Modelling And Optimal Operation Of Smart Buildings-integrated Electricity, Gas And Heating Systems At Community Level

Technologies of renewable generations,distributed energy resources(DERs),integrated energy utilization,have been a crucial support for enhancing the quality of energy utilization and reducing the energy consumption for smart city,along with the fast development of technologies of monitoring,control and management in energy systems.As the important physical basis of smart city,integrated community energy systems(ICES)and integrated building energy systems(smart buildings in short)have been drawing wide attention all over the world.This thesis focuses on the modelling,characteristic analysis,optimal operation and coordinated control of the buildingsintegrated community energy systems.The proposed method can capitalize on the synergies from multiple energy networks of the ICES.The research objective of this thesis are energy efficiency improvement and energy consumption reduction of ICES,as well as facilitating integration of intermittent renewable generations in ICES.The main work is summarized as follows:(1)Regarding the smart buildings: The energy systems of a building can be managed as a flexible resource with the coordinated control method.Therefore,a virtual energy storage system model was developed based on heat storage characteristics of the thermal mass of a building.Then,optimal scheduling methods for one single building and aggregation of buildings were developed using multi-time scale method and model predictive control method.The proposed method can make full use of the potential of the virtual energy storage system and further contribute to the operation cost reduction and energy efficiency improvement of one building and the aggregation of buildings,while guarantee the customer temperature comfort level at the same time.(2)Regarding the ICES: The model of the energy coversion units(EC)of the ICES was developed based on the energy hub model to coordinate the optimal operations of the multiple coupling energy units of the EC.Then,an optimal hybrid power flow model was developed considering the complex constraints of the multi-vector energy networks of the ICES for its flexible operation.The optimization results of the ICES can demonstrate the improvement of the flexibility of the ICES with the proposed coordinated optimization method.Finally,an optimal scheduling method was developed for the ICES considering the interactions between the ‘Source' side and ‘Grid' side of the ICES.The proposed method is able to help the ICES reduce its operating cost and improve the energy efficiency.(3)Regarding the buildings-integrated community energy systems: Aiming to coordinate the ICES and the smart buildings in an optimal way,a multi-stage scheduling method was developed considering the interactions among the ‘Source' side,‘Grid' side and the ‘Load' side of the ICES.Then,the optimization model was converted to a mixed-integer second-order cone programming that can be efficiently solved by available software tools.Numerical results indicated that the proposed method can improve the energy efficiency and reduce the operational cost of the whole ICES system.(4)Regarding the flexibility of the ICES: A multi-level overloads relief strategy for transmission networks based on the flexibility of the ICES was proposed.When an overloads condition happens in the transmission network and further leads to emergency states of the transmission network,an appropriate operational scheme for ICES can be selected by the proposed method.Then,the ICES adjusts its operational status and schedules its ‘Source–Grid–Load' resources to respond to the overloads relief request from the transmission networks.The proposed method can improve the security of the transmission system using the flexibility of the ICES.