We present our Smart Home Framework (SHF) which simplifies the modelling, prototyping and simulation of smart infrastructure (i.e., smart home and smart communities). It provides the buildings blocks (e.g., home appliances) that can be extended and assembled together to build a smart infrastructure model to which appropriate AI techniques can be applied. This approach enables rapid modelling where new research initiatives can build on existing work

Alam, Muddasser

Alan, Alper

Ramchurn, Sarvapali D.

Rogers, Alex

English

Southampton (e-Prints Soton)

Poster Abstract: Towards a Smart Home FrameworkMuddasser Alam, Alper T. Alan, Alex Rogers, and Sarvapali D. RamchurnAgents, Interaction and Complexity Research Group, University of Southampton, UK.{moody,ata1g11,acr,sdr}@ecs.soton.ac.ukABSTRACTWe present our Smart Home Framework (SHF) which sim-plies the modelling, prototyping and simulation of smartinfrastructure (i.e., smart home and smart communities).It provides the buildings blocks (e.g., home appliances) thatcan be extended and assembled together to build a smart in-frastructure model to which appropriate AI techniques canbe applied. This approach enables rapid modelling wherenew research initiatives can build on existing work.Categories and Subject DescriptorsD.2.13 [Reusable Software]: Reuse models, libraries1. INTRODUCTIONSmart infrastructure such as smart homes, smart buildingsand smart communities are considered to be an integral partof the transition to a low-carbon economy. This infrastruc-tures is intended to embody many technologies such as smartmeters, energy-ecient appliances, renewable-energy gener-ation units, microstorage and electric vehicles. Hence, anumber of research initiatives have focused on the role andinterplay of these technologies in smart infrastructure. Themajority of work in this line involves similar activities suchas building a model of smart building, incorporating intel-ligence and simulation [3, p. 132], which have resulted ina number of shared and reusable tools, particularly, a largenumber of simulation software, with notable examples ofGridLab-D, Open-DSS, Simulink-SmartGrid and MapleSim.However, other activities have not received their due atten-tion, especially in the modelling phase where there is anabsence of shared tools and resources that can help createmodels of smart infrastructure. We believe that the devel-opment of such modelling resources will enable new researchinitiatives to build upon existing work, rather than startingfrom scratch. As a step towards this vision, we present asmart home framework (SHF): a software framework thatprovides the building blocks (e.g. appliances, generators andstorage) that can be assembled together to build generalPermission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies arenot made or distributed for proﬁt or commercial advantage and that copiesbear this notice and the full citation on the ﬁrst page. To copy otherwise, torepublish, to post on servers or to redistribute to lists, requires prior speciﬁcpermission and/or a fee.Buildsys’13, November 13, 2013, Rome, Italy.Copyright 2013 ACM 978-1-4503-1170-0 ...$15.00.models of smart homes and communities. These compo-nents can be extended to construct specialised models tomeet the specic needs of any particular project. This ap-proach enables rapid, bottom-up modelling of smart homesand communities where these components and models canbe shared and reused. We envision that such reuse will even-tually lead to standardised models (e.g., a standard modelof a washing machine or a smart home) to be shared (e.g.,via online repositories) and reused across the community. Inaddition, the SHF comes with a software toolkit that helpsin optimisation and visualisation of data. Finally, the SHFis aimed at enabling collaboration between researchers andis available as a free, open-source framework to all.2. RELATED WORKThe core purpose of our SHF is to enable researchers toquickly build the models of smart homes and communitiesby assembling general components. An example is to build asmart home by putting together components such as a solarpanel, some appliances, an electric battery and an electricvehicle or any other customised component. We note thatthe majority of simulation software come with parameterisedmodels of common components which can be customised us-ing the parameters values. For example, GridLab-D andMapleSim allow users to specify parameters for an appli-ance (e.g., energy-baseline (kWh) or motor-power (kW) fora washing machine). However, such models are tightly in-tegrated into the simulator and there is little exibility ofextending them into new models. For example, it can bedicult to extend an existing washing machine model intoone that has a built-in dryer. In contrast, the SHF providesmodels that can be easily extended into specialised mod-els. This focus on modelling, rather than simulation, is thecore dierence between the SHF and simulation software andtherefore, the SHF should be considered as a modelling tooland not as a replacement of the simulation software. Indeed,there may be cases where both can be used together. An ex-ample is where the SHF-based smart home models can beintegrated with a simulator for very large-scale simulation.3. SMART HOME FRAMEWORKOur SHF architecture is based on a bottom-up, extendibleand plug-in methodology. The basic components are denedin a exible hierarchy (e.g., SolarPanel implements IRenew-ableGenerator extends IOnSiteGenrator extends IGenera-tor, see [4] for UML diagrams) making it easier to includenew