Design and Raspberry Pi-Based Implementation of an Intelligent Energy Management System for a Hybrid AC/DC Microgrid with Renewable Energy, Battery, Ultracapacitor and Hydrogen System

Abstract

Hybrid AC/DC microgrids (HMGs) have garnered significant research attention due to their ability to integrate consumption, generation, and storage devices within both AC and DC microgrids (MGs). In this context, this article presents the design and implementation of a novel intelligent energy management system (EMS) for a grid-connected HMG with AC and DC MGs, using a Raspberry Pi microcontroller. The DC MG integrates an ultracapacitor, a wind turbine, a hydrogen system and DC loads. Meanwhile, the AC MG comprises a battery bank, three-phase loads and a photovoltaic (PV) generator. The control system features local controllers for each device and a dynamic fuzzy-logic-based EMS implemented on a Raspberry Pi microcontroller to regulate all devices within the HMG. The fuzzy-logic-based EMS is compared to a conventional EMS based on state machine and an EMS based on a multivariable optimization algorithm (implemented using MATLAB's fmincon function) under different operating conditions, including different levels of generation, consumption and storage. The results demonstrate superior energy management and reduced grid dependency with the fuzzy-logic-based EMS. An experimental setup, comprising an OPAL-RT 4512 emulator and a Raspberry Pi microcontroller communicating via Modbus protocol, validates the findings. Both simulated and experimental results confirm the satisfactory performance of the HMG when controlled by the proposed intelligent EMS under various operating conditions.