Xiaolong Jin – författare

Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty discusses core concepts, advanced modeling and key operation strategies for integrated multi-energy systems geared for use in optimal operation. The book particularly focuses on reviewing novel operating strategies supported by relevant code in MATLAB and GAMS. It covers foundational concepts, key challenges and opportunities in operational implementation, followed by discussions of conventional approaches to modeling electricity, heat and gas networks. This modeling is the base for more detailed operation strategies for optimal operation of integrated multi-energy systems under uncertainty covered in the latter part of the work. Reviews advanced modeling approaches relevant to the integration of electricity, heat and gas systems in operation studies Covers stochastic and robust optimal operation of integrated multi-energy systems Evaluates MPC based, real-time dispatch of integrated multi-energy systems Considers uncertainty modeling for stochastic and robust optimization Assesses optimal operation and real-time dispatch for multi-energy building complexes

Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty discusses core concepts, advanced modeling and key operation strategies for integrated multi-energy systems geared for use in optimal operation. The book particularly focuses on reviewing novel operating strategies supported by relevant code in MATLAB and GAMS. It covers foundational concepts, key challenges and opportunities in operational implementation, followed by discussions of conventional approaches to modeling electricity, heat and gas networks. This modeling is the base for more detailed operation strategies for optimal operation of integrated multi-energy systems under uncertainty covered in the latter part of the work.- Reviews advanced modeling approaches relevant to the integration of electricity, heat and gas systems in operation studies- Covers stochastic and robust optimal operation of integrated multi-energy systems- Evaluates MPC based, real-time dispatch of integrated multi-energy systems- Considers uncertainty modeling for stochastic and robust optimization- Assesses optimal operation and real-time dispatch for multi-energy building complexes

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc. Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc. Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.