Sheng Wang

This book focuses on the risk modeling, analysis and control of multi-energy systems considering cross-sectorial failure propagation. Both models and methods have been addressed with engineering practice. This is accomplished by doing a thorough investigation into the modeling of system physics and reliabilities in both long- and short-term phases. Different models and methods to evaluate the risk of multi-energy systems considering various disturbances, e.g., component failures, load uncertainties and extreme weather, are studied in detail. Furthermore, several risk control strategies for multi-energy systems, such as long-term capacity planning and integrated demand response, are analyzed in this book, which is especially suited for readers interested in system risk management. The book can benefit researchers, engineers, and graduate students in the fields of electrical and electronic engineering, energy engineering, complex network and control engineering, etc.

This book focuses on the risk modeling, analysis and control of multi-energy systems considering cross-sectorial failure propagation. Both models and methods have been addressed with engineering practice. This is accomplished by doing a thorough investigation into the modeling of system physics and reliabilities in both long- and short-term phases. Different models and methods to evaluate the risk of multi-energy systems considering various disturbances, e.g., component failures, load uncertainties and extreme weather, are studied in detail. Furthermore, several risk control strategies for multi-energy systems, such as long-term capacity planning and integrated demand response, are analyzed in this book, which is especially suited for readers interested in system risk management. The book can benefit researchers, engineers, and graduate students in the fields of electrical and electronic engineering, energy engineering, complex network and control engineering, etc.

This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.