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Work in progress: Towards the energy-efficient consumption applied to digital home

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In recent decades, there has been an increase in the use of robotics in home automation environments. That, joined to the interest in efficient consumption of energy, is the base of the research exposed next. Nowadays, the increase of robotic systems
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    Work in progress: Towards the energy-efficient consumption applied to Digital Home  Ignacio González Alonso, Alejandro Álvarez Vázquez, Mercedes Fernández Alcalá and Almudena García Fuente.  Department of Computer Science. University of Oviedo. Oviedo, Spain. gonzalezaloignacio@uniovi.es, alvarezvalejandro@uniovi.es, fernandezmercedes@uniovi.es, agarciaf@uniovi.es  Abstract - In recent decades, there has been an increase in the use of robotics in home automation environments. That,  joined to the interest in efficient consumption of energy, is the base of the research exposed next. Nowadays, the increase of robotic systems in human daily activities has facilitated its integration and diversification and, due to this, new needs have come up. An example of this situation is the case of service robots that, as well as give comfort to the user, they can provide an energy efficient consumption. The aim of this work is to lay the concept of energy and Smart Grids in a smart home interoperability protocol like DHCompliant. This will make possible a greater energy and economic saving, providing the user the possibility of making strategic decisions regarding their energy consumption.    Keywords: Power Management, Energy-aware systems,  Interoperability. I.   I  NTRODUCTION  In the last decades, the use of different robotic systems has increased considerably, in different environments like industry (i.e. Articulated robot 5 DOF, model Catalyst-5), space (i.e. Space Shuttle Canadarm Robotic Arm) and home automation (i.e. Roomba). Some studies point out that this increment in heterogeneous systems means that it is needed to guarantee the interoperability between them.  Nowadays there are different protocols for interoperability and energy efficiency. From the most generic like HTTP, UDP/IP, and TCP/IP to other more specific protocols such as Pulse Protocol [1], oriented to energy efficiency. In the proposed solution it will be defined a set of saving and management energy concepts. Also, through the energy service offered by the protocol, the user will be able to get to know in detail the data linked with energy consumption in a home automation environment. Through data obtained, users will be able to intervene in decisions about that consumption. The following sections will present the concepts of interoperability and Smart Grids, then it will be defined the objectives and methodology that will be used to develop a module of Energy control into the Smart Home. II.   E VOLUTION AND ENERGY EFFICIENCY IN THE PROTOCOLS  In recent years, the interest by energy consumption, saving and management of that consumption has increased [2]. Some of the most important researches and advances have  been carried out in areas as diverse as automotive industry and home automation environments. It is necessary to mention the study done by UCLA’s researchers [3]. In 2003, they defined STEM, a topology management for energy efficient sensor networks, specifically wireless sensor networks, where the energy efficient is the key design challenge and the energy consumption is typically dominated by the node's communication subsystem. Besides, in 2006, National University of Singapore  published a study about the energy management [4]. It is focused on Energy management in the standard IEEE 802.16e. In it, it is shown the comparison between using and not using standardized sleep mode in IEEE 802.16e.  A.   UPnP (Universal Plug and Play) The UPnP (Universal Plug and Play) [5] architecture offers pervasive peer-to-peer network connectivity of PCs of all form factors, intelligent appliances, and wireless devices. The UPnP architecture is a distributed, open networking architecture that leverages TCP/IP and the Web to enable seamless proximity networking in addition to control and data transfer among networked devices in the home, office, and everywhere in between.  Nowadays, UPnP Forum members work together to define and publish UPnP device control protocols built upon open, Internet based communication standards. It means the integration of efficient energy consumption and the usage of Smart Grids in UPnP. Members carried out  periodically videoconferences and at this moment they have proposed a use case in their site web. In this research, user can select his prefer tariff knowing information tariffs.  B.    