also different DR strategies based on dynamic pricing and peak power limiting are conducted to evaluate the technical and economic impacts of ESS and DG units. Besides, shiftable loads such as washing machine and dishwasher are also considered in Home Energy Management (HEM) system structure for the effective operation of the household. Moreover, a further sensitivity analysis is realized in order to discuss the impact of ESS and DG sizing on daily cost of smart household operation considering further pros and cons.

Single Phase PV Grid-Connected in Smart Household Energy System with Anticipation on Fault Conditions

This paper proposes an algorithm of Smart household energy systems to anticipate fault conditions in power system grid. Single phase PV grid-connected in smart household energy system is a smart system that determines electrical supply conditions to the load in residential electrical system. The smart system is consisted of two voltage source, conventional electricity system from national electricity provider as preferred source and photovoltaic as the alternative source. In smart system, fault conditions can be anticipated by selecting the appropriate voltage sources to supply the load. The condition of smart system can be described in power flow regulation to the load by detection and identification of amplitude, phase angle, and frequency of the voltage source compared to the system reference. The system mechanism is based on detection of voltage source using static transfer switch (STS) with phase locked loop (PLL) as voltage detection algorithm which output is used to determine decision logic algorithm for switching conditions. The results show that conditions of smart power system flow can be obtained based on voltage source selection in decision logic when fault condition occurs. DOI: http://dx.doi.org/10.11591/ijpeds.v4i1.5368

Improving Energy Efficiency of Smart Household Appliances and Devices

With the ever-increasing volume of applications of various kinds of electric drives in all spheres of human activity, the issues in improving the efficiency of the electromechanical converters of electric energy, one of the most important components of the electric drive (ED), are becoming increasingly important. Such issues include reducing their weight and size, improving the functional characteristics of these devices to increase their operational life and reducing the cost of manufacture. Taking full advantage of these opportunities relates to the AC and DC single-phase commutator motor (SCM), which is widely used in regulated and high-speed motor drives in home appliances and electric hand tools. The SCM is used in machinery where the load torque has a hyperbolic dependence on the rotational speed and the need to work with a large motor overload due to the “soft” mechanical characteristics of such motors.

Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households

In the near future, a smart grid will accommodate customers who are prepared to invest in generation-battery systems and employ energy management systems in order to cut down on their electricity bills. The main objective of this paper is to determine the optimum capacity of a customer's distributed-generation system (such as a wind turbine) and battery within the framework of a smart grid. The proposed approach involves developing an electricity management system based on stochastic variables, such as wind speed, electricity rates, and load. Then, a hybrid stochastic method based on Monte Carlo simulation and particle swarm optimization is proposed to determine the optimum size of the wind generation-battery system. Several sensitivity analyses demonstrate the proper performance of the proposed method in different conditions.

Regulated Charging of Plug-in Hybrid Electric Vehicles for Minimizing Load Variance in Household Smart Microgrid

With the advent of the plug-in hybrid electric vehicles (PHEVs), the vehicle-to-grid (V2G) technology is attracting increasing attention recently. It is believed that the V2G option can aid to improve the efficiency and reliability of the power grid, as well as reduce overall cost and carbon emission. In this paper, the possibility of smoothing out the load variance in a household microgrid by regulating the charging patterns of family PHEVs is investigated. First, the mathematic model of the problem is built up. Then, the case study is conducted, which demonstrates that, by regulating the charging profiles of the PHEVs, the variance of load power can be dramatically reduced. Third, the energy losses and the subsidy mechanism are discussed. Finally, the impacts of the requested net charging quantities and the battery capacity of PHEVs on the performance of the regulated charging are investigated.

