Zhe Zhang – författare

Wind Energy Systems: Control, Optimization, and Market Strategies, the latest volume in the Elsevier Wind Energy Engineering series, presents in-depth coverage of the technical aspects of controlling and optimizing wind energy resources, including advanced control strategies to enhance anti-disturbance and stable operation. The book begins by introducing wind energy resources in power systems and provides an overview of control, optimization methods, and market strategies. This is followed by individual chapters that detail advanced methods and approaches, moving from traditional centralized electricity grids characterized by source-grid-load systems to systems that integrate storage of energy, thus source-grid-load-storage electricity grids.Users will find cutting-edge knowledge supported by case studies, practical applications, and code. This latest volume will be of interest to those involved in the planning, design, operation, and maintenance of wind energy systems, including researchers, students, faculty, engineers, industry practitioners, and R&D professionals.Shares the latest research findings in the control and optimization of wind energy systems, along with their market strategiesDescribes advanced control strategies of grid-connected wind energy conversion systems in the safe and stable operation of power systemsExamines optimal operation strategies of power systems, considering the uncertainty of wind powerIncludes case studies and real-world examples and provides codes for optimization strategies and algorithms

Wind Energy Systems: Control, Optimization, and Market Strategies, the latest volume in the Elsevier Wind Energy Engineering series, presents in-depth coverage of the technical aspects of controlling and optimizing wind energy resources, including advanced control strategies to enhance anti-disturbance and stable operation. The book begins by introducing wind energy resources in power systems and provides an overview of control, optimization methods, and market strategies. This is followed by individual chapters that detail advanced methods and approaches, moving from traditional centralized electricity grids characterized by source-grid-load systems to systems that integrate storage of energy, thus source-grid-load-storage electricity grids.Users will find cutting-edge knowledge supported by case studies, practical applications, and code. This latest volume will be of interest to those involved in the planning, design, operation, and maintenance of wind energy systems, including researchers, students, faculty, engineers, industry practitioners, and R&D professionals. - Shares the latest research findings in the control and optimization of wind energy systems, along with their market strategies- Describes advanced control strategies of grid-connected wind energy conversion systems in the safe and stable operation of power systems- Examines optimal operation strategies of power systems, considering the uncertainty of wind power- Includes case studies and real-world examples and provides codes for optimization strategies and algorithms

This book focuses on undergraduate student engagement in China and the UK. It offers an innovative perspective on this aspect, which, although pervasive, is not always acknowledged by its users to be complex and multidimensional in nature, firmly rooted in cultural, social and disciplinary norms, and difficult to measure. Competition within the global higher education market has become increasingly intense amongst universities; and the higher education sector in China, currently the largest source of international students, is beginning to compete strongly for its home market. Against this consumerist background, student engagement, with its close relation to positive learning outcomes, is increasingly receiving attention from higher education managers and researchers who seek to improve the quality of their ‘products’.The research study on which the book is based draws on three courses, two in China and one in the UK. It offers a binary perspective across twovery different cultures (Western and Confucian) and two very different subject areas (Chinese language and mathematics). The study employs a mixed-methods design and develops a conceptual framework derived from statistical and thematic analysis. An original theoretical lens, combining a bioecological perspective (Bronfenbrenner) and a sociocultural one (Holland et al.’s Figured Worlds), adds further interpretive power to help understand the construct of student engagement.

This book focuses on undergraduate student engagement in China and the UK. It offers an innovative perspective on this aspect, which, although pervasive, is not always acknowledged by its users to be complex and multidimensional in nature, firmly rooted in cultural, social and disciplinary norms, and difficult to measure. Competition within the global higher education market has become increasingly intense amongst universities; and the higher education sector in China, currently the largest source of international students, is beginning to compete strongly for its home market. Against this consumerist background, student engagement, with its close relation to positive learning outcomes, is increasingly receiving attention from higher education managers and researchers who seek to improve the quality of their ‘products’.The research study on which the book is based draws on three courses, two in China and one in the UK. It offers a binary perspective across twovery different cultures (Western and Confucian) and two very different subject areas (Chinese language and mathematics). The study employs a mixed-methods design and develops a conceptual framework derived from statistical and thematic analysis. An original theoretical lens, combining a bioecological perspective (Bronfenbrenner) and a sociocultural one (Holland et al.’s Figured Worlds), adds further interpretive power to help understand the construct of student engagement.

Understand how to use MLOps as an engineering discipline to help with the challenges of bringing machine learning models to production quickly and consistently. This book will help companies worldwide to adopt and incorporate machine learning into their processes and products to improve their competitiveness.The book delves into this engineering discipline's aspects and components and explores best practices and case studies. Adopting MLOps requires a sound strategy, which the book's early chapters cover in detail. The book also discusses the infrastructure and best practices of Feature Engineering, Model Training, Model Serving, and Machine Learning Observability. Ray, the open source project that provides a unified framework and libraries to scale machine learning workload and the Python application, is introduced, and you will see how it fits into the MLOps technical stack.This book is intended for machine learning practitioners, such as machine learning engineers, and data scientists, who wish to help their company by adopting, building maps, and practicing MLOps. What You'll LearnGain an understanding of the MLOps disciplineKnow the MLOps technical stack and its componentsGet familiar with the MLOps adoption strategyUnderstand feature engineering Who This Book Is ForMachine learning practitioners, data scientists, and software engineers who are focusing on building machine learning systems and infrastructure to bring ML models to production