-
Hardware Home Energy Management System for Monitoring the
Quality of Energy Service at Small
Consumers
Ciprian Ionut PAUNESCU, Tudor ZABAVA, Lucian TOMA, Constantin
BULAC, Mircea EREMIA Department of Electrical Power Systems
University POLITEHNICA of Bucharest
Bucharest, Romania Email: [email protected]
Abstract This paper presents a laboratory hardware system,
developed in the Department of Electrical Power Systems of
University Politehnica of Bucharest, that simulate an energy
management system to be applied in a smart home. The core of the
system is a controller that is capable of switching on/off various
domestic appliances as a response to price signals. The system may
be capable of communicating with all loads and with the main meter,
and may provide information about the power quality. Also, the
system may be capable of responding to suppliers signals in order
to provide a demand response service.
Index Terms-- home energy management system (HEM), smart home,
smart grids
I. INTRODUCTION According to Siemens [1], the buildings are
responsible
for 40% of the world energy consumption and for 21% of the total
greenhouse emissions. For these reasons, buildings are key elements
in the targets to reduce the energy consumption and to implement
sustainable development programs. Implementation of advanced
technologies and transforming the buildings into manageable
entities may help reducing the greenhouse emissions by up to
40%.
The smart home concept, together with the energy management
systems for small applications, are normal evolutions in the
implementation process of the smart grids concept towards
transforming the traditional consumers in more active ones,
becoming in some cases prosumers. Various solutions have been
proposed in the literature, and innovative projects have been
implemented in pilot projects, many of them focusing on metering
and data management.
A connected home platform and development framework for design,
development and deployment of smart home services is presented in
[2], whereas a lightweight key establishment protocol for smart
home energy management systems and the implementation details of
the protocol are proposed in [3]. One challenging technical issues
is the
compatibility between equipments. The Zigbee technology for
application in the smart home is presented in [4], where a new
routing protocol DMPR (Disjoint Multi Path based Routing) to
improve the performance of the ZigBee sensor networks is proposed.
The interaction between the user and the home energy management
system is decisive in helping the customer to easily adopt the new
technology. A user interaction interface for energy management in
smart homes is proposed in [5].
Various control and optimization algorithms have been proposed.
An optimal and automatic residential energy consumption scheduling
framework which attempts to achieve a desired trade-off between
minimizing the electricity payment and minimizing the waiting time
for the operation of each appliance in household in the presence of
a real-time pricing tariff combined with inclining block rates is
proposed in [6]. Authors of [7] and [8] propose optimization
algorithms to be implemented in the home energy management systems
to determine the optimal operation of residential appliances within
5-minute time slots while considering uncertainties in real-time
electricity prices.
II. THE CONCEPT OF HOME ENERGY MANAGEMENT SYSTEM
A home energy management (HEM) system includes any hardware and
software elements by means of which various energy management
objectives can be achieved. HEM includes metering systems, sensors
and communication infrastructure and thus it can be easily
identified by a smart metering system. A HEM is customized in terms
of customers needs and the type of energy services provided by the
suppliers.
A home energy management may be configured mainly into three
areas (Fig. 1): the main metering area, the home appliances area
and the external communication area. The home controller is the
brain which hosts the applications for
978-1-4673-6487-4/14/$31.00 2014 IEEE
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control and optimization. The communication with the home
appliances is performed via sensors.
The software implemented in the HEM system, through the home
controller, allows the customer to get informed about a large range
of economical and technical characteristics, among which:
Power/energy quality supplied from the public distribution grid;
the most important parameters are the voltage level, voltage dips,
overvoltages, flicker and harmonics;
Energy cost, for both the already consumed energy and for the
next period consumption based on forecasts; furthermore the energy
price for the next hours may also be provided; it is expected that
hourly or 15 minutes tariffs will be regular at small consumers in
the near future;
Operation scheduling and energy consumption may be performed in
terms of energy price and availability of local generation;
Figure 1. HEM Architecture [9].
A display may be used as the interface between the owner and the
HEM system. The owner may set the operation schedule, may start up
or shut down load appliances, or may change the status of various
load appliances for volunteer disconnection when requested by the
energy supplier.
