Hybrid approximate dynamic programming approach for dynamic optimal energy flow in the integrated gas and power systems
Document Type
Conference Proceeding
Date of Original Version
6-28-2017
Abstract
This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real-time updated forecast information. The simulation results demonstrate the effectiveness of the proposed algorithm.
Publication Title, e.g., Journal
2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings
Volume
2018-January
Citation/Publisher Attribution
Shuai, Hang, Xiaomeng Ai, Jinyu Wen, Jiakun Fang, Zhe Chen, and Haibo He. "Hybrid approximate dynamic programming approach for dynamic optimal energy flow in the integrated gas and power systems." 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings 2018-January, (2017): 1-6. doi: 10.1109/EI2.2017.8245577.