posted on 2025-05-11, 12:51authored byDongxiao Wang
This thesis focuses on the smart control of energy storage systems with high intermittent renewables in active distribution network to deal with voltage and overloading issues. Firstly, battery energy storage systems are studied to cope with overloading issue in distribution network with high penetration of renewable energy. The proposed control framework has covered a variety of innovative aspects compared with previous work, including the study of communication network topology change, the incorporation of battery depth of discharge rate into consensus protocol to fairly shed loading amount, sensitivity scalar study and leader selection research. After that, a virtual energy storage system is employed to provide ancillary services in active distribution network. Specifically, overloading control and voltage regulation is studied. The demand response strategy is designed to utilize virtual devices that will transform demand response into a dispatchable capacity resource. The distributed control algorithms are studied as well to handle large scale involved distributed resources and enable plug-and-play functionality. At last, a system model framework for the distributed renewable energy sources, demand response features and multi-objective optimization is established for all balancing and network service requirements in the microgrid. It has the benefits of increasing the reliability of power system operation, improving energy efficiency, and enabling increased consumer participation in power system operation. The proposed control schemes have been tested on a number of benchmark test systems. Their effectiveness and feasibility are verified by simulation result.
History
Year awarded
2017.0
Thesis category
Doctoral Degree
Degree
Doctor of Philosophy (PhD)
Supervisors
Meng, Ke (University of Sydney); Chen, Guo (University of Newcastle); Dong, Zhaoyang (University of Newcastle); Coates, Colin (University of Newcastle)
Language
en, English
College/Research Centre
Faculty of Engineering and Built Environment
School
School of Electrical Engineering and Computer Science