A HEM may be designed so that to manage not only information
about electrical energy but also information about other services,
including water, natural gas, heating, etc.
The three zones of the HEM system are presented as follows.
A. The Home Appliances area This area consists of all load
appliances, generation units
(wind turbine, PV panel, diesel genset, battery, etc.), sensors,
switches, and communication infrastructure with the home
controller.
In order to apply some control functions, the load appliances
may be divided into two categories:
vital loads, which cannot be controlled, e.g. life systems,
refrigerator, desktop computer, etc.
controllable loads, which may be optimally scheduled for
operation or can be switched on/off at any time, e.g. heating
system, iron, air conditioner, washing machine, electric vehicle,
etc.
The home controller can get information from each load appliance
regarding the on/off state and the instantaneous consumption. On
the other hand, the home controller can receive information from
the generation units regarding instantaneous generation, state of
charge, atmospheric conditions, etc. and may schedule
charging/discharging of the battery (or the electric vehicle),
operation of controllable loads (e.g. washing machine).
Based on the information about the load appliances and the local
generation, the home controller may forecast the load for the next
hours, may calculate the amount of power available for
disconnection if required by the energy supplier.
B. The Metering Area It consists of all meters authorized by the
service supplier
and the distribution company (for electricity, water and natural
gas) and the communication infrastructure with the home
controller.
Until now, no clear general characteristics of the meters have
been defined in no country. The European Commission has issued a
directive by which the EU member states, if feasible [10], are
required to implement the smart metering for electrical energy at
all levels, while at least 80% of the meters to comply with the
smart metering requirements until year 2020.
Since these meters are the only equipments authorized as
judicial interface between the customer and the service supplier
and the distribution company, besides the energy quantity, they
should be designed so that to provide at least energy quality
parameters and compatible communication protocol. Other functions
(e.g. operation scheduling) are more appropriate to be implemented
in the home controller as they may be customized according to the
customers needs. Examples of meters, for electrical energy, water
and natural gas are shown in Figure 2.
a. b. c.
Figure 2. Meters: a) electrical energy; b) water; c) natural
gas.
New administrative service can be provided after smart metering
implementation. The electrical energy supplier may become a service
provider and may include in its services contract other services
like water and natural gas, representing, from judicial point of
view, the customer in relation with the distribution companies.
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C. The External Communication Area It represents communication
infrastructure and protocol
between the smart home and the supplier, via the home
controller, although the supplier may get information about the
customer load directly from the authorized meter. Information from
a certain number of meters are gathered into a data concentrator
then sent to the central system of the supplier. The most efficient
communication is by Ethernet type infrastructure, although radio
communication is more secure.
Example of information exchanged between the customer and the
energy supplier is shown in Table I.
TABLE I. INFORMATION EXCHANGED BETWEEN THE SMART HOME AND THE
ENERGY SUPPLIER
from smart home to energy supplier
from energy supplier to smart home
instantaneous load load forecast availability to disconnect
loads
energy price monthly invoice scheduled service interruptions
daily information in the energy
field
III. THE SMART HOME ENERGY MANAGEMENT SIMULATOR
A. HEM architecture The HEM system was designed so that to
fulfill the
requirements for home-comfort of a smart home, which means that
a friendly interface should be attached for remote control, by
smart phone, pad, computer, etc. The GUI software was implemented
under PHP, thereby facilitating communication with the database,
sensors, smart meter, as well as with the user terminals using a
single platform. The GUI can be accessed from any terminal that
incorporates a web browser, and thus installing a software on all
user devices is not necessary. Another advantage of the web
platform is that, with the internet router installed, it can be
accessed from any corner of the world.
Figure 3 shows the main HEM architecture.
The decision module is a Raspberry PI simulator, which is a
programmable board that hosts the simulation and control software
under the Linux platform. This type of device is the best choice
considering the performance/price ratio, and its price is about $35
only.
The command module is a programmable logic controller (PLC),
called MicroDev D4-USB, which is a device that communicates with
the decision module (home controller) via an USB 2.0 protocol. Its
role is to implement the decisions taken by the control software.
This PLC has been designed in the Department of Electrical Power
Systems of University Politehnica of Bucharest, and its front and
back views are shown in Figure 4.
