Energy Management in Smart Homes using an Experimental Setup …webx.ubi.pt/~catalao/ICEUBI_Mendes.pdf · 2014-03-30 · Energy Management in Smart Homes using an Experimental Setup

INTERNATIONAL CONFERENCE ON ENGINEERING UBI2013 - 27-29 Nov 2013 – University of Beira Interior – Covilhã, Portugal

Energy Management in Smart Homes using an Experimental Setup with Wireless Technologies T.D.P. Mendes a, G.J. Osório a, E.M.G. Rodrigues a, J.P.S. Catalão a,b,c a University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha, Portugal b INESC-ID, R. Alves Redol, 9, 1000-029 Lisbon, Portugal c IST, University of Lisbon, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal e-mail de contacto: [email protected]

Conference Topic – CT9 - Energy Abstract This paper aims to provide experiences from field tests using wireless technologies and the associated solutions, namely microcontrollers and software applications, for energy management in smart homes. The system architecture is described and experimental results are provided for monitoring and intelligent control of home appliances, enabling demand response in real-time. The benefits of advanced information and communication technologies associated to home automation are thus demonstrated for improving energy efficiency.

Key Words: Energy management, Smart homes, Field tests, Wireless technologies. 1. Introduction

Over the last years there has been an increased interest in cutting edge technologies and solutions contributing to the smart home concept [1]-[6].The smart grid architecture (Figure 1) aims to endow consumers with information in real time for energy management [7], benefiting from the advances in the communication technologies [8]. The contribution of this paper is the development, test and demonstration of a new experimental setup for monitoring and intelligent control of home appliances using wireless technologies, namely ZigBee devices. Any device at home can be remotely connected or disconnected using the internet, thus enabling demand response. Furthermore, energy consumption at the home can be monitored and controlled in such a way as to allow cost reductions and efficiency improvements. Wireless sensor networks are rapidly gaining popularity for smart grid applications, especially the use of the IEEE 802.15.4 and ZigBee to effectively deliver solutions for energy management and efficiency, home and commercial building automation [9]. ZigBee standard is a specification of a high level communication protocol based on the IEEE 802.15.4 standard. ZigBee devices have very low power consumption, fit perfectly in embedded systems and applications in all areas in which the main requirements are easy implementation and versatility.

Figure 1 – Smart grid architecture [7].


2. Wireless Network Protocol Overview

Wireless technologies for covering short distances among a private group of devices, either for personal use or for providing custom services in residential or industrial areas is now a reality. Various proprietary protocols as well as open standards are competing on Different levels of communication capabilities are disposable. For smart home concept implementation, open standards reveal to be suitable because device integration does not depend on a specific manufacturer. Furthermore, more players will compete on the market by lowering devices prices. In this paper the focus is on wireless personal area network (WPAN) whose main characteristics are:

Low cost; Low power; Short range; Small networks;

2.1 Zigbee over IEEE 802.15.4

It is a low power wireless specification based on the Institute of Electrical and Electronics Engineers (IEEE) standard 802.15.4. ZigBee is targeted towards applications such as remote control, distributed automations services but also smart meter emerging market. Zigbee operates in the industrial, scientific and medical radio bands. 2.4 GHz is allowed in most jurisdictions worldwide while other bands are also permitted in specific regions of the globe: 868 MHz in Europe and 915 MHz in the USA. The ZigBee technology is organized as a protocol stack, i.e. in a multilayer architecture such as the ISO OSI. The layers have interfaces that expose entities to higher layers via an SAP (Service Access Point), and each primitive supports a number of services to accomplish the functionality provided. The entities may be: data that provides data transmission services, or run, which provides all of the other features. Figure 2 illustrates the ZigBee stack layers: Application layer (APL - Application Layer) and network layer (NWK - Network Layer). The PHY and MAC layers belong to the IEEE 802.15.4 standard. Each layer interacts with the layer directly below, through their service primitives contained in their SAPs, provided by its internal entities and data management.

Figure 2 – ZigBee Standard.

The APL layer is responsible for managing user applications and abstract their network. In this layer, communication is end-to-end, i.e., independent of how many intermediate nodes are communicating between devices, allowing transmissions with return acknowledgment (ACK - Acknowledgement) or not. In it are three important sub-layers: the application support sublayer (APS - Application Support Sublayer), the application framework (Application Framework) and the ZigBee device object (ZDO - ZigBee Device Object).


