Simultaneous Frequency Regulation and Active Power Sharing in Islanded Microgrid using Deep Reinforcement Learning

This paper presents a novel approach that integrates deep reinforcement learning (DRL) with the conventional virtual synchronous generator (VSG) to address dual objectives of microgrid (MG) control, frequency regulation and precise active power sharing. MGs typically consist of multiple Inverter-Based-Distributed-Generators (IBDGs) connected in parallel through different line impedances. The conventional active power loop (APL) of the VSG encounters significant steady-state frequency errors as load increases/decreases during islanded operation. To mitigate this issue, secondary-level controllers like proportional-integral (PI) control are added to the APL to regulate the frequency of IBDGs. However, PI control compromises power-sharing capabilities when the impedance values of connecting feeders for each IBDG are mismatched. To eliminate frequency errors and achieve accurate power sharing concurrently, this study adopts a DRL-based strategy. The agent collects state information from each IBDG in the microgrid as input and undergoes training using a reward function crafted to satisfy both objectives simultaneously. The performance of the trained agent is demonstrated in a two-inverter microgrid system designed in MATLAB/SIMULINK and is compared against traditional methods

Instantaneous Current and Average Power Flow Characterization of a DC-DC-DC Triple Active Bridge Converter

The Triple Active Bridge (TAB) is a Three-Port Power Converter that Facilitates Bi-Directional Power Flow and Provides Galvanic Isolation, Making It a Subject of Significant Research Attention. This is Attributed to its Diverse Applications in High-Frequency DC-DC Conversion, Electric Vehicles, Renewable Energy Integration, and Micro-Grids. Controlling the System at Run-Time Involves Modification of the Two Phase-Shift Parameters between Respective Bridges. by Analyzing the Fundamental Converter Operating Equations, Future Control Designers Can Use This Framework to Optimize Control Schemes to Mitigate the Under-Determined Nature of the TAB Converter. in This Paper, We Elucidate the Foundational Operational Principles of the TAB and Establish the Defining Equations for Instantaneous Current and Average Power Flow. Furthermore, We Validate These Equations through a Comparative Analysis Involving a Simulation Model of the TAB in PLECS and Hardware Implementation

Active and Reactive Power Flow Control of the Dual Active Bridge Converter

The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present work introduces a combined feedback/feed-forward current control system, utilizing the calculated and measured converter currents translated into the dq reference frame, to control the output power. The system was simulated in PLECS to demonstrate the control algorithm\u27s ability to track the dq currents and provide the necessary output power