Over the decades, energy issues have been getting more important.
In the U.S., 48% of energy consumption is from buildings, of
which 25% is associated with heating and cooling at an annual
cost of $40 billion. Furthermore, on an annual basis, buildings
in the United States consume 73% of its electricity.
With rising energy costs, the need to design and integrate scalable
energy consumption reduction strategies in buildings calls
for novel approaches. There are numerous challenges associated
with energy resources such as supply and depletion of energy resources
and heavy environmental impacts. The rise in energy
consumption in buildings can be attributed to several factors such
as enhancement of building services and comfort levels, through heating, cooling and lighting needs and increased time
spent indoors.
Collaboration
To effectively address the above challenges, we estabilish an active collaborative environment with the sustainable energy project under the leadership of Prof. Burcin Becerik-Gerber and her collaborators.
Specifically, we are building smart energy systems based on multiagent coordination and collaborating with researchers from different departments including Computer Science (Teamcore Research Group), Civil and Environmental Engineering (Innovation in Integrated Informatics LAB) and Psychology departments at USC and School of Information Systems at Singapore Management University.
Multiagent Systems to Conserve Energy
Recent developments in multiagent systems are opening up
the possibility of deploying multiagent teams to achieve complex goals in such energy domains that inherently have uncertain and
dynamic environments with limited resources. To model and optimize buildings' energy consumption, building
agents, facility managers and human occupants are demanding robust, intelligent and
adaptable ambient planning techniques. To realize both tangible benefits
such as energy and operation savings, value property, reduction
in occupant complaints as well as the intangible benefits such as
occupant comfort and satisfaction, designers must develop energy
adaptive capabilities within the building environmental control systems.
This project focuses on a novel application to be deployed
at Ralph & Goldy Lewis Hall (RGL) at the University of Southern
California as a practical research testbed to optimize multiple
competing objectives: i) amount of energy used in the buildings; ii)
occupants' comfort level; and iii) practical usage considerations. This work
provides three key contributions. First, we explicitly consider uncertainty while reasoning
about coordination in a distributed manner. In particular, we uses a novel algorithm for generating optimal MDP (Markov Decision Problem)
policies that explicitly consider multiple criteria optimization (energy
and personal comfort) as well as uncertainty over occupant
preferences when negotiating energy reduction
Second, human
behaviors and their occupancy preferences are incorporated into
planning and modeled as part of the system. As as result, our system
is capable of generating an optimal plan not only for building usage
but also for occupants. Third, the influence of various control
strategies for multiagent teams is evaluated on an existing university
building as the practical research testbed with actual energy
consumption data in the validated simulation testbed. Since the simulation environment
is based on actual data, this result can be easily deployed into
the real-world. For future
work, we consider opportunities for direct occupant participation
and incentivization via handheld devices and deploy our system to
the real-world.
Research Testbed Building: RGL at USC
Validated Simulation Testbed
Human Subject Study on Energy Conservation
We also design and conduct a validation experiment on a group of human occupants in commercial buildings via a set of agents in our system: room and proxy agents.
There is a dedicated room agent per office
and conference room, in charge of reducing energy consumption
in that room. It can access sensors to retrieve room information
and energy use and impact the operation of actuators. A proxy
agent is on an individual occupant's hand-held device and it
has the corresponding occupant's models. Proxy agents communicate
on behalf of an occupant to the room agent based on their
adjustable autonomy - when to interrupt a user and when to act
autonomously. Room agents may directly communicate with occupants
without proxy agents, and different room agents coordinate
among themselves as well as with proxy agents.
We conduct this investigation: i) to verify if our system can lead to
changes in occupants' behaviors and to reduce energy consumption in commercial buildings,
ii) to validate the parameter values used during the negotiation process such as the acceptance/compliance rate for the suggestion
and iii) to understand what types of feedback are most effective to affect occupants' energy-related decisions.
Jun-young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Farrokh Jazizadeh, Geoffrey Kavulya, Laura Klein, Burcin Becerik-Gerber, Timothy Hayes, and Wendy Wood,
"SAVES: A Sustainable Multiagent Application to Conserve Building Energy Considering Occupants," in Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June, 2012 (Innovative Applications Track)