The application framework shall include user applications residing on endpoints (1 to 240), and the ZigBee Device Object (ZDO) which resides on the endpoint 0 (zero). Each of these interacts with the service primitives in SAP - APSDE the APS sublayer for sending data between peer applications. The tasks of network and device management are performed by user applications through ZDO own. In turn, the ZDO delegate these functions to the APS (through the service primitives of APSME - SAP), or ZPD. The ZigBee device object (ZDO) is a base class functionality, which provides an interface between the user application objects, the device profiles (ZPD - ZigBee Device Profile), and application support sublayer (APS). The ZDO is located between the application framework and the APS, and meets all requirements of applications operating in the ZigBee stack. The application support sublayer (APS) interacts directly with the network layer (NWK), through its service primitives provided by NLDE - SAP (data transfer between peers) and NLME - SAP (network management and device). She is also responsible for managing groups and linkages of the network. In it are contained entities: data (APSDE - APS Date Entity) and management (APSME - APS Management Entity), which perform all the tasks through their service primitives located in their SAPs. The Network layer (NWK) is the lowest layer of the ZigBee standard, and is responsible for performing the multiple hops (multi - hop) network, for routing based on specific topologies (star, tree or mesh), the formation and management PAN, and many other functions that focus only ZigBee network. She concentrates two entities: data (NLDE - NWK Layer Data Entity) and management (NLME - NWK Layer Management Entity), which provide service primitives to the application layer, through their SAPs. There is also a security service provider (SSP - Security Service Provider) that works directly with the units of security management of network layer (NWK) and application support sublayer (APS). The security is through the use of AES -128 encryption and authentication. There are three ZigBee device types: coordinator, router and end point. Concerning the network topologies, we can have star, mesh and tree topologies, as shown in Figure 3.

Figure 3 – ZigBee network topologies: a) Star; b) Mesh; c) Tree.

2.2 Bluetooth

Also known as the IEEE 802.15.1 specification, it is a short-range communications technology aiming the interconnection of devices centered on an individual person's workspace - being known as wireless person area network (WPAN). From an application point of view it is intended for connecting devices such as mice, keyboards, and printers on ad-hoc mode. Bluetooth networks are established dynamically and automatically as new wireless devices are integrated. It offers higher level service profiles, such as FTP-like file servers, file pushing, voice transport, serial line emulation, and more.


Two types of topology are supported: piconet and scatternet. When a device is serving as master and the other devices are operated as slaves, the network organization has the name of piconet. In this arrangement only point-point communication capability is permitted between each slave and the network master device. However for the master entity the transmission may be point-to-point or point-to-multipoint. All slave transmission tasks are regulated by a broadcast signal that synchronizes the slave devices operations relatively to the master clock. Slave units can switch between active mode an standby mode in order to reduce power consumption. In the other network arrangement, scatternet, various piconet networks share the same geographic area. This topology allows a Bluetooth device being connected to more than one piconet network at the same time. Therefore, a single device may participate as slave in several piconets. However, playing with the master role is restricted to a single piconet.

2.3 Wi Fi - IEEE 802.11 a/b/g/n/i

Wireless-fidelity (Wi-Fi) is commonly used to describe a class of wireless local area network (WLAN) devices based on the IEEE 802.11 norm which is a group of wireless communication interfaces. Wi-Fi devices aim to connect and access the Internet directly or through a router without any physical association with a wired network by using unlicensed radio bands. Likewise other wireless technologies, there is no need planning prior to network formation. IEEE 802.11 standard defines a basic set of mobile or fixed stations named basic service set (BSS), which comprises a set of mobile or fixed stations. In a case a station moves out, it is not any more able to communicate with other members of the BSS. There are two distinct network configurations. On an IBSS mode all members of the BSS talk between themselves directly and self-organize without an access point (AP). On an ESS mode several BSS’s are interconnected in order to create an extended network. To link multiple BSS’s an architectural component called distribution system (SD) is used, enabling with AP interface the building of Wi-Fi networks of arbitrary size and complexity.

2.4 SimpliciTI

Developed by Texas Instruments is an open source low power proprietary RF network protocol. It supports 2 basic topologies: peer-to-peer and star topology in which the star hub is a peer to every other device. Three device types are specified by the protocol:

a) The Access Point node is used primarily for network management tasks. It can also support End Device configurations. Moreover, in the star configuration can also be configured as a gateway interface;

b) A Repeater node has the mission to extend the radio range in network. In practice what it does is to repeat frames by linking two or more nodes;

c) The End Device supports most of the sensors or actuators of the network. A peer-to-peer network is possible among end devices or through a Repeater.

