IIoT-Driven Automation Architecture for Renewable-Integrated Smart Grids in Energy-Intensive Industries

Abstract

Industries requiring a significant amount of energy are heavily reliant on electricity and have to find ways to keep their operations running smoothly while also meeting sustainability and carbon reduction goals. The increasing integration of renewable energy, electric vehicles (EVs), and battery energy storage systems (BESS) introduces challenging unpredictability, bidirectional power flows, and coordination at a real-time level, which standard supervisory control and automation systems have not been able to manage. These issues are a significant contributing factor to peak demand, high costs, and decreased resiliency of energy grids. This paper presents a solution to this problem by proposing a specific type of automation architecture to integrate renewable energy and smart grids for industrial use based on the Industrial Internet of Things (IIoT). The system consists of a four-layer architecture of perception, communication, edge-cloud processing, and application layers. The use of Distributed IIoT sensors for real-time data acquisition and edge gateways for low-latency analytics and control is included. An AI-enabled Energy Management System (EMS) coordinates solar PV generation, EV charging, and BESS for optimal use of the EMS's load forecasting, Model Predictive Control (MPC), and demand response. The system is designed for secure, scalable, interoperable industrial use. The performance evaluation is carried out on a virtual industrial microgrid that contains 2MW of solar PV, 1.5 MWh of BESS, and flexible EV loads. When considering conventional rule-based control, the proposed method offers 24–26% peak demand reduction, 18–21% savings on energy costs, 28% reduction in greenhouse gas emissions, reduction of 32% in greenhouse gas emissions, and a 32% increase in utilization of renewable energy. Furthermore, edge computing decreases communication lags by 40%, resulting in a better system response and increased operational reliability. The performance results indicate that the automation of IIoT offers a high degree of efficiency, flexibility, and sustainability to industrial smart grids. The proposed framework offers a practical solution that is also scalable to the next generation of energy management systems in smart industries with low-carbon and intelligent power systems.