## 1 Introduction  
Energy storage systems (ESSs) are capable of providing a wide array of services, including arbitrage, resource adequacy enhancement, congestion management, reduction of renewable energy source (RES) curtailment and frequency and voltage regulation [1; 2; 3]. RES integration in autonomous systems necessitates increased storage capacities, among other things, to manage curtailments at low load periods [4; 5]. Substantial research is available regarding benefits afforded by storage in terms of unit scheduling and load dispatch, RES hosting capacity and resource adequacy in islands grids [6; 7; 8; 9]. The low inertia of autonomous systems [10] amplifies the need for fast-acting storage units, with battery energy storage systems (BESSs) being the most appropriate technology, given the water column dynamics limitations inherent in pumped hydro facilities [11; 12]. Li-ion is the prevailing technology, due to ease of deployment, high energy and power density, high lifetime expectancy, low self-discharge and continuous cost reduction [13; 14], making them ideal for small- and medium-scale non-interconnected grids. With the accelerated decarbonization of the electricity sector, the introduction of fast response energy storage is considered as a key enabler to support the transition towards a generation mix dominated by stochastic RESs. Beyond autonomous island systems, energy storage brings considerable advantages in several applications including residential, industrial and commercial facilities, e.g., [15; 16; 17; 18]. Enhancing the power management efficiency of seaports is another storage application field, attracting increasing research interest [3]. Electromobility constitutes another principal application field for batteries, where substantial research is taking place, including on optimum power management and battery design and sizing [19]. Focusing on electric power systems, the contribution of RES units to frequency control via droop and inertial emulation is well established in the literature [20; 21; 22; 23]. Similar control principles have been applied to BESSs, taking into consideration state of charge (SOC) limits, to avoid battery degradation [14; 24; 25; 26; 27; 28; 29; 30; 31]. In [25; 26], the authors present a method increasing the storage droop coefficient, when SOC is outside its normal range, while, in [26], another method is also proposed, superposing a charging/discharging term and the droop control. [PERSON] et al. [30] propose SOC restoration to take place when the frequency regulation task permits, i.e., when frequency deviations are limited, whereas regulation is prioritized when deviations are large. The need for imposing constraints in SOC restoration, taking account of available system reserves, is noted in [30], as well as the existing gap in the literature on coordinating frequency and SOC regulation. [PERSON] et al. [31] propose a fuzzy logic controller for SOC restoration when the energy reserves are close to 50%, while using a different scheme (PI control of SOC) for larger SOC deviations. BESS participation in load-frequency control (LFC), traditionally referred to as secondary regulation or deployment of automatic frequency restoration reserves (aFRR) [32], has received less attention. The intermittency of RES generation leads to the increase in aFRR system needs [33]. Enabling effective storage participation in the provision of aFRR reduces the burden placed on conventional power plants and eventually the balancing cost of the system, whilst enhancing frequency stability [5; 34; 35]. As noted in [23], there is room for further improvement in effective coordination between generating and storage units to implement primary and secondary frequency regulation, especially in isolated systems. In [36; 37; 38; 39], an automatic generation control (AGC) system is implemented allocating slow active power variations to conventional units and faster ones to battery systems. A similar control principle is also followed by PJM [10]. [PERSON] et al.