Unlike other wireless protocols, SimpliciTI utilizes a very basic core API (application programming interface) which implies small memory requirements and low amount of MCU resources. Protocol architecture does not follow ISO reference model. Only 3 layers are needed for its implementation: data Link, physical, network and application layers. Physical and data link layers are not explicitly defined by the norm. Instead, SimplicityTI may run on any TI radio, operating below 1GHz or at 2.4GHz either standard or proprietary. Hence, data are received directly from the RF transceiver which processes the data frame. However to hide the differences between supported hardware radios, a layer called Minimal RF Interface performs a frame write/read interface. In addition, in order to secure a minimum support for various TI mcu’s, SimpliciTI provides also an interface for this purpose in the form of a BSP entity (Board Support Package). Above, the Network Layer manages the RX and TX queues and dispatch frames to their destination, as well as may set network parameters such as base frequency or modulation method, data rate and other general radio parameters.


2.5 Wireless protocols comparison Table I illustrate the main differences among the four protocols [7-15].

Table 1- Main differences among the four protocols.

ZigBee over 802.15.4

Bluetooth (IEEE 802.15.1)

Wi-Fi IEEE 802.11a

/b/g/n/i SimpliciTI

ISM bands 2.4GHz

915MHz (USA) 868MHz (EU)

2.4 GHz 2.4GHz 5 GHZ

2.4 GHz and

Sub 1 GHz

Number of RF channels 16 79 14 ( 2.4 GHz)

8 (5 GHz) Set by the application

Network topology

Ad-hoc, peer to peer, star or mesh

Ad-hoc, piconet or scatternet Point to hub Start and

peer to peer

MAC scheme CSMA-CA TDD CSMA-CA/PCF Listen-

before-talk (LBT)

Modulation scheme

BPSK (868-915MHz)

OQPSK(2.4GHz)

GFSK/DQPSK 8DPSK

(optional)

BPSK, QPSK,COFDM, CCK, M-QAM MSK

Nominal rate 250kbit/s

1Mbit/s (v1.2) 3Mbit/s (v2.0) 24Mbit/s (v3.0)

11-65-450(IEEE802.11n) Mbit/s

Up to 250kbit/s

Power saving mechanism Supported Supported Supported Supported

Encryption AES128 64 and 128 bit Only IEEE 802.11i

AES128 on enabled HW

devices, other in software

Data authentication 32/64/128bit code Device pairing

protocol Only IEEE 802.11i Not supported

Data protection 16bit CRC 32bit CRC 32bit CRC Depends on

TI radio

Autonomy (Days) 100 to 1000+ 1 to 7 0.5 to 5

Depends on battery

specifications Range (m) 10-100 m 10 m 10 -100m 10m

Application areas

Remote control and automation in

residential and commercial

buildings

Wireless connectivity

between personal

devices such as headphones,

mobile phones or laptops.

Wireless LAN connectivity,

broadband Internet access

Distributed alarm and security devices, energy

meters and home

automation

Advantages

Low power consumption,

several application profiles (home

automation, smart energy) and

topology flexibility

Speed and flexibility

Speed and flexibility

Small code size and low

software complexity


Bluetooth as well as Wi-Fi IEEE802.11 show a higher data throughput while Zigbee and Simplicity can´t surpass 250kbit/s as maximum data rate. All protocols have encryption native mechanisms. Regarding data authentication support only SimpliciTI does not exhibit this functionality. Even if Bluetooth and Wi Fi IEEE 802.11 are targeted for short range applications as the other protocols, there are serious limitations when it comes to set up a wireless network based on smart home concept. The absence of an internal structure to deal with this application context would require substantial efforts on application layer design. Although SimpliciTI address home automation, still lacks resources for effective monitoring and intelligent control of home appliances. In addition mesh arrangement capability has no internal support. By the other hand ZigBee protocol address the requirements for smart energy home network through standard interfaces and device definitions, allowing product interoperability among smart energy devices produced by various manufacturers [16].

3. Energy management system architecture

A simple home energy management model is proposed for our experimental tests as shown in Figure 4. It can be distinguished two distinct wireless infrastructures: Home Area network (HAN) and Wide Area Network (WAN). At the lowest level a ZigBee network is responsible for energy monitoring and remote control of electric loads such as washing machine, air conditioner, lighting and including power measurement capability too. One single device has the network coordination role (Zigbee coordinator), being responsible for initiating the network itself as well as for sending remote control messages. Data frames are only allowed through direct transmission between the Zigbee coordinator and Zigbee end devices. Taking in consideration that the smart energy concept proposed by paper’s authors aims mostly small size homes, we discarded the necessity of assigning router capabilities to specific Zigbee modules. At the highest level, a communication infrastructure for covering large geographic areas enable the home owner to track its domestic energy consumption in real time, reacting and deciding which of those home loads should be disconnected.

