Real time power management strategy for hybrid energy storage systems coupled with variable energy sources in power smoothing applications

As the renewable energy sources (RES) production is strongly influenced by multiple geographic factors and highly variable, the need for both energy storage integration and robust real-time power management strategies development is obvious. Wind power represents the largest generating capacity among RES, being at the same time the most fluctuant. The capability to overcome the great disadvantage of wind power variability supports rising its penetration while preserving current operation modes of power systems, so new fashions to achieve this target are of great interest. This paper aims to prove the robustness of a recently introduced power management strategy, able to operate in online conditions, based on simultaneous perturbation stochastic approximation (SPSA) algorithm. To this regard, two different real datasets for wind power profiles with different statistical features are employed. The power management strategy is implemented on a hybrid energy storage system comprising a battery and a flywheel, modeled in Simulink/Matlab. The objectives of the proposed strategy are to reduce the instantaneous power ramp of the profile injected to the grid while smoothening the power profile exchanged by the battery in order to preserve it. Simulations are performed in representative conditions selected on statistical basis. It is demonstrated that the SPSA based power management achieves similar performances in all simulation conditions, proving to be robust. As a performance indicator, the reduction of the power ramp in reference to the 90% CDF threshold is evaluated. It is remarked as an 80% power ramp reduction is obtained towards the grid in both sites. Moreover, the further target is achieved in terms of battery lifetime extension; specifically, the fluctuation of the power profile exchanged by the battery is smoothed by 63% in the first site and 48% in the second, with respect to the flywheel one. (C) 2021 The Authors. Published by Elsevier Ltd.