Risk Based Assessment Of Subsynchronous Resonance In Ac Dc Systems

Risk Based Assessment of Subsynchronous Resonance in AC/DC Systems

This relevant and timely thesis presents the pioneering use of risk-based assessment tools to analyse the interaction between electrical and mechanical systems in mixed AC/DC power networks at subsynchronous frequencies. It also discusses assessing the effect of uncertainties in the mechanical parameters of a turbine generator on SSR in a meshed network with both symmetrical and asymmetrical compensation systems. The research presented has resulted in 12 publications including three top international journal papers (IEEE Transactions on Power Systems) and nine international conference publications, including two award-winning papers.

Risk Based Assessment of Subsynchronous Resonance in AC

Proceedings of 5th International Conference on Artificial Intelligence and Smart Energy

This book discusses the latest developments in computing techniques that power smart energy and sustainable solutions. Over the last few years, artificial intelligence (AI) has been more deeply embedded in our lives, revolutionizing industries and communication. Intelligent computing models are now transforming traditional energy applications in this digital age through smart automation, optimization, and adaptation. The book addresses major facets of intelligent computing and communication technologies, such as intelligent data analysis, predictive modeling, optimization, neural networks, AI, machine learning, deep learning, and the Internet of Things (IoT). All these technologies are discussed in practical applications, e.g., smart cities and smart industries, their transformative possibilities.