@article{Li2024, 
author = {Qi Li and Xueli Zou and Yuchen Pu and Weirong Chen},
title = {Real-time Energy Management Method for Electric-hydrogen Hybrid Energy Storage Microgrids Based on DP-MPC},
year = {2024},
journal = {CSEE Journal of Power and Energy Systems},
volume = {10},
number = {1},
pages = {324-336},
keywords = {Electric-hydrogen hybrid energy, economic energy management, improved dynamic programming, microgrid, model predictive control},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2020.02160},
doi = {10.17775/CSEEJPES.2020.02160},
abstract = {With the increasing presence of intermittent energy resources in microgrids, it is difficult to precisely predict the output of renewable resources and their load demand. In order to realize the economical operations of the system, an energy management method based on a model predictive control (MPC) and dynamic programming (DP) algorithm is proposed. This method can reasonably distribute the energy of the battery, fuel cell, electrolyzer and external grid, and maximize the output of the distributed power supply while ensuring the power balance and cost optimization of the system. Based on an ultra-short-term forecast, the output power of the photovoltaic array and the demand power of the system load are predicted. The off-line global optimization of traditional dynamic programming is replaced by the repeated rolling optimization in a limited period of time to obtain power values of each unit in the energy storage system. Compared with the traditional DP, MILP-MPC and the logic based real-time management method, the proposed energy management method is proved to be feasible and effective.}
}