| data science for energy transition: Data Science Applied to Sustainability Analysis Jennifer Dunn, Prasanna Balaprakash, 2021-05-11 Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses |
| data science for energy transition: Empowering the Great Energy Transition Scott Valentine, Benjamin K. Sovacool, Marilyn Brown, 2019-12-17 At a time when climate-change deniers hold the reins of power in the United States and international greenhouse gas negotiations continue at a slow crawl, what options are available to cities, companies, and consumers around the world who seek a cleaner future? Scott Victor Valentine, Marilyn A. Brown, and Benjamin K. Sovacool explore developments and strategies that will help fast-track the transition to renewable energy. They provide an expert analysis of the achievable steps that citizens, organizational leaders, and policy makers can take to put their commitments to sustainability into practice. Empowering the Great Energy Transition examines trends that suggest a transition away from carbon-intensive energy sources is inevitable—there are too many forces for change at work to stop a shift to clean energy. Yet under the status quo, change will be too slow to avert the worst consequences of climate change. Humanity is on a path to incur avoidable social, environmental, and economic costs. Valentine, Brown, and Sovacool argue that new policies and business models are needed to surmount the hurdles separating the current consumption model from a sustainable energy future. Empowering the Great Energy Transition shows that with well-placed efforts, we can set humanity on a course that supports entrepreneurs and communities in mitigating the environmental harm caused by technologies whose time has come and gone. |
| data science for energy transition: The Material Basis of Energy Transitions Alena Bleicher, Alexandra Pehlken, 2020-08-05 The Material Basis of Energy Transitions explores the intersection between critical raw material provision and the energy system. Chapters draw on examples and case studies involving energy technologies (e.g., electric power, transport) and raw material provision (e.g., mining, recycling), and consider these in their regional and global contexts. The book critically discusses issues such as the notion of criticality in the context of a circular economy, approaches for estimating the need for raw materials, certification schemes for raw materials, the role of consumers, and the impact of renewable energy development on resource conflicts. Each chapter deals with a specific issue that characterizes the interdependency between critical raw materials and renewable energies by examining case studies from a particular conceptual perspective. The book is a resource for students and researchers from the social sciences, natural sciences, and engineering, as well as interdisciplinary scholars interested in the field of renewable energies, the circular economy, recycling, transport, and mining. The book is also of interest to policymakers in the fields of renewable energy, recycling, and mining, professionals from the energy and resource industries, as well as energy experts and consultants looking for an interdisciplinary assessment of critical materials. - Provides a comprehensive overview of key issues related to the nexus between renewable energy and critical raw materials - Explores interdisciplinary perspectives from the natural sciences, engineering, and social sciences - Discusses critical strategies to address the nexus from a practitioner's perspective |
| data science for energy transition: Machine Learning and Data Science in the Power Generation Industry Patrick Bangert, 2021-01-14 Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. - Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful - Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them - Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems - Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls |
| data science for energy transition: Energy Transitions Vaclav Smil, 2010-05-26 This bold and controversial argument shows why energy transitions are inherently complex and prolonged affairs, and how ignoring this fact raises unrealistic expectations that the United States and other global economies can be weaned quickly from a primary dependency on fossil fuels. Energy transitions are fundamental processes behind the evolution of human societies: they both drive and are driven by technical, economic, and social changes. In a bold and provocative argument, Energy Transitions: History, Requirements, Prospects describes the history of modern society's dependence on fossil fuels and the prospects for the transition to a nonfossil world. Vaclav Smil, who has published more on various aspects of energy than any working scientist, makes it clear that this transition will not be accomplished easily, and that it cannot be accomplished within the timetables established by the Obama administration. The book begins with a survey of the basic properties of modern energy systems. It then offers detailed explanations of universal patterns of energy transitions, the peculiarities of changing energy use in the world's leading economies, and the coming shifts from fossil fuels to renewable conversions. Specific cases of these transitions are analyzed for eight of the world's leading energy consumers. The author closes with perspectives on the nature and pace of the coming energy transition to renewable conversions. |