Protocols oriented to energy efficiency ZigBee is a specification for a set of high level protocols of wireless communication. Its goals are secure communications with low send data rate and to maximize its batteries life. These are some characteristics that make it different from other technologies: low energy, network mesh topology and easy integration. LongWork protocol or Network Control Standard EIA 709.1 is an open protocol and a communication standard developed by Echeron Corporation. LongWork is used in  building automation, industrial control and transports. BACnet is a data communication protocol for building 978-1-4673-0378-1/11/$26.00 ©2011 IEEE    automation and control networks. It is an ISO global standard and a European standard. It is an open and standard protocol. For that reason, Data from different systems are available in one common format, independent of vendor. This protocol defines some services that are used to communicate between building devices. Department of Computer Science of Johns Hopkins University defined Pulse Protocol. It is an energy efficient  protocol for infrastructure access. A set of simulation have demonstrated that this protocol is effective at both routing and conserving energy. The Pulse protocol utilizes a  periodic flow initiated at the network gateways, which  provides both routing and synchronization to the network. This synchronization is used to allow idle nodes to power off their radios for a large percentage of the time when they are not needed for packet forwarding. The protocol design is centered on the fixed pulse interval. The pulse serves two functions simultaneously. First, it serves as the  primary routing mechanism by periodically updating each node in the networks route to the nearest pulse source. In addition, it is used to provide network-wide time synchronization. The protocol has got a high scalability in relation with mobility, flow number and node number. C.   SMART GRID The concept of Smart Grid is the evolution of the current  philosophy of power consumption. In order to adjust the electric consumption to the conditions and pricing at real time, energy suppliers and clients have decided to respond to the demand for energy. This contrasts with the traditional system where the energy supply must meet demand [6]. This change into the electric industry tries to produce a transformation from a centralized, producer-controlled network to one that is less centralized and more consumer-interactive [7]. The smart grid is based on the use of smart energy technologies to optimize the system by supply control through digital information systems (applications and smart meters) that communicate via Internet with the  power suppliers. Key aspects of the Smart Grid are: •   Ability of the grid to self-healing after a disturbance. •   Power supply free from sags, swells, outages, and other power quality/reliability issues. •   Support for renewable energy sources. •   Better asset utilization via monitoring. •   Increased monitoring through low cost sensors. The smart grid is therefore a link between two independent infrastructures (communication and energy). This combination of electric measuring system and device of access to telecommunications will be used to exchange information between users and providers to accommodate the needs of energy availability. The user shall have an essential role in optimizing the Smart Grid; LG offers a full range of smart appliances based on LG THINQ™ Technology [8] focused on five features. The Smart Grid feature represents the base of LG THINQ™ Technology, it deploys a smart meter to ensure that appliances use the minimum amount of energy at the least expensive rates as  possible hence Less Energy, Lower Electricity Bills, Eco-Friendlier Life. Load control will reduce the need of peak load power  plants and infrastructure necessary to support them. The Smart Grid technology emphasizes two concepts: •   Metering. The smart energy meter is able to log, in real time, energy consumption at fine granularities and to store the values into a digital form. •   Visualization. Visualization of the metering data is vital if the grid operators and building managers have to make better decisions and policies with respect to energy usage. 1)    Advanced Metering Infrastructure (AMI) AMI [9] is the deployment of a metering solution with two-way communications to the electric meter to enable key features. AMI is characterized by: •   Two way communications to the electric meter to enable time stamping of meter data, outage reporting, communication into the customer  premise, service connect / disconnect on-request reads, and other functions. •   Ability of the AMI network to self registers meter  points. •   Ability of the AMI network to reconfigure due to a failure in communications. •   AMI system interconnection to utility billing, outage management systems, and other applications. 2)   Visualizing Energy Resources Dynamically on Earth (VERDE) The VERDE [10] tool is a U.S. Department of Energy  project that provides visualization of energy data. VERDE seeks to provide real-time awareness of the electrical grid combining geographic and weather data with real-time sensors reading to give a "health status" of the nation's electric infrastructure. VERDE also can model and simulate grid behavior and analyze contingency plans for emergencies. With a platform built on Google Earth, it will provide rapid information about blackouts and power quality, as well as insights into system operation for utilities. 