Integrating Renewable Energy Sources with Micro Grid Using IOT and Machine Learning

Abstract

The power system landscape has undergone significant changes over the past few decades, marked by increasing electricity demand, power losses, grid failures, and the absence of smart technology. Simultaneously, security threats have escalated, and conventional power grids are struggling to cope with these challenges. In response to these evolving demands, the Internet of Things (IoT) has rapidly gained prominence due to its transformative potential. By incorporating IoT technology into power grids, we have the ability to improve the efficiency, sustainability, scalability, capacity, reliability, and stability of traditional grid systems. 1. This document provides an in-depth analysis of IoT-enabled intelligent power grids, emphasizing the importance of tackling security concerns, examining diverse use cases, and deliberating on alternative frameworks. Furthermore, we explore IoT and non-IoT technologies utilized in smart grid systems, such as sensing, computing technologies, communication, and applicable standards.

Keywords

• energy management
• artificial neural network
• microgrid
• renewable energy
• iot
• energy demand prediction