| data science for energy transition: Urban Energy Transition Peter Droege, 2011-09-06 This compendium of 29 chapters from 18 countries contains both fundamental and advanced insight into the inevitable shift from cities dominated by the fossil-fuel systems of the industrial age to a renewable-energy based urban development framework. The cross-disciplinary handbook covers a range of diverse yet relevant topics, including: carbon emissions policy and practice; the role of embodied energy; urban thermal performance planning; building efficiency services; energy poverty alleviation efforts; renewable community support networks; aspects of household level bio-fuel markets; urban renewable energy legislation, programs and incentives; innovations in individual transport systems; global urban mobility trends; implications of intelligent energy networks and distributed energy supply and storage; and the case for new regional monetary systems and lifestyles. Presented are practical and principled aspects of technology, economics, design, culture and society, presenting perspectives that are both local and international in scope and relevance. |
| data science for energy transition: Energy Transitions Olivier Labussière, Alain Nadaï, 2018-04-30 This book elucidates what it means to transition to alternative sources of energy and discusses the potential for this energy transition to be a more democratic process. The book dynamically describes a recent sociotechnical study of a number of energy transitions occurring in several countries - France, Germany and Tunisia, and involving different energy technologies - including solar, on/off-shore wind, smart grids, biomass, low-energy buildings, and carbon capture and storage. Drawing on a pragmatist tradition of social inquiry, the authors examine the consequences of energy transition processes for the actors and entities that are affected by them, as well as the spaces for political participation they offer. This critical inquiry is organised according to foundational categories that have defined the energy transition - ‘renewable’ energy resources, markets, economic instruments, technological demonstration, spatiality (‘scale’) and temporality (‘horizon(s)’). Using a set of select case studies, this book systematically investigates the role these categories play in the current developments in energy transitions. |
| data science for energy transition: Pilot Society and the Energy Transition Marianne Ryghaug, Tomas Moe Skjølsvold, 2020-11-23 This open access book examines the role of pilot and demonstration projects as crucial devices for conducting innovation in the context of the energy transition. Bridging literature from sustainability transitions and Science and Technology Studies (STS), it argues that such projects play a crucial role, not only in shaping future energy and mobility systems, but in transforming societies more broadly. Pilot projects constitute socio-technical configurations where imagined future realities are materialized. With this as a backdrop, the book explores pilot projects as political entities, focusing on questions of how they gain their legitimacy, which resources are mobilized in their production, and how they can serve as sites of public participation and the production of energy citizenship. The book argues that such projects too often have a narrow technology focus, and that this is a missed opportunity. The book concludes by critically discussing the potential roles of research and innovation policy in transforming how such projects are configured and conducted. |
| data science for energy transition: The Role of Public Participation in Energy Transitions Ortwin Renn, Frank Ulmer, Anna Deckert, 2020-03-21 The Role of Public Participation in Energy Transitions provides a conceptual and empirical approach to stakeholder and citizen involvement in the ongoing energy transition conversation, focusing on projects surrounding energy conversion and efficiency, reducing energy demand, and using new forms of renewable energy sources. Sections review and contrast different approaches to citizen involvement, discuss the challenges of inclusive participation in complex energy policymaking, and provide conceptual foundations for the empirical case studies that constitute the second part of the book. The book is a valuable resource for academics in the field of energy planning and policymaking, as well as practitioners in energy governance, energy and urban planners and participation specialists. |
| data science for energy transition: Political Economies of Energy Transition Kathryn Hochstetler, 2020-11-26 Shows that economic concerns about jobs, costs, and consumption, rather than climate change, are likely to drive energy transition in developing countries. |
| data science for energy transition: Urban Energy Transition Peter Droege, 2018-08-17 Urban Energy Transition, second edition, is the definitive science and practice-based compendium of energy transformations in the global urban system. This volume is a timely and rich resource for all, as citizens, companies and their communities, from remote villages to megacities and metropolitan regions, rapidly move away from fossil fuel and nuclear power, to renewable energy as civic infrastructure investment, source of revenue and prosperity, and existential resilience strategy. |