Figure 4 – Zigbee energy management architecture overview.


4. Experimental Procedure

The field test was conducted using the following tools:

a) 2 XBee wireless RF modules compliant with ZigBee standard; b) MSP430G2553 TI microcontroller; c) 8 channel Relay board; d) Arduino shield board.

The Arduino shield board is used for placing the ZigBee and also to wire this board to the MSP430G2553 microcontroller. The relay output can be connected to a lamp or any other home appliance. Several software tools were used: Embedded Workbench IDE v. 5.51.4 cross-compiler, X-CTU configuration tool and the old Hyperterminal terminal emulation program. MSP430G2553 firmware was compiler on IAR Embedded Workbench MSP430. The first step to start with the program was to switch LED state. This purpose allows connecting the relay ON/OFF. The transmission data rate was set at 9600 bits per second. After the construction of the program, we moved to the configuration of the modules using the X-CTU software, noting the respective codes of Xbee modules, as illustrated in the following Figure 5.

Figure 5 – Addressing modules.

Then, the program uses the X-CTU Maxstream to configure the modules, that is, using the parameters DH and DL, which are source addresses and destination modules respectively. These addresses are changed in the software menu as "Modem Configuration". According to the figure the network identifier (PAN ID) is designated by “3332”, the same value in the two modules. In module 1, the address DH is “13A200” and address DL is “405C2B82” module 2. The module 2 configuration is exactly the same as the previous module except, address DL that has the value “405C2BAC”. After all has been assembled as in Figure 1, we used another HyperTerminal software. This software allows receiving or sending data; in this test case will receive information from the LED - "LED ON" or "LED OFF", sending the character corresponding to the letter "L" to turn on the LED on, and the letter "D" to turn off the LED. When making the transmission mode: the letter "L" indicates to us that the LED will operate. The program inserted in MSP430, represented in ASCII code, is the language that understands the microcontroller to send the data. If the user presses any key of the computer without the letter "L" and "D", the HyperTerminal "ERROR" message will appear.


This word "ERROR" was programmed into the microcontroller, intending to work safely with no locks. Thus, to represent "ERROR" means that the microcontroller will ignore the other keys and also give information to the user about what is happening. Previously, the letter that has been ignored is the letter "T". With the IAR Embedded Workbench program open view of the microcontroller, when the letter was sent from Hyperterminal it appears in the following the letter "L". A smart meter is also considered for monitoring purposes, as shown in Figure 6. These devices are associated with an LCD display, which allows real-time visualization of the consumption.

Figure 6 – Commercial smart meter application.

In this work we use this meter to analyze consumption during the first three months of the year and see what the day with the high consumption. To get an idea Figure 7 represents the energy consumption related to the Month of January 2013.

Figure 7 – Power consumption on January 2013.


In this Figure 7, we can conclude which was the day of the month with highest consumption, more precisely on 17/01/2013 marked in red; the second reached 21.59 kWh in the energy monitor. A minimum of 5.70 kWh was measured on January 5 (green bar). Finally, this wireless display can also represent the monthly demand, i.e. the sum of the loads installed operating in the same time interval. In Figure 8, the demand for the month of January 2013 is shown.

Figure 8- Daily power consumption sample on January 2013.

It can be seen that power peak demand happened between 8:00 PM and 10:00 PM which corresponds to intensive domestic appliance usage during dinner preparation and when house habitants have already arrived. From 24:00 AM to 6:00 PA energy consumption is fairly low and almost constant. The reduced electric consumption observed at night period was expected since the number of electric loads connected to grid reaches a minimum value because the house occupants are sleeping. Intermediate power peaks refer to weak up every morning and to launch time.

5. Conclusion

This paper presents an experimental wireless network system for energy management based on the smart home concept. Prior to its implementation discussion, a comparison between short range wireless protocols is presented. The overview highlights the main characteristics of nonproprietary and proprietary standards. Zigbee, Bluetooth and Wi Fi IEEE 802.11 norms fit in the first category, while SimpliciTI, still open source, belongs to the other category. A simple smart home architecture is proposed using Zigbee standard, since it provides native functionalities for remote control and automation in residential buildings. Smart concept implementation relies on MSP430 TI microcontroller for establishing a PC-Zigbee network interface (Zigbee coordinator is wired to MCU board). Zigbee capability for remote electric load control is tested with low power devices such as leds, but also using relay board (Zigbee end device modules). A commercial power metering system is also used for analyzing domestic energy consumption. Gathered data are collected from real home electric consumption.