code. The plug-in approach is useful to replace the ex-isting code, for example, a new optimiser can be plugged-into replace the default optimiser in the toolkit.3.1 Building a Smart Home ModelThe SHF provides a rich set of interfaces, abstract and im-plemented classes as we summarise now. Detailed UML di-agrams, tutorials and example code are available online [4].Generation: The SHF provides classes to model (i) onsitegeneration and (ii) the electricity grid. Onsite generationinclude renewable and non-renewable (e.g., combined heat-power) generation. An energy source has certain attributesand operations depending on its type. For instance, theonsite non-renewable have an operational cost (monetaryand/or carbon footprint) while the renewable have uncer-tain power outputs. The generation module contains imple-mented classes for a number of energy sources that can bereadily instantiated. A new type of generator can be addedby extending the appropriate interface (e.g., IRenewableEn-ergySource or INonRenewableEnergySource). Furthermore,this module has tari classes (e.g., standard and o-peak)that can connect a smart home to the grid. Additionalclasses exist to include more sophisticated types of taris.Storage: The SHF contains classes to model (i) onsite stor-age (e.g., electric batteries at homes) and (ii) mobile stor-age. Each storage class has dierent attributes (e.g., onsitestorage is assumed to be available all the time). The SHFprovides basic models of electric batteries in terms of theircapacity, charging and discharging rates and eciency whilemore sophisticated models can be created by extension.Load: Load requirements are described in terms of appli-ances and their usage (i.e., load events). Common appli-ances (e.g., oven, fridge) are already implemented and moresophisticated models can be added. A load event describesa single use of an appliance and has a certain type and at-tributes. The supported load event types are: (i) deferrableand non-deferrable (ii) interruptible and non interruptible(iii) critical (iv) baseload (v) or combinations (e.g. a de-ferrable, interruptible and load event). It also supports sim-ple loads to model loads in an appliance-independent way.Miscellaneous: The SHF also supports HVAC (heating,ventilation, air conditioning) systems and electric vehicles.3.2 Building a Smart CommunityThe SHF can be used to create multiple smart homes thatcollectively can represent a smart community. This com-munity can be o-grid or connected to the grid. When acommunity model is ready it can be optimised or simulated(either using the SHF optimisation package or a third-partysimulator) as a whole [1] or on an individual homes basis [2].3.3 Additional ToolkitsThe SHF comes with a toolkit that contains (i) an optimisa-tion and (ii) a visualisation package. The optimisation pack-age includes a default optimiser (i.e., IBM CPLEX, availablefree of cost to academia) that supports convex optimisationand for more sophisticated or non-convex optimisation, athird-party optimiser can be plugged-in to replace it. Thevisualisation package is essentially a customised wrapperaround the JFreeChart library that can be used to visualisedata. For example, it can be used to quickly plot the loadevents or the battery charging in a smart home. Figure 1shows an example where a smart home model is built andoptimised using the default appliances/devices and CPLEXoptimiser and results are plotted via the visual toolkit. NoFigure 1: Graphs (battery, EV, loads, preferences, gen-eration, HVAC) show optimal use of resources in a home.additional code was needed outside the framework.4. APPLIEDEXAMPLESANDRESOURCESWe have utilised the SHF to enables smart homes to ex-change energy. For example, using the SHF we created ano-grid community where each home has a microgenerationunit, an electric battery and some load. We then showedthat the cooperative exchange of energy in such communi-ties can reduce the overall battery usage by 65% [1]. Morerecently, we presented a negotiation protocol to facilitate de-centralised energy exchange between self-interested agentsto reduce their battery usage [2]. In addition to this work,we believe that the SHF can be especially useful for researchprojects focused on exploring demand response, uncertaintyin renewable generation, optimal energy usage for cost andcarbon emissions reduction, electric vehicle charging, coali-tion formation for group taris and intelligent heating.The SHF website [4] has the tutorials and example codeto help get started with the SHF. We also provide exam-ples to build a model of (i) a smart home and (ii) a smartcommunity using the SHF and its toolkit. The SHF code ishosted on GitHub and is freely available under GP Licence.5. FUTURE WORKAt present, the SHF provides minimal support to model util-ities other than electricity (e.g., gas and water). Our futurework will provide modelling capacity for these utilities.6. REFERENCES[1] M. Alam, S. D. Ramchurn, and A. Rogers. Cooperativeenergy exchange for the ecient use of energy andresources in remote communities. In InternationalConference on Autonomous Agents and MultiagentSystems, Saint Paul, Minnesota, USA, 6-10 May 2013.[2] M. Alam, A. Rogers, and S. D. Ramchurn.Interdependent multi-issue negotiation for energyexchange in remote communities. In Proceedings ofAAAI, Washington, USA, 14-18 July 2013.[3] J. C. Augusto and C. D. Nugent. Designing smarthomes: the role of articial intelligence, volume 4008.Springer-Verlag NY Inc., 2006.[4] Smart Home Framework. Available online at.www.smarthomeframework.org.