| data science for energy transition: Data Science of Renewable Energy Integration Yuichi Ikeda, |
| data science for energy transition: The 4Ds of Energy Transition Muhammad Asif, 2022-07-18 The 4Ds of Energy Transition Enables readers to understand technology-driven approaches that address the challenges of today’s energy scenario and the shift towards sustainable energy transition This book provides a comprehensive account of the characteristics of energy transition, covering the latest advancements, trends, and practices around the topic. It charts the path to global energy sustainability based on existing technology by focusing on the four dynamic approaches of decarbonization, decreasing use, decentralization, and digitalization, plus the important technical, economic, social and policy perspectives surrounding those approaches. Each technology is demonstrated with an introduction and a set of specific chapters. The work appropriately incorporates up-to-date data, case studies, and comparative assessments to further aid in reader comprehension. Sample topics discussed within the work by key thinkers and researchers in the broader fields of energy include: Renewable energy and sustainable energy future Decarbonization in energy sector Hydrogen and fuel cells Electric mobility and sustainable transportation Energy conservation and management Distributed and off-grid generation, energy storage, and batteries Digitalization in energy sector; smart meters, smart grids, blockchain This book is an ideal professional resource for engineers, academics, and policy makers working in areas related to the development of energy solutions. |
| data science for energy transition: The Political Economy of Clean Energy Transitions Douglas Arent, Channing Arndt, Mackay Miller, Finn Tarp, Owen Zinaman, 2017 A volume on the political economy of clean energy transition in developed and developing regions, with a focus on the issues that different countries face as they transition from fossil fuels to lower carbon technologies. |
| data science for energy transition: Energy and Civilization Vaclav Smil, 2018-11-13 A comprehensive account of how energy has shaped society throughout history, from pre-agricultural foraging societies through today's fossil fuel–driven civilization. I wait for new Smil books the way some people wait for the next 'Star Wars' movie. In his latest book, Energy and Civilization: A History, he goes deep and broad to explain how innovations in humans' ability to turn energy into heat, light, and motion have been a driving force behind our cultural and economic progress over the past 10,000 years. —Bill Gates, Gates Notes, Best Books of the Year Energy is the only universal currency; it is necessary for getting anything done. The conversion of energy on Earth ranges from terra-forming forces of plate tectonics to cumulative erosive effects of raindrops. Life on Earth depends on the photosynthetic conversion of solar energy into plant biomass. Humans have come to rely on many more energy flows—ranging from fossil fuels to photovoltaic generation of electricity—for their civilized existence. In this monumental history, Vaclav Smil provides a comprehensive account of how energy has shaped society, from pre-agricultural foraging societies through today's fossil fuel–driven civilization. Humans are the only species that can systematically harness energies outside their bodies, using the power of their intellect and an enormous variety of artifacts—from the simplest tools to internal combustion engines and nuclear reactors. The epochal transition to fossil fuels affected everything: agriculture, industry, transportation, weapons, communication, economics, urbanization, quality of life, politics, and the environment. Smil describes humanity's energy eras in panoramic and interdisciplinary fashion, offering readers a magisterial overview. This book is an extensively updated and expanded version of Smil's Energy in World History (1994). Smil has incorporated an enormous amount of new material, reflecting the dramatic developments in energy studies over the last two decades and his own research over that time. |
| data science for energy transition: The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations Aboul Ella Hassanien, Ashraf Darwish, 2023-03-11 This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications. |
| data science for energy transition: Public Affairs Information Service Bulletin , 1971 |
| data science for energy transition: Data Science and Social Research N. Carlo Lauro, Enrica Amaturo, Maria Gabriella Grassia, Biagio Aragona, Marina Marino, 2017-11-17 This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices. |
