Fault Management in Speed Control Systems of Hydroelectric Power Plants Through Petri Nets Modeling: Case Study of the Alazán Power Plant, Ecuador

This study addresses the challenge of improving fault management in hydroelectric systems using Petri nets. The objective is to propose a novel methodology for efficient fault diagnosis and intervention in the Governor system, a critical component in regulating turbine speed. Traditional diagnostic approaches often rely on manual inspection and expert intuition, and they lack formal mechanisms to model concurrent or asynchronous system behavior—leading to delays and reduced accuracy in fault identification. Our approach introduces a structured modeling technique using Petri nets, enabling dynamic analysis of the system’s behavior and response to faults. A detailed methodology was developed, beginning with a thorough characterization of the system and its translation into a Petri net model. Simulation results demonstrate the model’s effectiveness in significantly reducing diagnostic and intervention times compared to traditional methods. Results show that using Petri nets improves fault detection accuracy, accelerates decision-making, and optimizes resource allocation. This research concludes that the proposed model offers a robust framework for enhancing fault management in hydroelectric plants, providing both operational efficiency and reduced downtime. Future work will focus on integrating real-time monitoring and further validating the model in live environments to ensure scalability and adaptability to other power generation systems.