THE ROLE OF INDUSTRIAL AUTOMATION IN THE ENERGY TRANSITION: TECHNOLOGIES FOR EFFICIENCY IN POWER PLANTS

Abstract

The energy transition places new demands on power-generation assets: higher flexibility, tighter integration with variable renewable resources, and continuous pressure to reduce CO₂ emissions and operating costs. Industrial automation—understood broadly as the integration of sensors, distributed controllers, advanced process control and data-driven decision systems—is a practical enabler of that transition. This article argues that modern automation architectures, when combined with real-time control, predictive analytics and digital-twin models, deliver measurable reductions in energy consumption and fuel losses, improve plant ramping performance, and extend equipment life through condition-based maintenance. Evidence from recent literature and applied studies is reviewed to show how high-fidelity sensing and state estimation, advanced regulatory and economic model-predictive controllers, and closed-loop digital twins with real-time orchestration platforms work together to improve efficiency in thermal, hydro and hybrid power plants. The synthesis highlights implementation challenges, such as interoperability, computational requirements and cybersecurity, and suggests pragmatic pathways for staged adoption that prioritize high-impact subsystems and verifiable energy savings.