| data science for energy transition: Future of Utilities - Utilities of the Future Fereidoon Sioshansi, 2016-03-15 Future of Utilities - Utilities of the Future: How technological innovations in distributed generation will reshape the electric power sector relates the latest information on the electric power sector its rapid transformation, particularly on the distribution network and customer side. Trends like the rapid rise of self-generation and distributed generation, microgrids, demand response, the dissemination of electric vehicles and zero-net energy buildings that promise to turn many consumers into prosumers are discussed. The book brings together authors from industry and academic backgrounds to present their original, cutting-edge and thought-provoking ideas on the challenges currently faced by electric utilities around the globe, the opportunities they present, and what the future might hold for both traditional players and new entrants to the sector. The book's first part lays out the present scenario, with concepts such as an integrated grid, microgrids, self-generation, customer-centric service, and pricing, while the second part focuses on how innovation, policy, regulation, and pricing models may come together to form a new electrical sector, exploring the reconfiguring of the current institutions, new rates design in light of changes to retail electricity markets and energy efficiency, and the cost and benefits of integration of distributed or intermittent generation, including coupling local renewable energy generation with electric vehicle fleets. The final section projects the future function and role of existing electrical utilities and newcomers to this sector, looking at new pathways for business and pricing models, consumer relations, technology, and innovation. - Contains discussions that help readers understand the underlying causes and drivers of change in the electrical sector, and what these changes mean in financial, operational, and regulatory terms - Provides thought-provoking ideas on the challenges currently faced by electric utilities around the globe, the opportunities they present, and what the future might hold for both traditional players and new entrants to the sector - Helps readers anticipate what developments are likely to define the function and role of the utility of the future |
| data science for energy transition: Handbook of Research on Developing Smart Cities Based on Digital Twins Del Giudice, Matteo, Osello, Anna, 2021-01-15 The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment. |
| data science for energy transition: Apply Data Science Thomas Barton, Christian Müller, 2023-01-01 This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown.The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. |
| data science for energy transition: Data Science and Machine Learning Applications in Subsurface Engineering Daniel Asante Otchere, 2024-02-06 This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary focus of the field of machine learning (ML). ML aims to develop data-driven methods and computational algorithms that can learn to identify complex and non-linear patterns to understand and predict the relationships between variables by analysing extensive data. Although ML models provide the final output for predictions, several steps need to be performed to achieve accurate predictions. These steps, data pre-processing, feature selection, feature engineering and outlier removal, are all contained in this book. New models are also developed using existing ML architecture and learning theories to improve the performance of traditional ML models and handle small and big data without manual adjustments. This research-oriented book will help subsurface engineers, geophysicists, and geoscientists become familiar with data science and ML advances relevant to subsurface engineering. Additionally, it demonstrates the use of data-driven approaches for salt identification, seismic interpretation, estimating enhanced oil recovery factor, predicting pore fluid types, petrophysical property prediction, estimating pressure drop in pipelines, bubble point pressure prediction, enhancing drilling mud loss, smart well completion and synthetic well log predictions. |
| data science for energy transition: The Geopolitics of the Global Energy Transition Manfred Hafner, Simone Tagliapietra, 2020-06-09 The world is currently undergoing an historic energy transition, driven by increasingly stringent decarbonisation policies and rapid advances in low-carbon technologies. The large-scale shift to low-carbon energy is disrupting the global energy system, impacting whole economies, and changing the political dynamics within and between countries. This open access book, written by leading energy scholars, examines the economic and geopolitical implications of the global energy transition, from both regional and thematic perspectives. The first part of the book addresses the geopolitical implications in the world’s main energy-producing and energy-consuming regions, while the second presents in-depth case studies on selected issues, ranging from the geopolitics of renewable energy, to the mineral foundations of the global energy transformation, to governance issues in connection with the changing global energy order. Given its scope, the book will appeal to researchers in energy, climate change and international relations, as well as to professionals working in the energy industry. |