Cooperative energy exchange for the ecient use of energy and resources in remote communities.

Designing smart homes: the role of arti intelligence, volume 4008.

Interdependent multi-issue negotiation for energy exchange in remote communities.

Towards a smart home framework

Muddasser Alam

Alper T. Alan

Alex Rogers

Sarvapali D. Ramchurn

Crossref

Poster Abstract: Towards a Smart Home Framework
Muddasser Alam, Alper T. Alan, Alex Rogers, and Sarvapali D. Ramchurn
Agents, Interaction and Complexity Research Group, University of Southampton, UK.
{moody,ata1g11,acr,sdr}@ecs.soton.ac.uk
ABSTRACT
We present our Smart Home Framework (SHF) which sim-
plifies the modelling, prototyping and simulation of smart
infrastructure (i.e., smart home and smart communities).
It provides the buildings blocks (e.g., home appliances) that
can be extended and assembled together to build a smart in-
frastructure model to which appropriate AI techniques can
be applied. This approach enables rapid modelling where
new research initiatives can build on existing work.
Categories and Subject Descriptors
D.2.13 [Reusable Software]: Reuse models, libraries
1. INTRODUCTION
Smart infrastructure such as smart homes, smart buildings
and smart communities are considered to be an integral part
of the transition to a low-carbon economy. This infrastruc-
tures is intended to embody many technologies such as smart
meters, energy-efficient appliances, renewable-energy gener-
ation units, microstorage and electric vehicles. Hence, a
number of research initiatives have focused on the role and
interplay of these technologies in smart infrastructure. The
majority of work in this line involves similar activities such
as building a model of smart building, incorporating intel-
ligence and simulation [3, p. 132], which have resulted in
a number of shared and reusable tools, particularly, a large
number of simulation software, with notable examples of
GridLab-D, Open-DSS, Simulink-SmartGrid and MapleSim.
However, other activities have not received their due atten-
tion, especially in the modelling phase where there is an
absence of shared tools and resources that can help create
models of smart infrastructure. We believe that the devel-
opment of such modelling resources will enable new research
initiatives to build upon existing work, rather than starting
from scratch. As a step towards this vision, we present a
smart home framework (SHF): a software framework that
provides the building blocks (e.g. appliances, generators and
storage) that can be assembled together to build general
Permission to make digital or hard copies of all or part of this work for
personal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. To copy otherwise, to
republish, to post on servers or to redistribute to lists, requires prior specific
permission and/or a fee.
Buildsys’13, November 13, 2013, Rome, Italy.
Copyright 2013 ACM 978-1-4503-1170-0 ...$15.00.
models of smart homes and communities. These compo-
nents can be extended to construct specialised models to
meet the specific needs of any particular project. This ap-
proach enables rapid, bottom-up modelling of smart homes
and communities where these components and models can
be shared and reused. We envision that such reuse will even-
tually lead to standardised models (e.g., a standard model
of a washing machine or a smart home) to be shared (e.g.,
via online repositories) and reused across the community. In
addition, the SHF comes with a software toolkit that helps
in optimisation and visualisation of data. Finally, the SHF
is aimed at enabling collaboration between researchers and
is available as a free, open-source framework to all.
2. RELATED WORK
The core purpose of our SHF is to enable researchers to
