Hierarchical control is a widely used strategy that can increase resilience and improve the reliability of the electrical network based on microgrid global variables. The large amounts of data required during transitions prompt the use of more reliable and flexible communications to achieve the control objectives. Such communications can involve potential cyber vulnerabilities and latency restrictions, which cannot be always addressed in real-time. To accurately capture the system’s overall operation, this paper proposes a co-simulation framework driven by flexible communications and a resilient control algorithm to regulate the frequency and voltage deviations in a networked microgrid. Model-based predictive control has been implemented, to avoid slow transient response associated with linear hierarchical control. Software-Defined Networking (SDN) is responsible for increasing the communication intelligence during the power-sharing process. The effects of critical communications and overall system performance are reviewed and compared for different co-simulation scenarios. Graphical Network Simulator (GNS3) is used in combination with model-based predictive control and SDN, to provide latency below 100 ms, as defined in IEC 61850. Testing of the proposed system under different cyber attack scenarios demonstrate its excellent performance. The novel control architecture presented in the paper provides a reference framework for future cloud computing-based microgrids.

Renewable energy has gained significant attention of researchers in the last years, mainly due to the importance of using unlimited energy sources to supply homes, industries, cities and countries. In this context, this document focuses on the solar injection by employing a neutral point clamped (NPC) topology together with utilization of a maximum power point tracking (MPPT) and space vector modulation (SVM) techniques. Model predictive control (MPC) is employed to manage the currents and track their references. The proposed algorithms do not employ a cost function to decide which voltage to apply resulting in a spread frequency spectrum, and instead, a concentrated SVM spectrum is imposed. Notwithstanding, the DC link capacitors voltage balance is ensured and the computational burden is notably reduced as compared to traditional Finite Set Model Predictive Control (FS-MPC). Nevertheless, the consistent results are a consequence of the critical analysis that shows the feasibility of the proposal and guarantees the good performance of the entire system in simulated and experimental platforms.

The inclusion of solar systems in rural microgrids is becoming increasingly important to supply energy for irrigation, electric motors, lighting and other. This paper presents the implementation of an exact linearization technique for the modeling and control of a DC/DC converter for use in a microgrid based on a photovoltaic (PV) generation system where non-linear converters are used. The basic advantage of this technique is in linearizing the converter model, thus allowing different operating points to be considered under different conditions. This paper presents a general description of the implemented microgrid topology. The exact linearization theory adapted for power converters is applied to both a Single-Ended Primary-Inductor converter (SEPIC) to extract energy from PV modules and to a Boost converter to increase the voltage. Experimental results are also presented to validate the effectiveness of the proposed control.

Over the last few decades, the consolidated goal of reducing greenhouse gasses has increased the relevance of renewable energy research, electromobility, energy storage, and distributed generation, micro-grids, among others. Micro-grids, systems working in islanding mode, are particular cases where some disadvantages are present due to the wide variations which may appear across their electrical quantities. Variations on the voltage amplitude and the frequency are intrinsic in the operation of weak grids, because they have low inertia and therefore the load must be able to cope with these variations, otherwise loads may trip electrical system protection. Particularly, on power electronic drives, these frequency deviations will lead to increased system nonlinearities, entailing a more critical controller design. To overcome these issues, this paper presents an implementation of a resonant controller with self-tuned gains. The strategy imposes a constant sampling time which allows these controllers to be used in variable frequency environments. In addition, the computational capacity required for the digital board is also considered. The simulated and experimental results provided demonstrate the good performance of this proposal.

Power converters have turned into a critical and every-day solution for electric power systems. In fact, the incorporation of renewable energies has led towards the constant improvement of power converter topologies and their controls. In this context, over the last 10 years, model predictive control (MPC) is positioned as one the most studied and promising alternatives for power converter control. In voltage source inverters (VSI), MPC has only been applied in the inner current control loop, accelerating and improving its dynamic response, but as mentioned, has been limited only to the current control loop. The fastest of the MPC techniques is the Deadbeat (DB) control, and in this paper, it is proposed to employ DB control on the entire system, therefore accelerating the time response not only for the current loops, but also for voltage loops. At the same time, this avoids overshoots and overpower in order to protect the power converter, leading to the fastest dynamic response according to VSI capabilities. For renewable energies, fast-dynamics entails fast maximum power tracking and therefore, maximizes energy harvesting, or in other words, reduces the losses due to the control dynamics. Thus, this paper gives a clear procedure and key points for designing a DB control for all the variables based on a mathematical model, which is corroborated by simulations and the experimental results.

The use of renewable energies sources is taking great importance due to the high demand for electricity and the decrease in the use of fossil fuels worldwide. In this context, electricity generation through photovoltaic panels is gaining a lot of interest due to the reduction in installation costs and the rapid advance of the development of new technologies. To minimize or reduce the negative impact of partial shading or mismatches of photovoltaic panels, many researchers have proposed four configurations that depend on the power ranges and the application. The microinverter is a promising solution in photovoltaic systems, due to its high efficiency of Maximum Power Point Tracking and high flexibility. However, there are several challenges to improve microinverter’s reliability and conversion efficiency that depend on the proper control design and the power converter design. This paper presents a review of different control strategies in microinverters for different applications. The control strategies are described and compared based on stability, dynamic response, topologies, and control objectives. One of the most important results showed that there is little research regarding the stability and robustness analysis of the reviewed control strategies.