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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) |
| Number of pages | 6 |
| Publisher | IEEE Press |
| Publication date | Nov 2017 |
| ISBN (Electronic) | 978-1-5386-1427-3 |
| DOIs | |
| Publication status | Published - Nov 2017 |
| Event | 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) - Beijing, China Duration: 26 Nov 2017 → 28 Nov 2017 |
Conference
| Conference | 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) |
|---|---|
| Country/Territory | China |
| City | Beijing |
| Period | 26/11/2017 → 28/11/2017 |
Keywords
- Integrated gas and power systems
- Dynamic energy flow
- Approximate dynamic programming (ADP)
- Model predictive control (MPC)
- Online optimization