Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

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.