E3S Web of Conferences (Jan 2024)

Designing a Renewable Energy System for Industrial IoT with Artificial Intelligence

  • Menaka C.,
  • Awasthi Aishwary,
  • Chandra Yadav Dhyan,
  • Jain Sandeep Kumar

DOI
https://doi.org/10.1051/e3sconf/202454013008
Journal volume & issue
Vol. 540
p. 13008

Abstract

Read online

This paper reviews the integration of renewable energy systems with Industrial IoT (IIoT) through Artificial Intelligence (AI). It examines various studies focusing on the design and monitoring of solar-powered wireless sensor nodes in diverse IIoT settings, particularly outdoors. A proposed distributed network architecture, underpinned by open-source technologies, aims for efficient solar power harvesting and data acquisition on solar radiation and ambient parameters. This data aids in devising estimation techniques to predict solar panel voltage outputs, optimizing energy utilisation of solar-powered sensor nodes. The discourse extends to photovoltaic plants, emphasising continuous monitoring and fault detection for operational safety and reliability. Reviewed works advocate embedding AI and IoT for remote sensing, fault detection, and diagnosis, addressing challenges posed by undetectable faults. Furthermore, the paper explores AI’s transformative potential in the broader energy sector, impacting electricity production, distribution, energy storage, and efficiency. The synergy of AI, IIoT, and renewable energy systems is underscored as a conduit for enhancing energy management, operational transparency, and deploying cost-effective solutions for complex industrial challenges, significantly bolstering the efficiency and intelligence of industrial production and services.