A model-free distributed cooperative frequency control strategy for MT-HVDC systems using reinforcement learning method

Abstract

The performance of the existing frequency control strategies for MT-HVDC systems relies on the accuracy of the mathematical models. However, it is hard to obtain the exact mathematical models of MT-HVDC systems. To deal with this challenge, this paper presents a distributed cooperative frequency control strategy for MT-HVDC systems by using a reinforcement learning method, i.e., value iteration algorithm. Specifically, the proposed control strategy is data driven and hence model free. Besides, the proposed control strategy is distributed in the sense that each AC area only requires the local and neighboring information, rather than the information of all the AC areas. Moreover, the proposed control strategy makes the connected AC areas compensate load disturbances together by sharing their power reserves via HVDC grids, which greatly decreases the operation costs of MT-HVDC systems. The performance of the proposed control strategy is validated by cases study.