Anonymous authentication for privacy-preserving IoT target-driven applications

The Internet of Things (IoT) will be formed by smart objects and services interacting autonomously and in real-time. As an application scenario, household smart meters will provide real-time neighborhood information which enables a smart community to cooperatively identify patterns, adapt consumption and improve overall quality of life, making the shared environment more sustainable. There is, in these types of settings, a major need toward securing all communications, placing equal effort on guaranteeing privacy properties (e.g., participant anonymity, unlinkability) as on assuring security properties (e.g., content authenticity). In this article, we present a fully decentralized anonymous authentication protocol aimed at encouraging the implementation of privacy-preserving IoT target-driven applications. The system is set up by an ad-hoc community of decentralized founding nodes. From then on, nodes can interact, being participants of cyber-physical systems, preserving full anonymity. We also present a performance and security analysis of the proposed system.

An event driven Smart Home Controller enabling consumer economic saving and automated Demand Side Management

This paper proposes the design of a Smart Home Controller strategy providing efficient management of electric energy in a domestic environment. The problem is formalized as an event driven binary linear programming problem, the output of which specifies the best time to run of smart household appliances, under a virtual power threshold constraint, taking into account the real power threshold and the forecast of consumption from not plannable loads. The optimization is performed each time the system is triggered by proper events, in order to tailor the controller action to the real life dynamics of an household. This problem formulation allows to analyze relevant scenarios from consumer and energy retailer point of view: here overload management, optimization of economic saving in case of Time of Use Tariff and Demand Side Management have been discussed and simulated. Simulations have been performed on relevant test cases, based on real load profiles provided by the smart appliance manufacturer Electrolux S.p.A. and on energy tariffs suggested by the energy retailer Edison. Results provide a proof of concept about the consumers benefits coming from the use of local energy management systems and the relevance of automated Demand Side Management for the general target of efficient and cost effective operation of electric networks.

A Survey of Communications and Networking Technologies for Energy Management in Buildings and Home Automation

With the exploding power consumption in private households and increasing environmental and regulatory restraints, the need to improve the overall efficiency of electrical networks has never been greater. That being said, the most efficient way to minimize the power consumption is by voluntary mitigation of home electric energy consumption, based on energy-awareness and automatic or manual reduction of standby power of idling home appliances. Deploying bi-directional smart meters and home energy management (HEM) agents that provision real-time usage monitoring and remote control, will enable HEM in “smart households.” Furthermore, the traditionally inelastic demand curve has began to change, and these emerging HEM technologies enable consumers (industrial to residential) to respond to the energy market behavior to reduce their consumption at peak prices, to supply reserves on a as-needed basis, and to reduce demand on the electric grid. Because the development of smart grid-related activities has resulted in an increased interest in demand response (DR) and demand side management (DSM) programs, this paper presents some popular DR and DSM initiatives that include planning, implementation and evaluation techniques for reducing energy consumption and peak electricity demand. The paper then focuses on reviewing and distinguishing the various state-of-the-art HEM control and networking technologies, and outlines directions for promoting the shift towards a society with low energy demand and low greenhouse gas emissions. The paper also surveys the existing software and hardware tools, platforms, and test beds for evaluating the performance of the information and communications technologies that are at the core of future smart grids. It is envisioned that this paper will inspire future research and design efforts in developing standardized and user-friendly smart energy monitoring systems that are suitable for wide scale deployment in homes.

A Novel Smart Household Control System by Computer Vision

For the disable people or the aged people, they need extra help in their daily household life. Various modern devices have been developed to improve their living quality. These devices always have automatic functions which are considered crucial for their independent life. Different to the traditional automatic household appliance such as manually infrared remote-controller and automatic voice-operated switch, this paper presents a novel approach based on computer vision to realize intelligent household control. This proposed system uses Adaboost and ASM algorithm for face detection and feature point calibration. Based on the facial key points, the head postures and mouth states are calculated and then coded into a special data packet. Finally, the packet is sent by an infrared carrier to the intelligent appliance with infrared receiver to control their operation manner. By using computer vision technology with infrared communication, the system is especially effective for the disable people such as the upper-body paraplegic and the people with hand dysfunction.