| data science for energy transition: The Great Transition: Shifting from Fossil Fuels to Solar and Wind Energy Lester R. Brown, 2015-04-20 The great energy transition from fossil fuels to renewable sources of energy is under way. As oil insecurity deepens, the extraction risks of fossil fuels rise, and concerns about climate instability cast a shadow over the future of coal, a new world energy economy is emerging. The old economy, fueled by oil, natural gas, and coal is being replaced with one powered by wind, solar, and geothermal energy. The Great Transition details the accelerating pace of this global energy revolution. As many countries become less enamored with coal and nuclear power, they are embracing an array of clean, renewable energies. Whereas solar energy projects were once small-scale, largely designed for residential use, energy investors are now building utility-scale solar projects. Strides are being made: some of the huge wind farm complexes under construction in China will each produce as much electricity as several nuclear power plants, and an electrified transport system supplemented by the use of bicycles could reshape the way we think about mobility. |
| data science for energy transition: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| data science for energy transition: Transition to Renewable Energy Systems Detlef Stolten, Viktor Scherer, 2013-05-13 In this ready reference, top academic researchers, industry players and government officers join forces to develop commercial concepts for the transition from current nuclear or fossil fuel-based energy to renewable energy systems within a limited time span. They take into account the latest science and technology, including an analysis of the feasibility and impact on the environment, economy and society. In so doing, they discuss such complex topics as electrical and gas grids, fossil power plants and energy storage technologies. The contributions also include robust, conceivable and breakthrough technologies that will be viable and implementable by 2020. |
| data science for energy transition: Energy Transition Syed Abdul Rehman Khan, Mirela Panait, Felix Puime Guillen, Lukman Raimi, 2022-08-29 This book opens up a critical dimension of energy transition taking in account multidimensional challenges on economic, social and environmental fields. The book discusses the trends in the field of energy transition and evolving practices adopted by public authorities and companies for betterment of environment and society. The editors (4) identify directions and challenges involved in the energy transition. The novelty of this book is the multidisciplinary approach, being presented the economic, social and environmental challenges involved in the energy transition. The energy transition is accompanied by a complex process of changing attitudes and behaviors of energy consumers and producers. The consequences are profound not only economically and environmentally but also socially, renewable energy being a solution for energy poverty reduction and development of rural communities. Therefore, certain social and environmental problems generated by energy poverty are solved by using renewable energy. Moreover, the complexity of the phenomenon is presented not only in terms of the analysis of the main sources of renewable energy but also the ethical aspects involved in the use of sources such as biofuels. In the case of this source, the main problem is whether the use of certain agricultural products for the production of biofuels threatens food security, especially in rural areas. All categories of stakeholders must show responsibility and get involved in this complex process which requires a remarkable technical and financial effort. The energy transition can offer innovative solutions through which the impact of economic activity on the environment is minimized, and in this way, industrial ecology achieves its objectives to support sustainable development. The demands imposed by industrial ecology must shape not only the behavior of oil and gas companies but also of entities involved in the production and consumption of renewable energy. Given the negative externalities generated, companies in the fossil fuel sector have become increasingly socially responsible, their social and environmental performance (non-financial) being presented in detail in the annual sustainability reports to inform stakeholders. Therefore, this book is an important read not only for scholars, but also for those who are interested in ensuring an environmentally sustainable future taking in account energy transition challenges. |
| data science for energy transition: Wind and Solar Energy Transition in China Marius Korsnes, 2019-09-25 This book explores the mobilisation of China’s wind and solar industries and examines the implications of this development to energy generation and distribution, innovation and governance. Unlike other publications that focus mainly on the formal policy landscape and statistics of industry development, this book delves deeper into the ways in which the wind and solar industries have evolved through negotiations made by the involved stakeholders, and how these industries play into larger Chinese development and policymaking interests. Overall, it sheds new light on the strategic development of China’s renewable energy industry, the flexible governance methods employed and the internal struggles which Chinese local, regional and central policymakers, and state-owned and private enterprises have faced. This book will be of great relevance to students and scholars of renewable energy technologies, energy policy and sustainability transitions, as well as policymakers with a specific interest in China. |