3)    Phasor Measurement Units Phasor Measurement Units (PMUs) [7] are among the most interesting development in the field of real-time monitoring of power systems. PMU units provide real-time measurement of positive sequence voltages and currents at power system substations. III.   D ESCRIPTION OF DHC  ARCHITECTURE  DHCompliant has been the architecture used in the  present experiment. It is a home automation and robotic system interoperability protocol set up over UPnP and it includes the following subsystems: Groups, Localization, Intelligence, Energy and Security & Privacy. In the Figure 1 it is shown a diagram that resumes DHC Architecture: The DHC- Energy [11] subsystem is intended to lay    the concept of energy management and smart grids into the DHCompliant protocol. It will be defined a set of saving and management energy concepts. Also, through DHC Energy, the user will be able to get to know in detail the data linked with energy consumption in a home automation environment. From this data, the user may intervene in the system to make decisions that affect energy consumption. All this information allows the user to administer the task execution mode in order to optimize energy waste, as well as control and monitor the monthly energetic consumption. This results in a reduced economic impact for the user as well as a lower environmental impact, laying the foundations for the energetic saving in the Smart Home.   A.    Interaction description between DHC-energy components There are four main components into the system: DHC-Energy UPnP Service within the DHCompliant UPnP Virtual Device, a Roomba vacuum cleaner robot which has performed the tasks, a Graphic User Interface (GUI) to interact with the DHC UPnP Device and an arena where the experiment have taken place. The experiment was modeled through SysML. IV.   O BJECTIVES AND SOLUTION PROPOSALS  The aim of this research is to lay the concept of energy and Smart Grids in the DHCompliant protocol. It will be defined a set of saving and management energy concepts. Also, through DHC Energy, the user will be able to get to know in detail the data linked with energy consumption in a home automation environment. Through data obtained, user will be able to intervene in decisions about that consumption.  A.    Previous Requirements In UPnP, it is possible to obtain the IP by two ways, using a DNS server that generates dynamic IP or through Auto-IP. In the first option, from time to time, it is necessary to check out if another device is using that IP address. All these actions mean an increase of sending messages and therefore, an increment in energy consumption. For this reason, DHCompliant must use dynamic IP and that is the reason why it is necessary to define the compulsory use of the dynamic IP in DHCompliant. The electrical appliances are classified in different categories according to their energy efficiency. Energy efficiency classes can be divided into seven categories; named using letters from A to G, being the A class the lower consumer. DHCompliant recommends the use of categories A-C, to minimize the energy consumption. In a home automation environment, it will be necessary to have a Smart Meter device. It is a computerized replacement of the electrical meter attached to the exterior of many of our homes today. It will indicate the different hourly tariffs. Also, it will inform, in real-time, about the electric and gas consumption. And finally, it will show the actual tariff. In a collaborative task executed by several robots, the leader is chosen among them, depending on each robot’s energy consumption. This choice aims to save the maximum amount of energy.  B.    Energy Management and Smart Grids 4)   Set tariff information In this section, it will be discussed the selection of the most economic energy configuration, in function of the chosen utility. The user can read tariff names and associated tariff information (maximum power consumption, cost per kWh, etc). With all these data, the user is able to select the most advisable tariff. The monitorization will be in real time, and the user would choose the best moment to whether to use the devices or not. When the user wants to determinate the moment to turn one dispositive on, the Control Point provides a list of tariffs and the time-of-day when each one is applied. Then, the user selects the time at the Control Point when the device shall turn on, and accepts the tariff. Finally, the device turns on at the desired time, if the tariff applies. Users will select a maximum acceptable price per kWh, then the device may turn on if the current tariff complies with this selection (i.e. price per kWh is lower or equal to maximum acceptable price) and the period for this tariff is longer than the device run-time. 5)    Device states On the other hand, it is important to know the user’s  preferences. These will be compared with the data sensed. The data show the device states and the source of energy. The source of energy can be renewable energy or the normal electric supply. 