smart heating and cooling systems for energy efficient...
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Problem
guiding questions
Can distributed and decentralized, scalable and easy-implement-ing control algorithms be designed?
What are the system- wide objectives and constraints based on practical requirements?
What models should be used for heating and cooling systems and building thermal dynamics?
The problem considered in this project is generally formulated as a steady-state optimization problem: Under real-time outdoor temperature and indoor heat gain, can a control scheme for the heating and cooling system be designed in a distributed way, so that the temperature in each zone in the building is maintained in its comfort range, and the energy consumption of the building is minimized, subject to related operating constraints?
As one of the primary consumers in the United States, buildings are respon-sible for about 30% of energy consumption, 71% of electricity consumption, while resulting in 33% of CO2 emissions. Roughly speaking, heating and cooling systems account for half of a building’s energy use. It is therefore necessary to make these systems smarter to increase both energy efficiency and environmental sustainability. Two main heating and cooling systems are used within modern buildings: the Air Handling Unit and Variable Air Volume, which is dominant in com-mercial buildings, and the Ground Source Heat Pump which is frequently applied in net-zero buildings. Generally speaking, most research uses model predictive control for the control and optimization of these systems, which is usually implemented in a centralized and complicated way. As such, opportunity exists to develop distributed and decentralized, scalable, and easily-implemented control algorithms.
smart Heating and Cooling systems for energy efficient Buildings
PRoJeCt desCRiPtion
Provide a framework for high-perfor-mance and high-confi dence tem-perature control of energy eff icientbuildings.
Develop distributed algorithms and architectures to address sustain-ability issues in large-scale sociotechnical systems.
Contribute to the fi eld of optimal control in control engineering.
iMPACt
This project will facilitate the development of distributed algorithms and architectures to achieve high-performance and high-confi dence control and management of energy eff icient buildings. As a further extension, one can study the infl uence of buildings with the proposed smart heating and cooling systems to the power grid. The fundamental progress made in this project can also be used to address sustainability issues in other large-scale sociotechnical systems, such as air and urban transportation systems, water and gas distribution systems, and power systems. The theoretical part of this research will also contribute to the fi eld of control engineering in steady-state optimiza-tion and optimization-based control, which complements the framework of optimal control.
This project aims to develop a novel control framework for temperature regulation in modern buildings. Un-der our proposed control schemes, each controllable component in a building will properly adapt its behavior so that preset system-wide objectives are achieved under normal and abnormal operating conditions.
ContACt
20 Sumner RoadCambridge, MA 02138tel. 617-495-8807fax. 617-496-4408 email: [email protected]
30
35
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Tem
pera
ture
(c−
degre
e)
Outdoor temperature
22 24
Q
1
Q2
Q3
Q4
0.1
0.2
0.3
0.4
0.5
Flo
w r
ate
(kg/s
)
Flow rates appm
1
m1
appm2
m2
appm3
m3
appm4
m4
appsumm
summ
0 2 4 6 8−2
0
2
appzeta1
zeta1
appzeta2
zeta2
appzeta3
zeta3
appzeta4
zeta4
applam
lam
22 24 0 2 4 6 22 24
22 24
23
24
25
Tem
pera
ture
(c−
degre
e)
appT
T4
Tset
30
35
40
Tem
pera
ture
(c−
degre
e)
Outdoor temperature
22 24
Q1
Q2
Q3
Q4
0.1
0.2
0.3
0.4
0.5
Flo
w r
ate
(kg/s
)
Flow ratesappm
1
m1
appm2
m2
appm3
m3
appm4
m4
appsumm
summ
0 2 4 6 8−2
0
2
appzeta1
zeta1
appzeta2
zeta2
appzeta3
zeta3
appzeta4
zeta4
applam
lam
22 24 0 2 4 6 22 24
22 24
23
24
25
Tem
pera
ture
(c−
degre
e)
appT
T4
Tset