A three-stage intelligent coordinated operation for grouped hydrogen-based hybrid storage systems considering the degradation and the future impacts based on multi-criteria decision making

Hybrid storage is often integrated to tackle the uncertainty of renewable energy sources. To face a variety of ancillary services, hybrid storage systems are often grouped together forming a larger energy and power densities storage system. However, to healthily coordinated schedule the grouped hybrid storages is still a problem. In this paper, a three stage combined algorithm is proposed to cooperate the grouped hybrid storage systems: first, multi-criteria decision making is adopted to allocate expected power to each hybrid storage system; second, model predictive control (MPC) associated with support vector machine and Kalman filter is used to dispatch the allocated power to hydrogen storage and battery; third, a PID controller is deployed for reference tracking. Simulation results show that prediction errors in MPC cause the increases of operation cost and degradation index. For the operation cost, the combined fuzzy membership and MPC-Kalman filter algorithm has a better performance. The PID controller has a good ability to track reference signals. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes a three-stage algorithm to coordinate grouped hybrid storage systems: first, using multi-criteria decision making to allocate expected power to each hybrid storage system; second, employing model predictive control with support vector machine to dispatch the allocated power; third, utilizing a PID controller for reference tracking. Simulation results indicate that prediction errors in MPC lead to increased operation cost and system degradation index. The combination of fuzzy membership and MPC-Kalman filter algorithm shows better performance in reducing operation cost. The PID controller demonstrates good ability in tracking reference signals.