6)    Regulation based on meta information One of the main ways of managing the energy saving,  both at home and at intelligent builds, it is trough the temperature regulation based on meta information. It is necessary to use the metadata to know the temperature of the internal environment, as well as the temperature and external features (i.e. temperature, dampness, number of sunlight hours, rain, wind, etc.). F IGURE 1:   DHC OMPLIANT A RCHITECTURE .    7)    Measurement & Suggestion for carbon usage/Energy At this point, some recommendations, major decisions and actions will be carried out. This is the central part of a Smart Energy Network, allowing even to alternate  between the use of renewable energy to make more efficient power consumption, to less energy cost. Here, it is necessary to speak about the carbon footprint. It is a measure of the exclusive total amount of carbon dioxide emissions that is directly, and indirectly, caused by an activity or it is accumulated over the life stages of a product. 8)   Source regulation In this option, according to the “suggestions” discussed on the previous stage, the internal management will be carried out. So, the input data of this scenario will be the user preferences. 9)    Energy profiles a)    Previous requirements It is necessary that all the devices at home have different  power- consumption modes. These will be: the high consumption mode, low consumption and the OFF mode. Users can select the profile that best fits their needs with these options. b)    Definition of energy profiles There are a large number of devices to regulate their  power consumption (TV, phone mobiles, computers, i.e.). Therefore, in DHC – Energy it has been defined a series of energy consumption patterns (or, as they are usually called, energy profiles). Thus, the user will be able to choose one of the defined profiles for each device or for every house. c)    Assigning a profile for a device The user will be able to choose a device and assign an energy profile to it. Now, the three main profiles referred  before are shown: •   High – When the device is working at its full capacity. In this profile, the power-saving device will be the minimum. •   Low – When the device is working at its low capacity. In this profile, the power-saving device will be the highest. •   OFF – When the device is switched off. This profile is used to note that the user does not need the device and the energy consumption is null. d)    Assigning a profile for a full home automation environment Getting a full automation environment will be able with the addition of a new profile to the previous three. Furthermore of high, low and OFF profiles, it is necessary to create a new one called Emergency Profile. Using this  profile, only the most important devices will be plug in, while the others will be switched off. Plug in devices have to be selected previously, and all of them will work under the Low Consumption profile. A CKNOWLEDGMENT  This work was possible thanks to the financial support by the Spanish Department of Science and Technology. We must acknowledge the continuous support given by the University of Oviedo, and also for providing all the resources that made possible our research and, in  particular, by their management of the DHCompliant  project grant: MITC-09-TSI-020100-2009-359. We also thank Marina Gómez and Julia Menéndez for their technical assistance. R  EFERENCES   [1] B. Awerbuch, D. Holmer, and H. Rubens, “The pulse protocol: Energy efficient infrastructure access,” in INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, 2004, vol.2, p. 1467–1478. [2] J. Marco and N. D. Vaughan, “Architectural modelling of an energy management control system using the SysML,” International Journal of Vehicle Design, vol.55, no.1, pp. 1 - 22, 2011. [3] C. Schurgers, V. Tsiatsis, and M. B. Srivastava, “STEM: Topology management for energy efficient sensor networks,” in Aerospace Conference Proceedings, 2002. IEEE, 2005, vol.3, p. 3. [4] Y. Zhang and M. Fujise, “Energy management in the IEEE 802.16 e MAC,” Communications Letters, IEEE, vol.10, no.4, p. 311–313, 2006. [5] UPnP Forum, “UPnP Forum - Website.”[Online]. Available: http://www.upnp.org/. [Accessed: 08:23:35]. [6] Y. Agarwal, T. Weng, and R. Gupta, “Micro-Systems Driving Smart Energy Metering in Smart Grids,” DAC’07. [7] U.S. Department of Energy, “The Smart Grid: An Introduction.”2008. [8] LG, “LG THINQ Technology,” 2011. [Online]. Available: http://www.lgnewsroom.com/newsroom/contents_main.php?category=6&product_code=4&product_type=4&post_index=741. [Accessed: 09:46:38]. [9] D. G. Hart, “Using AMI to realize the Smart Grid,” in Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, 2008, p. 1–2. [10] M. Shankar, J. Stovall, A. Sorokine, B. Bhaduri, and T. King, “Visualizing Energy Resources Dynamically on Earth,” in Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, 2008, p. 1–4. [11] Infobotica Research Group, DHC-Energy Draft Specification 0.2. 2010.
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