quickly build the models of smart homes and communities
by assembling general components. An example is to build a
smart home by putting together components such as a solar
panel, some appliances, an electric battery and an electric
vehicle or any other customised component. We note that
the majority of simulation software come with parameterised
models of common components which can be customised us-
ing the parameters values. For example, GridLab-D and
MapleSim allow users to specify parameters for an appli-
ance (e.g., energy-baseline (kWh) or motor-power (kW) for
a washing machine). However, such models are tightly in-
tegrated into the simulator and there is little flexibility of
extending them into new models. For example, it can be
difficult to extend an existing washing machine model into
one that has a built-in dryer. In contrast, the SHF provides
models that can be easily extended into specialised mod-
els. This focus on modelling, rather than simulation, is the
core difference between the SHF and simulation software and
therefore, the SHF should be considered as a modelling tool
and not as a replacement of the simulation software. Indeed,
there may be cases where both can be used together. An ex-
ample is where the SHF-based smart home models can be
integrated with a simulator for very large-scale simulation.
3. SMART HOME FRAMEWORK
Our SHF architecture is based on a bottom-up, extendible
and plug-in methodology. The basic components are defined
in a flexible hierarchy (e.g., SolarPanel implements IRenew-
ableGenerator extends IOnSiteGenrator extends IGenera-
tor, see [4] for UML diagrams) making it easier to include
new code. The plug-in approach is useful to replace the ex-
isting code, for example, a new optimiser can be plugged-in
to replace the default optimiser in the toolkit.
3.1 Building a Smart Home Model
The SHF provides a rich set of interfaces, abstract and im-
plemented classes as we summarise now. Detailed UML di-
agrams, tutorials and example code are available online [4].
Generation: The SHF provides classes to model (i) onsite
generation and (ii) the electricity grid. Onsite generation
include renewable and non-renewable (e.g., combined heat-
power) generation. An energy source has certain attributes
and operations depending on its type. For instance, the
onsite non-renewable have an operational cost (monetary
and/or carbon footprint) while the renewable have uncer-
tain power outputs. The generation module contains imple-
mented classes for a number of energy sources that can be
readily instantiated. A new type of generator can be added
by extending the appropriate interface (e.g., IRenewableEn-
ergySource or INonRenewableEnergySource). Furthermore,
this module has tariff classes (e.g., standard and off-peak)
that can connect a smart home to the grid. Additional
classes exist to include more sophisticated types of tariffs.
Storage: The SHF contains classes to model (i) onsite stor-
age (e.g., electric batteries at homes) and (ii) mobile stor-
age. Each storage class has different attributes (e.g., onsite
storage is assumed to be available all the time). The SHF
provides basic models of electric batteries in terms of their
capacity, charging and discharging rates and efficiency while
more sophisticated models can be created by extension.
Load: Load requirements are described in terms of appli-
ances and their usage (i.e., load events). Common appli-
ances (e.g., oven, fridge) are already implemented and more
sophisticated models can be added. A load event describes
a single use of an appliance and has a certain type and at-
tributes. The supported load event types are: (i) deferrable
and non-deferrable (ii) interruptible and non interruptible
(iii) critical (iv) baseload (v) or combinations (e.g. a de-