| data science for energy transition: Governing the Energy Transition Geert Verbong, Derk Loorbach, 2012-03-29 The Energy Transition, the inevitable shift away from cheap, centralized, largely fossil-based energy systems, is one of the core challenges of our time. This book provides a coherent and novel insight into the nature of this challenge and possible strategies to accelerate and guide such transitions. It brings together prominent European scholars and practitioners from the fields of energy transition research and governance to draw attention to the current complex dynamics in the energy domain, and offer elegant and provocative explanations for current crises and lock-ins. They identify multiple energy transition pathways that emerge and increasingly compete, and emphasize the need and possibilities for novel governance. By analysing the complexity of energy transition processes and the difficulties in shifting to sustainable pathways, this text questions the extent to which actually governing energy transitions is already reality, just an illusion, or a bare necessity. |
| data science for energy transition: Shaping an Inclusive Energy Transition Margot P. C. Weijnen, Zofia Lukszo, Samira Farahani, 2021-08-05 This open access book makes a case for a socially inclusive energy transition and illustrates how engineering and public policy professionals can contribute to shaping an inclusive energy transition, building on a socio-technical systems engineering approach. Accomplishing a net-zero greenhouse gas emissions economy in 2050 is a daunting challenge. This book explores the challenges of the energy transition from the perspectives of technological innovation, public policy, social values and ethics. It elaborates on two particular gaps in the design of public policy interventions focused on decarbonization of the energy system and discusses how both could be remedied. First, the siloed organization of public administration fails to account for the many interdependencies between the energy sector, the mobility system, digital infrastructure and the built environment. Cross-sector coordination of policies and policy instruments is needed to avoid potentially adverse effects upon society and the economy, which may hamper the energy transition rather than accelerate it. Second, energy and climate policies pay insufficient attention to the social values at stake in the energy transition. In addressing these gaps, this book intends to inspire decision makers engaged in the energy transition to embrace the transition as an opportunity to bring a more inclusive society into being. |
| data science for energy transition: Data Science for Entrepreneurship Werner Liebregts, Willem-Jan van den Heuvel, Arjan van den Born, 2023-03-23 The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited by entrepreneurs. This book provides a detailed, yet practical, introduction to the fundamental principles of data science and how entrepreneurs and would-be entrepreneurs can take advantage of it. It walks the reader through sections on data engineering, and data analytics as well as sections on data entrepreneurship and data use in relation to society. The book also offers ways to close the research and practice gaps between data science and entrepreneurship. By having read this book, students of entrepreneurship courses will be better able to commercialize data-driven ideas that may be solutions to real-life problems. Chapters contain detailed examples and cases for a better understanding. Discussion points or questions at the end of each chapter help to deeply reflect on the learning material. |
| data science for energy transition: 100% Renewable Energy Transition Claudia Kemfert, Christian Breyer, Pao-Yu Oei, 2020-01-23 Energy markets are already undergoing considerable transitions to accommodate new (renewable) energy forms, new (decentral) energy players, and new system requirements, e.g. flexibility and resilience. Traditional energy markets for fossil fuels are therefore under pressure, while not-yet-mature (renewable) energy markets are emerging. As a consequence, investments in large-scale and capital intensive (traditional) energy production projects are surrounded by high uncertainty, and are difficult to hedge by private entities. Traditional energy production companies are transforming into energy service suppliers and companies aggregating numerous potential market players are emerging, while regulation and system management are playing an increasing role. To address these increasing uncertainties and complexities, economic analysis, forecasting, modeling and investment assessment require fresh approaches and views. Novel research is thus required to simulate multiple actor interplays and idiosyncratic behavior. The required approaches cannot deal only with energy supply, but need to include active demand and cover systemic aspects. Energy market transitions challenge policy-making. Market coordination failure, the removal of barriers hindering restructuring and the combination of market signals with command-and-control policy measures are some of the new aims of policies. The aim of this Special Issue is to collect research papers that address the above issues using novel methods from any adequate perspective, including economic analysis, modeling of systems, behavioral forecasting, and policy assessment. The issue will include, but is not be limited to: Local control schemes and algorithms for distributed generation systems Centralized and decentralized sustainable energy management strategies Communication architectures, protocols and properties of practical applications Topologies of distributed generation systems improving flexibility, efficiency and power quality Practical issues in the control design and implementation of distributed generation systems Energy transition studies for optimized pathway options aiming for high levels of sustainability |
