Advanced fault diagnosis and prognostics using digital twin technology

Abstract

The increased utilization of alternative sources of energy—wind, solar, biomass, geothermal, and tidal energy, for instance—requires advanced technologies that are not only reliable but also efficient and sustainable. Though these renewable energy systems are inherently environmentally friendly, they usually operate under fluctuating and often adverse conditions, which makes them susceptible to operational failures and malfunctions. Conventional maintenance approaches, whether reactive or preventive, are insufficient for the complexities found in these systems, often resulting in unscheduled downtimes, inefficient operations, and high costs. An innovative approach to creating virtual representations of physical assets, digital twin technology (DTT) uses real-time information to continuously update these representations. This chapter delves into the advanced applications of DTT in fault diagnosis and prognostics in non-conventional energy systems. By analyzing real-time monitoring, machine learning algorithms, and predictive analytics applied toward proactive fault identification, remaining useful life estimation, and prescriptive methodologies for maintenance, the authors present an excellent study. This chapter showcases the practical application of DTT in wind energy systems, solar farms, and battery storage units, highlighting measurable improvements in operational efficiency, fault detection capability, and maintenance cost savings. For instance, fault detection through DTT was enhanced by more than 12%, while optimized maintenance schedules led to a 30% reduction in downtime across different case studies. Further, the chapter covers the complexities of deploying DTT, including data integration, model calibration, and cybersecurity risks. It also explores future directions of AI-enhanced digital twins, the integration of robotics for self-healing systems, and quantum computing in real-time simulation. Digital twin technology allows for the development of a sustainable energy future by changing the way renewable systems are monitored, maintained, and optimized. This chapter provides details that explain what DTT was designed to do and its vital role in improving non-traditional sources of energy.