In the last years, the overall system inertia is decreasing due to the growing amount of energy resources connected to the grid by means of power inverters. As a consequence, reduced levels of inertia can affect the power system stability since slight variations of power generation or load may cause wider frequency deviations and higher rate of change of frequency (RoCoF) values. To mitigate this trouble, end-user distributed energy resources (DERs) interfaced through grid-following inverters, if opportunely controlled, can provide additional inertia. This paper investigated the possibility of improving the control law implemented by a low-cost controller on remotely controllable legacy DERs to provide synthetic inertia (SI) contributions. With this aim, power hardware-in-the-loop simulations were carried out to test the capability of the proposed controller to autonomously measure frequency and RoCoF and provide SI actions by controlling an actual battery energy storage system.

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Providing fast frequency regulation by means of energy storage systems is currently considered as a viable solution to low-inertia issues, caused by power electronics-interfaced generators. In particular, hybrid energy storage systems, composed by more energy storage technologies having different power and energy ratings, can optimally support the frequency regulation. A supercapacitor/battery storage system, for example, can exploit the supercapacitor dynamic active power response for synthetic inertia control, while the battery can provide primary and secondary frequency regulation. However, the optimal energy management of hybrid energy storage systems during transients needs to be addressed further in literature. In this paper, a State of Charge (SOC) feedback control scheme is proposed, that adjusts the active power output reference depending on the state of charge, avoiding excessive stress on the components and limiting the state of charge excursions. Control system parameters are optimally tuned minimizing a weighted multi-objective function in the solution of an optimal control problem. Test results adopting different weights are presented and discussed.