Research Article
The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost
@INPROCEEDINGS{10.4108/eai.2-6-2023.2334665, author={Yuheng Sha and Qian Ma and Chao Xu and Xue Tan and Jun Yan and Jing Zhang and Tingting Li}, title={The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost}, proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2023}, month={8}, keywords={"source-net-load-storage" collaboration; two-layer optimization model; quantum genetic algorithm}, doi={10.4108/eai.2-6-2023.2334665} }- Yuheng Sha
Qian Ma
Chao Xu
Xue Tan
Jun Yan
Jing Zhang
Tingting Li
Year: 2023
The Two-layer Optimization Model Design of "Source-Network-Charge-Storage" Coordination for a New Power System Considering Integrated Cost
ICIDC
EAI
DOI: 10.4108/eai.2-6-2023.2334665
Abstract
The widespread adoption of renewable energy plays a crucial role in achieving the Sustainable Development Goals of a low carbon power system. To effectively manage and control the distribution network system and promote integrated coordination, a two-layer optimization model is proposed. This model is based on the coordination of "source-network-charge-storage" within the framework of the new power system. With the lowest annual integrated cost as the upper optimization objective and the optimal load variation as the lower optimization objective, quantum genetic algorithm was used to conduct simulation analysis, and the results showed that the model proposed in this paper could not only save the integrated cost of active distribution network, but also improve the proportion of new energy consumption and improve the comprehensive benefits of distribution network system.
