Research on Operation Optimization of "Optical Storage Charging and Swap" Power Station Based on Robust Optimization Algorithm

• Published in: IEEE International Conference on Power and Renewable Energy (Online) pp. 852 - 858
• Main Authors: Shi, Shanshan, Zhang, Yu, Wei, Xinchi, Zhang, Kaiyu, Li, Puhao, Li, Wenzhu, Peng, Daogang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.09.2021
• Subjects: Costs; data-driven; Distribution networks; Electric vehicles; multi-source energy; optical storage and charging; Prediction algorithms; Prediction theory; Predictive models; robust optimization; User experience
• ISSN: 2768-0525
• DOI: 10.1109/ICPRE52634.2021.9635429

Aiming at problems such as poor user experience of electric vehicles, high charging costs, and excessive supply pressure on the distribution network, this paper establishes a robust optimization model that takes into account the random characteristics of uncertain variables, power station operating costs, and environmental protection. The model is based on a set of uncertainties constrained by classification probability and opportunity to achieve an accurate description of the operation of the power station. At the same time, through the reasonable setting of the load reserve coefficient and the number of uncertain variables, the robust system is not subject to external changes and continues to maintain a stable state. Finally, the dual theory is used to decouple the robust model, and the relaxation algorithm is used to solve iteratively. Taking an optical storage charging and swapping station as an example, the correctness of the proposed model and method is verified.