The tool revealed to be easy to use and effective when it comes to track daily consumption. However, the energy meter does not allow the connection to a Zigbee network, still it shows RF capability but on proprietary basis. In the near future it is intended to expand the experimental wireless network system by developing and integrating an electric power meter with Zigbee capability.

References [1] D.-M. Han and J.-H. Lim, "Design and implementation of smart home energy management

systems based on ZigBee," IEEE Transactions on Consumer Electronics, vol. 56, no. 3, pp. 1417-1425, 2010.

[2] B. Asare-Bediako, P. F. Ribeiro, and W. L. Kling, "Integrated energy optimization with smarthome energy management systems," in: Proc. 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe-ISGT Europe, Berlin, Germany, 2012.

[3] What is the Smart Grid?.Purdue University, IN. [Online].Available: http://www.purdue.edu/discoverypark/energy/research/efficiency/smart-grid_what-is.php

[4] D. Markovic, D. Cvetkovic, D. Zivkovic, and R. Popovic, "Challenges of information and communication technology in energy efficient smart homes," Renewable and Sustainable Energy Reviews, vol. 16, pp. 1210-1216, 2012.

[5] D.-M. Han and J.-H. Lim, "Smart home energy management system using IEEE802.15.4 and ZigBee," IEEE Transactions on Consumer Electronics, vol. 56, no. 3, pp. 1403-1410, 2010.

[6] I. F. Akyildiz, “Wireless Sensor Networks,” Georgia Institute of Technology, pp. 6, 2010. [7] N.C. Batista, R. Melício, J.C.O. Matias, J.P.S. Catalão, “ZigBee wireless area network for

home automation and energy management: field trials and installation approaches", in: Proceedings of the 3rd IEEE PES Innovative Smart Grid Technologies Europe Conference — ISGT Europe 2012, Berlin, Germany, October 14-17, 2012.

[8] M. Erol-Kantarci and H.T. Mouftah, " Smart home energy management system using IEEE 802.15.4 and Zigbee," IEEE Transactions on Smart Grid, vol. 2, no. 2, pp. 314-325, 2011.

[9] Jin-Shyan Lee, H. Su, “Comparative study of wireless protocols: Bluetooth, UWB, ZigBee, and Wi-Fi,” IEEE industrial electronics society Conference, 2007.

[10]P. Smith, “Comparisons between Low Power Wireless Technologies”, on-line, 24-May 2011.

[11]S. Farahani, “ ZigBee Wireless Networks and Transceivers, Book 1st Edition, 22-Sep-2008. [12]P. Yi, “ Developing ZigBee Deployment Guideline Under Wifi Interference for Smart Grid

Applications”, IEEE Transactions on Smart Grid, Vol. 2, NO.1, March 2011. [13]Wi-fi, website: [https://www.wi-fi.org/], accessed 1 Sep 2013. [14]Introduction to SimpliciTI, website: [http://www.ti.com/lit/ml/swru130b/swru130b.pdf],

accessed 5 Sep 2013. [15]L. Friedman, “SimpliciTI: Simple Modular RF Network Specification”, San Diego, California

USA, 2007. [16]Dae-Man Han and Jae-Hyun Lim, "Wireless sensor networks for cost-efficient residential

energy management in the smart grid," IEEE Transactions on Consumer Electronics, vol. 56, no. 3 pp. 1403 -1410, 2010.

[17]J. Byun, B. Jeon, J. Noh, Y. Kim, and S. Park, "An intelligent self-adjusting sensor for smart home services based on ZigBee communications," IEEE Transactions on Consumer Electronics, vol. 58, no. 3, pp. 794-802, 2012.

[18]M. Kuzlu, M. Pipattanasomporn, and S. Rahman, "Hardware demonstration of a home energy management system for demand response applications," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1704-1711, 2012.

[19]B. Qela, and H. T. Mouftah, "Observe, Learn, and Adapt (OLA)—An algorithmfor energy management in smart homes using wireless sensors and artificial intelligence," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 2262-2272, 2012.

Documents

Energy Management in Smart Homes using an Experimental Setup …webx.ubi.pt/~catalao/ICEUBI_Mendes.pdf · 2014-03-30 · Energy Management in Smart Homes using an Experimental Setup