The MicroDev PLC device was manufactured for the purpose of
performing simulations in a student laboratory and not for
commercial purposes, thereby its architecture allows easy
configuration and implementation of various functions so that the
home area management concept is much easy to teach.
Decisionmodule
Interface with thecommand module
Interface to theintelligent meterWeb interface
Interface withthe database
PHP
Database Commandmodule
USBMySQL
TCP/IPHTTP
Meter(simulated)
Browser(client)
Figure 3. HEM Arhitecture.
a)
b)
Figure 4. Front (a) and back (b) views of the MicroDev D4-USB
device: 1 microcontroller; 2 - USB port; 3 digital inputs; 4
relays; 5 - relays exists; 6 - LCD port; 7 LCD; 8 - RF module; 9 -
RF module antenna.
The PLC unit have one LCD with 4 lines and 40 characters per
line, which displays information from the home controller via USB,
such as energy price or real power consumptions, 7 relay outputs
for auxiliary circuits and SSR control for high power consumption,
digital and analog inputs for sensors and other data acquisition.
It consists also of an 433MHz radio frequency (RF) module for
wireless communication with the RF controlled plugs.
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MicroDev can be used as a meter as it is capable of metering
electrical parameters, and thus for this stage no other meter was
used. However, in terms of future developments of the installation,
a smart meter will be installed mainly to test characteristics and
functionality of the future metering equipment.
MicroDev receives decisional signal from the Raspberry PI
simulator and commands switching on/off of the electrical
appliances via solid state relays.
The Pinguino IDE (Integrated Development Environment) was used
to program the MicroDev device thanks to its important advantages:
it is open source and open hardware and there are open source
compilers available for all platforms (Windows, GNU/Linux and Mac
OS X)
The database was created under MySQL because it can run on a
large number of software platforms. Furthermore it is easy to use
also due to the free application phpMyAdmin written under PHP.
The database stores various types of information, from admin
information to energy information. The information stored in the
database is accessed and processed by the decision module.
B. The hardware simulator A laboratory hardware smart home
simulator (Fig. 5) was
developed within the Laboratory of Smart Grids from the
Department of Electrical Power System, University Politehnica of
Bucharest, according to the home energy management system concept
presented above. It is an open system and it can be easily used for
teaching.
Figure 5. Laboratory hardware smart home simulator.
The components of the HEM laboratory platform are:
1. Smart meter; 2. Bipolar fuses, from left to right: S1, S2, S3
and S4; 3. MicroDev command module; 4-5. Solid State Relays (SSR)
40 A; 6-7. Regular plugs, connected to S2 and S3 through
SSR1 and SSR2;
8-10. Controllable plugs, connected to fuses S4, with control on
the addresses 11111A, 11111B, and 11111C;
11. Load, 100W, connected to plug 6; 12-14. Loads, 60W,
connected to plugs 7, 9 and 10; 15. Plug to supply the router and
the microcontroller to
fuse S1; 16. Home controller - Raspberry PI simulator; 17.
Wireless router TP-LINK - TL-WR740N.
The loads are simulated through electric lamps. The loads are
supplied either through controlled or uncontrolled plugs. Loads 11
and 12 are controlled via SSP, whereas loads 13 and 14 are
controlled via controlled plugs. A large number of loads can be
also simulated.
A controllable plug is shown in Figure 6.
Figure 6. Controllable plug.
An ID is associated to each plug. The user may choose from what
plug to supply a certain load. The plugs communicate on the 433 MHz
frequency and they continuously analyze any signal to check if the
controlled ID signal match with their ID. This type of plugs allows
remote control of the loads from the used terminal. All other
loads, controlled via SSRs are controlled by the home controlled
only based on a predefined algorithm.
C. Functions of the simulation and control software The
algorithm implemented in the home controller aims
mainly to minimize the total energy costs by optimally switching
on/off controllable loads in terms of energy price. The energy
price is assumed to vary at predefined time intervals. The interval
length was set to one hour. It is assumed that the energy price for
all interval of the next day is known in advance, thus allowing the
software to perform minimization of the total cost. The software
may also generate random price profile within a minimum and a
maximum limit so that the price may be known in advance also in a
predefined time.
