High penetration of renewable energy resources in the power system results in various new challenges for power system operators. One of the promising solutions to sustain the quality and reliability of the power system is the integration of energy storage systems (ESSs). This article investigates the current and emerging trends and technologies for grid-connected ESSs. Different technologies of ESSs categorized as mechanical, electrical, electrochemical, chemical, and thermal are briefly explained. Especially, a detailed review of battery ESSs (BESSs) is provided as they are attracting much attention owing, in part, to the ongoing electrification of transportation. Then, the services that grid-connected ESSs provide to the grid are discussed. Grid connection of the BESSs requires power electronic converters. Therefore, a survey of popular power converter topologies, including transformer-based, transformerless with distributed or common dc-link, and hybrid systems, along with some discussions for implementing advanced grid support functionalities in the BESS control, is presented. Furthermore, the requirements of new standards and grid codes for grid-connected BESSs are reviewed for several countries around the globe. Finally, emerging technologies, including flexible power control of photovoltaic systems, hydrogen, and second-life batteries from electric vehicles, are discussed in this article.

The power system is experiencing an ever-increasing integration of photovoltaic power plants (PVPPs), which leads demand on the power system operators to force new requirements to sustain with quality and reliability of the grid. Subsequently, a significant quantity of flexible power point tracking (FPPT) algorithms have been proposed in the literature to enhance functionalities PVPPs. The intention of FPPT algorithms is to regulate the PV power to a specific value imposed by the grid codes and operational conditions. This will inevitably interfere the maximum power point tracking (MPPT) operation of PV systems. Nevertheless, the FPPT control makes PVPPs much more grid-friendly. The main contribution of this paper is to comprehensively compare available FPPT algorithms in the literature from different aspects and provide a benchmark for researchers and engineers to select suitable FPPT algorithms for specific applications. A classification and short description of them are provided. The dynamic performances of the investigated algorithms are compared with experimental tests on a scaled-down prototype. Directions for future studies in this area are also presented.

Photovoltaic power plants (PVPPs) typically operate by tracking the maximum power point in order to maximize conversion efficiency. However, with the continuous increase of installed grid-connected PVPPs, power system operators have been experiencing new challenges, like overloading, overvoltages and operation during grid voltage disturbances. Consequently, constant power generation (CPG) is imposed by grid codes. An algorithm for the calculation of the photovoltaic panel voltage reference, which generates a constant power from the PVPP, is introduced in this paper. The key novelty of the proposed algorithm is its applicability for both single- and two-stage PVPPs and flexibility to move the operation point to the right- or left-side of the maximum power point. Furthermore, the execution frequency of the algorithm and voltage increments between consecutive operating points are modified based on a hysteresis band controller in order to obtain fast dynamic response under transients and low power oscillation during steady-state operation. The performance of the proposed algorithm for both single- and two-stage PVPPs is examined on a 50-kVA simulation setup of these topologies. Moreover, experimental results on a 1-kVA PV system validate the effectiveness of the proposed algorithm under various operating conditions, demonstrating functionalities of the proposed CPG algorithm.

One of the major concerns associated with the increasing penetration of grid-connected photovoltaic (PV) power plants is the operational challenges (e.g., overloading and overvoltage), imposed due to the variability of PV power generation. A flexible power point tracking (FPPT), which can limit the PV output power to a specific value, has thus been defined in grid-connection regulations to tackle some of the integration challenging issues. However, the conventional FPPT algorithm based on the perturb and observe method suffers from slow dynamics. In this paper, an adaptive FPPT algorithm is thus proposed, which features fast dynamics under rapidly changing environmental conditions (e.g., due to passing clouds), while maintaining low power oscillations in steady-state. The proposed algorithm employs an extra measured sampling at each perturbation to observe the change in the operating condition (e.g., solar irradiance). Afterwards, the voltage-step is adaptively calculated following the observed condition (e.g., transient or steady-state) in a way to improve the tracking performance. Experimental results on a 3-kVA grid-connected single-phase PV system validate the effectiveness of the proposed algorithm in terms of fast dynamics and high accuracy under various operational conditions.

Multilevel cascade H-bridge (CHB) converters are one of the promising solutions for medium- and large-scale grid-connected photovoltaic power plants. However, there is a lack of a complete study about their operation during voltage sags. This paper proposes a flexible control strategy for the operation of photovoltaic grid-connected CHB inverters during unbalanced voltage sags. The key novelty is that the proposed strategy is able to inject both active and reactive powers to the grid with either balanced or unbalanced currents, while ensuring that all dc-link capacitor voltages remain balanced. The simulation and experimental evaluations of a 9-kVA grid-connected seven-level CHB illustrate and validate the performance of the proposed strategy for the operation of the grid-connected CHB converter during different unbalanced voltage sags.