Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks
Abstract
Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the current state of the power system to be able to detect critical situations immediately. This paper proposes a method based on artificial neural networks that is capable of providing an online supervision service, which works in real-time due to its low demand for computational resources. Additionally, the requirements regarding system state information of such a monitoring system are investigated to assess the measurement and communication setup necessary for its proper functionality and thus its applicability to real power systems.