ferrable, interruptible and load event). It also supports sim-
ple loads to model loads in an appliance-independent way.
Miscellaneous: The SHF also supports HVAC (heating,
ventilation, air conditioning) systems and electric vehicles.
3.2 Building a Smart Community
The SHF can be used to create multiple smart homes that
collectively can represent a smart community. This com-
munity can be off-grid or connected to the grid. When a
community model is ready it can be optimised or simulated
(either using the SHF optimisation package or a third-party
simulator) as a whole [1] or on an individual homes basis [2].
3.3 Additional Toolkits
The SHF comes with a toolkit that contains (i) an optimisa-
tion and (ii) a visualisation package. The optimisation pack-
age includes a default optimiser (i.e., IBM CPLEX, available
free of cost to academia) that supports convex optimisation
and for more sophisticated or non-convex optimisation, a
third-party optimiser can be plugged-in to replace it. The
visualisation package is essentially a customised wrapper
around the JFreeChart library that can be used to visualise
data. For example, it can be used to quickly plot the load
events or the battery charging in a smart home. Figure 1
shows an example where a smart home model is built and
optimised using the default appliances/devices and CPLEX
optimiser and results are plotted via the visual toolkit. No
Figure 1: Graphs (battery, EV, loads, preferences, gen-
eration, HVAC) show optimal use of resources in a home.
additional code was needed outside the framework.
4. APPLIED EXAMPLES AND RESOURCES
We have utilised the SHF to enables smart homes to ex-
change energy. For example, using the SHF we created an
off-grid community where each home has a microgeneration
unit, an electric battery and some load. We then showed
that the cooperative exchange of energy in such communi-
ties can reduce the overall battery usage by 65% [1]. More
recently, we presented a negotiation protocol to facilitate de-
centralised energy exchange between self-interested agents
to reduce their battery usage [2]. In addition to this work,
we believe that the SHF can be especially useful for research
projects focused on exploring demand response, uncertainty
in renewable generation, optimal energy usage for cost and
carbon emissions reduction, electric vehicle charging, coali-
tion formation for group tariffs and intelligent heating.
The SHF website [4] has the tutorials and example code
to help get started with the SHF. We also provide exam-
ples to build a model of (i) a smart home and (ii) a smart
community using the SHF and its toolkit. The SHF code is
hosted on GitHub and is freely available under GP Licence.
5. FUTURE WORK
At present, the SHF provides minimal support to model util-
ities other than electricity (e.g., gas and water). Our future
work will provide modelling capacity for these utilities.
6. REFERENCES
[1] M. Alam, S. D. Ramchurn, and A. Rogers. Cooperative
energy exchange for the efficient use of energy and
resources in remote communities. In International
Conference on Autonomous Agents and Multiagent
Systems, Saint Paul, Minnesota, USA, 6-10 May 2013.
[2] M. Alam, A. Rogers, and S. D. Ramchurn.
Interdependent multi-issue negotiation for energy
exchange in remote communities. In Proceedings of
AAAI, Washington, USA, 14-18 July 2013.
[3] J. C. Augusto and C. D. Nugent. Designing smart
homes: the role of artificial intelligence, volume 4008.
Springer-Verlag NY Inc., 2006.
[4] Smart Home Framework. Available online at.
www.smarthomeframework.org.


Towards a Smart Home Framework

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Towards a smart home framework

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