Smart coordination of virtual energy storage systems for distribution network management

With an increasing penetration of solar photovoltaic (PV) resources in distribution networks, voltage regulation becomes an important issue. In addition, due to the growth in air conditioning load in summer days, overloading management draws researchers’ attentions as well. This paper proposes a two...

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Bibliographic Details
Main Authors: Wang, Dongxiao, Lai, Chun Sing, Li, Xuecong, Wu, Runji, Gao, Xiaodan, Lai, Loi Lei, Wu, Xueqing, Xu, Yi, Wen, Yonggang, Vaccaro, Alfredo
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/159866
Description
Summary:With an increasing penetration of solar photovoltaic (PV) resources in distribution networks, voltage regulation becomes an important issue. In addition, due to the growth in air conditioning load in summer days, overloading management draws researchers’ attentions as well. This paper proposes a two-level consensus-driven distributed control strategy to coordinate virtual energy storage systems (VESSs), i.e. residential households with air conditioners, to avoid the violation of voltage and loading which are regarded as part of the main power quality issues in future distribution network. In the lower level, the precise modelling of VESSs is firstly built, then VESSs are aggregated via aggregators for better participating in the control scheme. Once the violation occurs, a consensus-driven control scheme in the upper level will be initiated to eliminate the error. Required active power adjustment is shared among VESSs aggregators via sparse communication networks, without compromising end users’ thermal comfort. Changes in the dynamic communication network topology are investigated to demonstrate their impacts on system performance. Simulation results based on a practical system in New South Wales, Australia is used to demonstrate the proposed control scheme, which can effectively manage voltage and loading in a distribution network with scalability and robustness.