A Decentralized Optimal Scheduling Method for Integrated Community Energy System

doi:10.12204/j.issn.1000-7229.2021.11.005

Abstract

Abstract:

In order to guarantee the information safety and confidential privacy of diverse energy entities among the integrated community energy system (ICES), and satisfy the multiple energy demand for electricity and heat, a decentralized optimal scheduling method is proposed in this paper. Firstly, the mathematical models of electric distribution system, natural gas distribution system and coupling system are established respectively and linearized by certain mathematical method. Secondly, the optimal scheduling model of ICES is developed with the operation cost set as the objective function. By introducing the consensus variable into the scheduling model, the optimal operation can be decoupled on the basis of the decentralized scheduling framework, which is suitable for the multiple entities integration for ICES. Finally, a typical ICES case is utilized to verify the proposed method. It is illustrated that the proposed decentralized scheduling method is able to provide the scheduling scheme same as that by centralized method, which is capable of the satisfaction for operation constraints, the realization of optimal operation and the protection of information safety and confidential privacy.

Key words: integrated community energy system (ICES), decentralized optimal scheduling, alternating direction method of multipliers (ADMM), consensus variable, multi-energy coupling

CLC Number:

TM73

LIN Wei, JIN Xiaolong, YE Rong. A Decentralized Optimal Scheduling Method for Integrated Community Energy System[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(11): 44-53.

Figures/Tables 13

Fig.1 Structure of electric distribution system

Fig.2 Piecewise linearization of modified Weymouth equation

Fig.3 Structure of two types of coupling systems

Fig.4 ICES decoupling by introducing the consensus variables

Fig.5 Flowchart of decentralized optimal scheduling

Fig.6 Structure of the ICES

Table 1 Electricity and heat load of coupling systemskW

Fig.7 Optimal scheduling scheme of coupling systems

Fig.8 Voltage magnitude of electric distribution system under different optimal scheduling schemes

Fig.9 Node pressure of natural gas distribution system under different optimal scheduling schemes

Table 2 Optimal scheduling scheme of EH1 under different partition coefficient for time period 17

Fig.10 Convergence process of coupling variables of EH1 for time period 17

Fig.11 Convergence process of residual of ICES for time period 17

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