This paper presents a parametric comparative analysis between the virtual synchronous generator (VSG) method and the droop control method to emulate inertia in the voltage-source inverter (VSI). Droop controllers are commonly used to regulate sharing power in microgrids and distribute power generation proportionally among VSI’s depending on their rated power. Additionally, VSG has been used to regulate the Rate-of-Change-of-Frequency (RoCoF) of the microgrid using virtual inertia. Although both methods can be used to regulate the frequency variation, the influence of each method on the closed-loop eigenvalues is not the same. In this work, the transient response of the frequency is analyzed for each method to determine their advantages and disadvantages regarding frequency regulation in microgrid applications. The results were verified by conducting experimental trials using VSI’s. These experiments demonstrated that VSG is more suitable for regulating RoCoF and frequency nadir than droop controllers since it provides inertial support and improves frequency response.

In a Microgrid, the integration of many tasks makes possible an adequate energy management system. Jobs involving real-time support and information procession for having an autonomous and scalable management system, and others such as massive storage capabilities and security considerations to guarantee reliability and validity, are a few. This paper considers them to propose a real-time energy management system based on the economic dispatch problem under a cloud-based architecture, ensuring the appropriately supervised learning functionality in a Microgrid cluster. Namely, it was necessary to revise and run Microgrid implementations, integrate real-time simulation platforms, connect to a virtual server from a Microgrid control, and set the energy management system using cloud computing and machine learning. Based on the results, this article presents a scalable and autonomous cloud-computing architecture for a real-time energy management system using machine learning techniques that allows power generation and energy consumption prediction.

This paper presents a design for a PR controller structure and explains in detail how to calculate their coefficients, for a Voltage Source Converter (VSC) operating in islanding mode. The design is developed in the discrete domain using a state-space model that includes a decoupling of the capacitor voltage technique and a cascade control structure. Moreover, the optimal values of the Proportional-Resonant controller coefficients are found based on the gain and phase margins. The validation of this design considers a 1 kVA VSC with PR controllers, simulation in MATLAB/Simulink, and experimental validation. This also presents a stability study of the proposed design.

This paper presents a voltage control design algorithm for a three-phase voltage source converter (VSC) connected to a linear load using a passive LCL filter. The controller is based on an optimal regulator, combined with the integral of the voltage error, which is called LQI that achieves null tracking of the error. The main objective of this paper is to present an algorithm to design a voltage controller through frequency analysis of the singular values of the system, the weight of the states involved in the system, the movement of the closed poles and their respective step response to evaluate performance and robustness against load changes. The simulation results show a satisfactory operation of the voltage controller with fast recovery after a resistive load change.

This paper presents a formal methodology for the analysis and design for discrete-time proportional-resonant classic (PR) controllers applied to a single-phase DC/AC converter using Sisotool/Matlab. This tool allows observing the response of the system before being simulated or experimentally implemented. Also, it allows to integrate and visualize the classical control theory requirements (overshoot, settling time, etc.) with the design of Proportional Resonant (PR) controllers. Simulations results demonstrate the effectiveness of the methodology presented for the design of PR controllers.