Research on optimal dispatching technology for virtual power plant  considering demand response

Xiaojun Wang; Hui Shen; Huifeng Dong; Zhe Wu; Xuqiang Yang; Shuo Wang; Shuyu Wang

doi:10.1117/12.3029347

22 May 2024 Research on optimal dispatching technology for virtual power plant considering demand response

Xiaojun Wang, Hui Shen, Huifeng Dong, Zhe Wu, Xuqiang Yang, Shuo Wang, Shuyu Wang

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 1317630 (2024) https://doi.org/10.1117/12.3029347
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

To promote energy absorption capacity and the efficiency of virtual power plant (VPP) operation and consider the complex and uncertain characteristics of the VPP system, a three-stage optimal dispatch model is proposed for VPPs. On this basis, a VPP three-stage bidding model is established that simultaneously takes into account electric vehicles (EVs) and demand response. The established model has the characteristics of high-dimensional nonlinearity. The proposed scheme has the effect of peak shaving and valley filling, and can enhance the consumption of renewable energy. Eventually, the effectiveness of the constructed model is verified through the simulation model. The simulation results confirm that the proposed optimization scheduling model has the advantages of efficiency and accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaojun Wang, Hui Shen, Huifeng Dong, Zhe Wu, Xuqiang Yang, Shuo Wang, and Shuyu Wang "Research on optimal dispatching technology for virtual power plant considering demand response", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 1317630 (22 May 2024); https://doi.org/10.1117/12.3029347

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