| data science for energy transition: Sustainametrics - envisioning a sustainable future with data science Shutaro Takeda, Alexander Ryota Keeley, Shunsuke Managi, Thomas Gloria, 2023-03-08 |
| data science for energy transition: Sustainable Energy Transition for Cities Miguel Amado, Francesca Poggi, 2022-04-29 Sustainable Energy Transition for Cities brings together empirical and applied research in both urban planning and sustainable energy, offering coherent and innovative best practices for urban energy transition planning. Using a multidisciplinary framework, the book views cities as an integrated system composed of components such as neighborhoods and districts within an overall net-zero energy balance. Intended for academics, practitioners and policymakers interested in sustainable energy transition, the book offers insights and best practices to promote the transition to a low carbon urban society. - Includes real-world case studies from around the globe - Examines replicable tools such as GIS, BIM and the E-City Platform for developing and implementing energy-efficient urban models - Provides learning aids such as figures, maps, conceptual models, operative schemes, literature reviews, guideline tables, extensive bibliography, and links |
| data science for energy transition: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery Kailong Liu, Yujie Wang, Xin Lai, 2022-04-08 This open access book comprehensively consolidates studies in the rapidly emerging field of battery management. The primary focus is to overview the new and emerging data science technologies for full-lifespan management of Li-ion batteries, which are categorized into three groups, namely (i) battery manufacturing management, (ii) battery operation management, and (iii) battery reutilization management. The key challenges, future trends as well as promising data-science technologies to further improve this research field are discussed. As battery full-lifespan (manufacturing, operation, and reutilization) management is a hot research topic in both energy and AI fields and none specific book has focused on systematically describing this particular from a data science perspective before, this book can attract the attention of academics, scientists, engineers, and practitioners. It is useful as a reference book for students and graduates working in related fields. Specifically, the audience could not only get the basics of battery manufacturing, operation, and reutilization but also the information of related data-science technologies. The step-by-step guidance, comprehensive introduction, and case studies to the topic make it accessible to audiences of different levels, from graduates to experienced engineers. |
| data science for energy transition: Renewables Michael Aklin, Johannes Urpelainen, 2018-03-23 A comprehensive political analysis of the rapid growth in renewable wind and solar power, mapping an energy transition through theory, case studies, and policy. Wind and solar are the most dynamic components of the global power sector. How did this happen? After the 1973 oil crisis, the limitations of an energy system based on fossil fuels created an urgent need to experiment with alternatives, and some pioneering governments reaped political gains by investing heavily in alternative energy such as wind or solar power. Public policy enabled growth over time, and economies of scale brought down costs dramatically. In this book, Michaël Aklin and Johannes Urpelainen offer a comprehensive political analysis of the rapid growth in renewable wind and solar power, mapping an energy transition through theory, case studies, and policy analysis. Aklin and Urpelainen argue that, because the fossil fuel energy system and political support for it are so entrenched, only an external shock—an abrupt rise in oil prices, or a nuclear power accident, for example—allows renewable energy to grow. They analyze the key factors that enable renewable energy to withstand political backlash, andt they draw on this analyisis to explain and predict the development of renewable energy in different countries over time. They examine the pioneering efforts in the United States, Germany, and Denmark after the 1973 oil crisis and other shocks; explain why the United States surrendered its leadership role in renewable energy; and trace the recent rapid growth of modern renewables in electricity generation, describing, among other things, the return of wind and solar to the United States. Finally, they apply the lessons of their analysis to contemporary energy policy issues. |
| data science for energy transition: Bio-Inspired Data-driven Distributed Energy in Robotics and Enabling Technologies Abhishek Kumar, Hemant Kumar Saini, Ashutosh Kumar Dubey, Vicente García Díaz, 2024-12-10 This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems. This book: Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities. Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems. Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things. Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum. Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem. The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering. |
