Integrating forecasting models in Cyber Physical Power Systems

Cyber Physical Power System (CPPS) has been recognized as the most promising enabling technology for integrating and coordinating computing, networking, and physical processes according to a holistic vision of the transmission system. In CPPS, the network components and the computing entities cooperate in order to collect pervasive electrical and meteorological data, identifying suitable control actions, and adapting the grid controllers parameters. In solving these critical issues, meteorological and lighting forecasting represents a relevant issue to address, as they allow a reduction of outages and disturbances in the power system. Armed with such a vision, in this paper an autonomic CPPS framework, which explicitly integrates dynamic thermal models, adaptive estimation techniques, and weather forecasting algorithms is conceptualized. Validity and effectiveness of the proposed framework is experimentally assessed on a real-life 150 kV equivalent section of the Italian power system.