Distributed model predictive control strategies for coordination of electro‐thermal devices in a cooperative energy management concept

2019 ◽  
Vol 41 (1) ◽  
pp. 170-189 ◽  
Author(s):  
Ivelina Stoyanova ◽  
Erdem Gümrükcü ◽  
Gustavo Aragon ◽  
Diego I. Hidalgo‐Rodriguez ◽  
Antonello Monti ◽  
...  
2018 ◽  
Vol 12 (18) ◽  
pp. 2507-2515
Author(s):  
Wicak Ananduta ◽  
Julian Barreiro-Gomez ◽  
Carlos Ocampo-Martinez ◽  
Nicanor Quijano

2019 ◽  
Vol 41 (1) ◽  
pp. 146-169 ◽  
Author(s):  
Wicak Ananduta ◽  
José María Maestre ◽  
Carlos Ocampo‐Martinez ◽  
Hideaki Ishii

2014 ◽  
Vol 24 (6) ◽  
pp. 740-749 ◽  
Author(s):  
H.F. Scherer ◽  
M. Pasamontes ◽  
J.L. Guzmán ◽  
J.D. Álvarez ◽  
E. Camponogara ◽  
...  

2019 ◽  
Vol 15 (7) ◽  
pp. 4086-4098 ◽  
Author(s):  
Ahmed Saad ◽  
Tarek Youssef ◽  
Ahmed T. Elsayed ◽  
Amr Amin ◽  
Omar Hanafy Abdalla ◽  
...  

Author(s):  
Fenglin Zhou ◽  
Yaoyu Li ◽  
Wenyi Wang

Human activities in buildings are connected by various transportation measures. For the emerging Smart and Connected Communities (S&CC), it is possible to synergize the energy management of smart buildings with the vehicle operation/travel information available from transportation infrastructure, e.g. the intelligent transportation systems (ITS). Such information enables the prediction of upcoming building occupancy and upcoming charging load of electrified vehicles. This paper presents a predictive energy management strategy for smart community with a distributed model predictive control framework, in which the upcoming building occupancy and charging load are assumed to be predictable to certain extent based on the ITS information. An illustrative example of smart community is used for simulation study based on a Modelica simulation model, in which a chilled-water plant sustains the ventilation and air conditioning of three buildings, and each building is assumed to host a number of charging stations. Simulation study is performed to validate the proposed strategy.


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