The high proliferation of converter-dominated Distributed Renewable Energy Sources (DRESs) at the distribution grid level has gradually replaced the conventional synchronous generators (SGs) of the transmission system, resulting in emerging stability and security challenges. The inherent characteristics of the SGs are currently used for providing ancillary services (ASs), following the instructions of the Transmission System Operator, while the DRESs are obliged to offer specific system support functions, without being remunerated for these functions, but only for the energy they inject. This changing environment has prompted the integration of energy storage systems as a solution for transfusing new characteristics and elaborating their business in the electricity markets, while the smart grid infrastructure and the upcoming microgrid architectures contribute to the transformation of the distribution grid. This review investigates the existing ASs in transmission system with the respective markets (emphasizing the DRESs’ participation in these markets) and proposes new ASs at distribution grid level, with emphasis to inertial response, active power ramp rate control, frequency response, voltage regulation, fault contribution and harmonic mitigation. The market tools and mechanisms for the procurement of these ASs are presented evolving the existing role of the Operators. Finally, potential barriers in the technical, regulatory, and financial framework have been identified and analyzed.

This work proposes a new control strategy for the voltage regulation of unbalanced low-voltage (LV) distribution grids with high penetration of distributed renewable energy sources (DRESs). The proposed method uses the available reactive power of DRESs as the primary means for voltage regulation. Furthermore, its distinct feature is the use of a distributed control architecture prioritizing the response of DRESs to maintain the network voltages within permissible limits and minimize the network losses. The prioritization process is locally implemented by each DRES combining two types of information: (a) the sensitivity matrix that quantifies the impact of reactive power variations on the network voltages and (b) voltage measurements along the network. Time-domain and time-series simulations on the IEEE European LV test feeder are performed to evaluate the performance of the proposed method against existing decentralized, distributed and centralized, optimization-based methods.

The variability of the output power of distributed renewable energy sources (DRESs) that originate from the fast-changing climatic conditions can negatively affect the grid stability. Therefore, grid operators have incorporated ramp-rate limitations (RRLs) for the injected DRES power in the grid codes. As the DRES penetration levels increase, the mitigation of high-power ramps is no longer considered as a system support function but rather an ancillary service (AS). Energy storage systems (ESSs) coordinated by RR control algorithms are often applied to mitigate these power fluctuations. However, no unified definition of active power ramps, which is essential to treat the RRL as AS, currently exists. This paper assesses the various definitions for ramp-rate RR and proposes RRL method control for a central battery ESS (BESS) in distribution systems (DSs). The ultimate objective is to restrain high-power ramps at the distribution transformer level so that RRL can be traded as AS to the upstream transmission system (TS). The proposed control is based on the direct control of the ΔP/Δt, which means that the control parameters are directly correlated with the RR requirements included in the grid codes. In addition, a novel method for restoring the state of charge (SoC) within a specific range following a high ramp-up/down event is proposed. Finally, a parametric method for estimating the sizing of central BESSs (BESS sizing for short) is developed. The BESS sizing is determined by considering the RR requirements, the DRES units, and the load mix of the examined DS. The BESS sizing is directly related to the constant RR achieved using the proposed control. Finally, the proposed methodologies are validated through simulations in MATLAB/Simulink and laboratory tests in a commercially available BESS.