The increasing demand for efficient and resilient renewable-based energy systems is driving research towards hybrid ac/dc microgrids (HMG), offering a practical pathway to future dc-dominant grids by directly integrating a wide range of dc-operated resources. This paper proposes a model-free real-time control strategy for coordinating distributed generators (DGs) to achieve dynamic global power sharing in an islanded HMG. Conventional model-based controllers are replaced with a deep reinforcement learning agent based on the deep deterministic policy gradient (DDPG) algorithm. Unlike most existing studies that rely on offline training through computer simulations, the proposed agent is trained online during normal operation, without requiring predefined system models or manual controller tuning. The effectiveness of the method is validated through hardware-in-the-loop (HIL) experiments under different load variation scenarios, demonstrating robust dynamic response and accurate global power sharing.

To keep up with the rising demand for electricity, renewable energy sources, including solar and wind power, are being increasingly utilized. However, grid stability is compromised by the intermittent nature of renewable energy resources. Technologies for energy storage provide a solution by enhancing system flexibility. As prosumer-based electrical systems and distributed energy resources expand, energy management systems are becoming more essential for optimizing system functionality and efficiency by coordinating the operation of various devices. This paper deals with a genetic algorithm-based energy management system consisting of PV generation, household load, electric vehicle, and energy storage system. The objective is to reduce electricity costs by defining the objective function and related constraints. The main novelty of this paper is the study of different parameters used in a genetic algorithm, and to find out the best set of parameters in terms of electricity cost reduction, that can be later used as guidelines to design similar types of systems.

The introduction of the three-phase dual-purpose dc-ac/dc power converter (PC), a recent addition to the universal converter family, holds significant promise for improving the reliability and flexibility of modern microgrids (MGs). This paper presents a novel energy management strategy for a flexible hybrid ac/dc MG architecture featuring dual-purpose dc-ac/dc power converters. These converters offer the capability of both dc/ac and dc/dc power conversion, allowing for connection to either the ac bus or the dc bus through simple reconfiguration, thereby providing enhanced modularity and operational adaptability to various MG conditions. Leveraging model-free reinforcement learning (RL) algorithms, the proposed strategy optimizes the operation mode of the dual-purpose converters to minimize the interlinking converter utilization based on historical MG operational data. The feasibility of the proposed MG architecture and the performance of the RL-based energy management strategy are verified by simulation results.

As power systems move towards decentralized models based on renewable energy sources with distributed generation, the role of power inverters in microgrids becomes increasingly important. In this paper, a three-level T-type quasi-impedance source inverter (3L-T-type qZSI) with a grid-forming control structure is studied for the first time in an islanded ac microgrid composed by three prosumers, supplying residential loads. The power sharing among prosumers is achieved through the well-known droop control method with virtual impedance, and proportional-resonant (PR) controller-based voltage and current control loops. A proportional-integral (PI) based control for regulating the dc-link voltage of the T-Type inverter was implemented making use of the boost ability of the qZS network. The proper operation of the microgrid has been tested by simulation with PLECS, demonstrating a robust behavior of the overall system and a good dynamic performance of the proposed control structure for the 3L-T-Type qZSI in different conditions.

In this paper a detailed analysis of a bidirectional buck boost converter used for charging/discharging a supercapacitor is carried out. The analysis takes into account conduction parameters of semiconductors and resistances of inductors, determining the variation of different performance indeces when the charge (and voltage) of supercapacitor varies.

This paper studies an operation strategy for a single-phase grid-connected 3LT-type qZSI to regulate the active and reactive power flows. This topology is quite promising in photovoltaic system. The different elements are properly calculated, providing simulation results with a good concordance with the theoretical predictions.

This work presents an energy management strategy based on scheduling battery operation in prosumer systems, according to forecast data available 24 hours in advance. The proposed method seeks to reach a beneficial compromise between prosumers and distribution grid operators, independently of specific economic context or technical regulations. An improvement to deal with forecast inaccuracy is carried out. Results demonstrate that it offers good properties regarding energy management, with a stored energy reserve estimation, battery lifetime preservation and self-consumption and self-sufficiency enhancement.

The upgrade of power systems in the last years due to the proliferation of distributed generation with renewable energy sources, active users and electric vehicles has become a challenge. In this new scenario, prosumers play an important role in order to buffer the consumption curve and, therefore, contributing to the grid requirements. Special attention is attracted by photovoltaic (PV) arrays integrated in residential buildings, because they can be complemented with energy storage systems (ESSs), such as batteries or ultracapacitors (UCs) or even a combination of both, with the aim to achieve that customers could manage their energy. The above reasons justify the need of an energy management system (EMS) that coordinates the operation of the energy storage devices in an optimized way, as they are expensive. In this paper, a comprehensive control system is proposed to exchange energy between the hybrid storage devices (batteries and UCs) of two dwells with PV installations in order to increase the availability of their ESSs and support the energy requirements during the most time possible, optimizing sizes and costs and avoiding saturation.

High penetration levels of distributed photovoltaic inverters on electrical distribution grids and due to the main points demanded in the latest issues of grid codes such as the reactive power injection during transient grid faults (voltage sags) and their disconnection in order to avoid the islanding phenomena, a suitable control algorithm combination is needed to provide an optimum operation at the electrical grids where they are connected, improving the power quality and the power supply continuity. This paper is devoted to the comparison through simulation of two power flow control strategies for 100 kW photovoltaic inverters in order to analyze the advantages and disadvantages of each one. The first one is based on the modulation index and the disphase controls of the reference signal face to the point of common coupling voltage. The second one is based on a synchronous reference frame with the voltage at the point of common coupling using idand iqcurrent component controllers.