The user interface with the HEM system is done via a dedicated
software developed under Android OS. The user can have access to
the loads characteristics and also can remotely switch on/off a
load appliance.
Figures 7 and 8 show print screens of a few pages as seen from a
smart phone. The GUI is similar for a pad or a PC. Using the WiFi
user terminal, loads can be added or deleted from the list, loads
can be remotely switched on/off according to the customer decision,
loads can be edited and so on.
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Figure 7. HEM GUI.
Figure 8. HEM GUI.
D. Simulations Figure 9 shows the load response to energy price
for a
boiler and an air conditioner. The loads are switched on when
the price is low, while during high price periods the loads are
switched off.
a.
b.
Figure 9. Load response in terms of energy price: a) boiler; b)
air conditioner.
The simulations were performed using some hypothetic energy
consumptions or price profile.
E. Future developments This technology and architecture for the
home energy
management concept will be implemented in a laboratory passive
house built in the yard of University Politehnica of Bucharest. The
house is provided with advanced construction technology and
heating/cooling technology. Real electrical appliances will be
added to the house and then additional functions will be added to
the already tested HEM system.
IV. CONCLUSIONS The laboratory home energy management
simulator
developed in UPB follows the actual trends of the smart grid
concept. The architecture and the algorithms implemented are based
on authors experience and not on existing legislation since no
regulation is in force regarding smart metering. The controller is
flexible for implementation of various functions and algorithms. It
is expected that smart metering to small consumers will be
available for the market in the near future.
The HEMS system may be able to record currents, voltages, power,
but also can communicate with a certified electrical meter to
record and process information related to the power quality,
including voltage dips, flicker, harmonics, etc. All the
information can be shown to the user through a friendly interface
via a smart phone of tablet.
REFERENCES [1]. ***, Siemens The company: Infrastructure &
Cities Sector Online:
http://www.siemens.com/about/pool/business/infrastructure_cities/ic_2013_q1_update_en.pdf
[2]. N. Papadopoulos, A. Meliones, D. Economou, I. Karras, I.
Liverezas, A Connected Home Platform and Development Framework for
Smart Home Control Applications, Proceedings of 7th IEEE
International Conference on Industrial Informatics, INDIN 2009,
Cardiff, Wales, UK, 23-26 June 2009.
[3]. Y. Li, Design of A Key Establishment Protocol for Smart
Home Energy Management System, Proceedings of 2013 5th
International Conference on Computational Intelligence,
Communication Systems and Networks (CICSyN), Madrid, Spain, 5-7
June 2013.
[4]. D.-M. Han and J.-H. Lim, Design and Implementation of Smart
Home Energy Management Systems based on ZigBee, IEEE Trans.
Consumer Electronics, vol. 56, issue 3, pp. 1417-1425, August
2010.
[5]. B. Becker, A. Kellerer, H. Schmeck, User Interaction
Interface for Energy Management in Smart Homes, Proceedings of 2012
IEEE PES Innovative Smart Grid Technologies (ISGT), Washington DC,
16-20 January 2012.
[6]. A.-H. Mohsenian-Rad, A. Leon-Garcia, Optimal Residential
Load Control With Price Prediction in Real-Time Electricity Pricing
Environments, IEEE Trans. Smart Grid, vol. 1, no. 2, September
2010.
[7]. Z. Chen, L. Wu, Y. Fu, Real-Time Price-Based Demand
Response Management for Residential Appliances via Stochastic
Optimization and Robust Optimization, IEEE Trans. Smart Grid, vol.
3, no. 4, December 2012.
[8]. Z. Chen, and L. Wu, Residential Appliance DR Energy
Management With Electric Privacy Protection by Online Stochastic
Optimization, IEEE Trans. Smart Grid, in press.
[9]. M. Eremia, L. Toma, Towards the intelligent cities of the
future Smart cities (in Romanian), The 7th edition of International
Conference on the Academic Days of the Academy of Technical
Sciences of Romania, Bucharest, Romania, Agir Publisher, ISSN
2066-6585, 11-12 October 2012.
[10]. ***, Intelligent metering in Romania (in Romanian), study
prepared by A.T. Kearney, Romanian National Energy Regulatory
Authority, 3 September 2012.
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