TY - JOUR
T1 - A collaborative operation decision model for distributed building clusters
AU - Dai, Rui
AU - Hu, Mengqi
AU - Yang, Dong
AU - Chen, Yang
N1 - Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - In the context of smart grid, the building can freely connect with other buildings to form clusters which are termed as building clusters to share energy. However, less study is conducted to develop optimal operation strategy for building clusters and evaluate the performance of building clusters in terms of different measures under different operation modes. Therefore, this research proposes a collaborative decision model to study the energy exchange among building clusters where the buildings share a combined cooling, heating and power system, thermal storage, and battery, and each building aims to minimize its energy cost, carbon emission or primary energy consumption. A collaborative decision framework is proposed to obtain Pareto operation decisions for the building clusters. We compare the performance of the collaborative strategy with the non-cooperative strategy where no energy sharing among the buildings. It is demonstrated that the collaborative strategy can significantly reduce energy cost, carbon emission and primary energy consumption under both grid connected and disconnected operation modes. The collaborative strategy under dynamic pricing plan is more cost effective than the strategy under flat pricing plan, which indicates that the collaborative strategy can motive buildings to more efficiently utilize the shared energy under dynamic pricing plan.
AB - In the context of smart grid, the building can freely connect with other buildings to form clusters which are termed as building clusters to share energy. However, less study is conducted to develop optimal operation strategy for building clusters and evaluate the performance of building clusters in terms of different measures under different operation modes. Therefore, this research proposes a collaborative decision model to study the energy exchange among building clusters where the buildings share a combined cooling, heating and power system, thermal storage, and battery, and each building aims to minimize its energy cost, carbon emission or primary energy consumption. A collaborative decision framework is proposed to obtain Pareto operation decisions for the building clusters. We compare the performance of the collaborative strategy with the non-cooperative strategy where no energy sharing among the buildings. It is demonstrated that the collaborative strategy can significantly reduce energy cost, carbon emission and primary energy consumption under both grid connected and disconnected operation modes. The collaborative strategy under dynamic pricing plan is more cost effective than the strategy under flat pricing plan, which indicates that the collaborative strategy can motive buildings to more efficiently utilize the shared energy under dynamic pricing plan.
KW - Collaborative decision
KW - Combined cooling heating and power system
KW - Multi-objective optimization
KW - Pareto optimality
KW - Smart buildings
UR - http://www.scopus.com/inward/record.url?scp=84928416750&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2015.03.042
DO - 10.1016/j.energy.2015.03.042
M3 - Article
AN - SCOPUS:84928416750
SN - 0360-5442
VL - 84
SP - 759
EP - 773
JO - Energy
JF - Energy
ER -