| data science for energy transition: Hydrogen Production and Energy Transition Marcel Van de Voorde, 2021-09-07 Carbon neutral hydrogen technologies play a key role in preventing climate change. Maximizing production of hydrogen in a clean and efficient manner is critical to the hydrogen economy. This book describes most of the potential hydrogen processing technologies and presents the state-of the- art and future developments of modern hydrogen technologies. Attention has been given to the theoretical aspects, thermodynamics, process calculations, and modeling approaches, new technologies and reports of multiple successful new pilot systems. The book should appeal to a brad readership and ideal for students of materials science, chemistry, physics; for researchers, chemical- and mechanical engineering, for industrialists, policymakers, economics, safety agencies and governments. |
| data science for energy transition: How to Avoid a Climate Disaster Bill Gates, 2021-02-16 NEW YORK TIMES BESTSELLER NATIONAL BESTSELLER In this urgent, singularly authoritative book, Bill Gates sets out a wide-ranging, practical--and accessible--plan for how the world can get to zero greenhouse gas emissions in time to avoid an irreversible climate catastrophe. Bill Gates has spent a decade investigating the causes and effects of climate change. With the help and guidance of experts in the fields of physics, chemistry, biology, engineering, political science and finance, he has focused on exactly what must be done in order to stop the planet's slide toward certain environmental disaster. In this book, he not only gathers together all the information we need to fully grasp how important it is that we work toward net-zero emissions of greenhouse gases but also details exactly what we need to do to achieve this profoundly important goal. He gives us a clear-eyed description of the challenges we face. He describes the areas in which technology is already helping to reduce emissions; where and how the current technology can be made to function more effectively; where breakthrough technologies are needed, and who is working on these essential innovations. Finally, he lays out a concrete plan for achieving the goal of zero emissions--suggesting not only policies that governments should adopt, but what we as individuals can do to keep our government, our employers and ourselves accountable in this crucial enterprise. As Bill Gates makes clear, achieving zero emissions will not be simple or easy to do, but by following the guidelines he sets out here, it is a goal firmly within our reach. |
| data science for energy transition: Energy Pardeep Singh, Suruchi Singh, Gaurav Kumar, Pooja Baweja, 2021-09-06 Energy Global energy demand has more than doubled since 1970. The use of energy is strongly related to almost every conceivable aspect of development: wealth, health, nutrition, water, infrastructure, education and even life expectancy itself are strongly and significantly related to the consumption of energy per capita. Many development indicators are strongly related to per-capita energy consumption. Fossil fuel is the most conventional source of energy but also increases greenhouse gas emissions. The economic development of many countries has come at the cost of the environment. However, it should not be presumed that a reconciliation of the two is not possible. The nexus concept is the interconnection between the resource energy, water, food, land, and climate. Such interconnections enable us to address trade-offs and seek synergies among them. Energy, water, food, land, and climate are essential resources of our natural environment and support our quality of life. Competition between these resources is increasing globally and is exacerbated by climate change. Improving resilience and securing resource availability would require improving resource efficiency. Many policies and programs are announced nationally and internationally for replacing the conventional mode and also emphasizing on conservation of fossil fuels and reuse of exhausted energy, so a gap in implications and outcomes can be broadly traced by comparing the data. This book aims to highlight problems and solutions related to conventional energy utilization, formation, and multitudes of ecological impacts and tools for the conservation of fossil fuels. The book also discusses modern energy services as one of the sustainable development goals and how the pressure on resource energy disturbs the natural flows. The recent advances in alternative energy sources and their possible future growth are discussed and on how conventional energy leads to greenhouse gas formation, which reduces energy use efficiency. The different policies and models operating is also addressed, and the gaps that remained between them. Climate change poses a challenge for renewable energy, and thus it is essential to identify the factors that would reduce the possibility of relying on sustainable energy sources. This book will be of interest to researchers and stakeholders, students, industries, NGOs, and governmental agencies directly or indirectly associated with energy research. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
