Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system’s stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.
This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
This book addresses the emerging paradigm of data-driven engineering design. In the big-data era, data is becoming a strategic asset for global manufacturers. This book shows how the power of data can be leveraged to drive the engineering design process, in particular, the early-stage design. Based on novel combinations of standing design methodology and the emerging data science, the book presents a collection of theoretically sound and practically viable design frameworks, which are intended to address a variety of critical design activities including conceptual design, complexity management, smart customization, smart product design, product service integration, and so forth. In addition, it includes a number of detailed case studies to showcase the application of data-driven engineering design. The book concludes with a set of promising research questions that warrant further investigation. Given its scope, the book will appeal to a broad readership, including postgraduate students, researchers, lecturers, and practitioners in the field of engineering design.
The beginning of Genesis in the Bible speaks of: God created all living beings and made light on the first day. At first, the earth was empty and chaotic, the abyss was dark, and the Spirit of God was running on the water. God said, there must be light! There is light. The Qinghai-Tibet Plateau, with an average elevation of over 4,000 meters, is the closest place on Earth to the sky. Although the air here is scarce and unsuitable for survival, the bright sunshine and the holy mountains and lakes here still nurture all living creatures, as well as a strong and great ethical group---Tibetan. They use the most persistent belief from hearts to guard the pure land in the process of human civilization. They use their lives to create a broad and profound historical culture, like the light of the sky, brilliant and glorious. Han Yuchen, a light chaser from the East. He devoted all the emotions in his heart to this place and created a series of excellent oil paintings with the sincerest reverence and worship. The intensive refraction of light and shadow in the work collides with our visions and stings our souls. The ordinary and noble characters living on the roof of the world, telling us the stories of love and faith, kindness and redemption, forbearance and sublimation, give us the enlightenment and the power of life. From this we found the complexity of life, the comfort of the soul, and return to simple joy. The following stories not only recorded the journey of Han Yuchen’s creative journeys, but also the discovery and exploration of Tibetan customs, and the pursuit for holy light.
Climate change poses an unprecedented challenge to the world economy and the global financial system. This paper sets out to understand and quantify the impact of climate mitigation, with a focus on climate-related news, which represents an important information source that investors use to revise their subjective assessments of climate risks. Using full-text data from Financial Times from January 2005 to March 2022, we develop machine learning-based indicators to measure risks from climate mitigation, and the direction of the risk is identified through manual labels. The documented risk premium indicates that climate mitigation news has been partially priced in the Canadian stock market. More specifically, stock prices react positively to market-wide climate-favorable news but they do not react negatively to climate-unfavorable news. The results are robust to different model specifications and across equity markets.
Appraisal is the way language users express their attitude towards things, people, behaviour or ideas. In the last few decades, significant achievements have been made in Appraisal Theory research, yet little attention has been paid to appraisal in scientific texts, especially in relation to the contrast to how it is applied in English and Chinese. This title examines the similarities and differences of Appraisal systems in English and Chinese scientific research articles. Using a self-constructed corpus of scientific research articles, the authors make cross-linguistic comparisons in terms of the quantity and distribution patterns of categories of appraisals. They creatively categorise articles into theoretical scientific research articles and applied studies and discover that for both languages, each genre can have its own favorite mode of distribution for the realization of appraisal systems. In addition, this research helps appraisal theory systems to become more explicit, specific, and more applicable for the analysis of scientific research articles. Students and scholars of applied linguistics, comparative linguistics and corpus linguistics will find this an essential reference.
The moment she fell, she was schemed by her classmates to become a 'miss'.He had thought that things would end like this.Who knew that the man would actually come to her door and say, "Since you've taken the money, shouldn't you serve me?
Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system’s stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.
Climate change poses an unprecedented challenge to the world economy and the global financial system. This paper sets out to understand and quantify the impact of climate mitigation, with a focus on climate-related news, which represents an important information source that investors use to revise their subjective assessments of climate risks. Using full-text data from Financial Times from January 2005 to March 2022, we develop machine learning-based indicators to measure risks from climate mitigation, and the direction of the risk is identified through manual labels. The documented risk premium indicates that climate mitigation news has been partially priced in the Canadian stock market. More specifically, stock prices react positively to market-wide climate-favorable news but they do not react negatively to climate-unfavorable news. The results are robust to different model specifications and across equity markets.
This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
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