Energy Analytics for Development
Energy Analytics for Development

Author: Energy Sector Management Assistance Programme

Publisher:

Published: 2017

Total Pages:

ISBN-13:

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With unprecedented speed and scale, digital transformation is affecting multiple industries, including energy. A combination of technologies, and a more complex world demanding greater agility and new competences impact all aspects of the energy sector and manifest themselves in changing patterns of consumption, new ways of asset optimization, and cross-industry partnerships. 'Smart solutions' are a product of this transformation and energy data are its source. By nature, the energy sector generates vast amounts of big data through meters, sensor networks, customer payments, credit history, satellite imagery, etc. It is not surprising that private and public energy companies are turning to the idea of leveraging big data analytics for performance optimization and improved service delivery. The transition to a digitized energy sector will not happen on its own, and a number of enablers are required to facilitate this change. Beyond improved digital infrastructure, digital skills and analytics capabilities will need to be strengthened. This new solutions brief aims to encourage the use of big data analytics in the energy sector by outlining opportunities and identify cases for where the use of big data analytics could help better address challenges faced by the energy sector today.

Open Data and Energy Analytics
Open Data and Energy Analytics

Author: Benedetto Nastasi

Publisher: MDPI

Published: 2020-06-25

Total Pages: 218

ISBN-13: 3039362186

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Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

Applied Data Analysis and Modeling for Energy Engineers and Scientists
Applied Data Analysis and Modeling for Energy Engineers and Scientists

Author: T. Agami Reddy

Publisher: Springer Science & Business Media

Published: 2011-08-09

Total Pages: 446

ISBN-13: 1441996133

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Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.

Open Data and Energy Analytics
Open Data and Energy Analytics

Author: Benedetto Nastasi

Publisher:

Published: 2020

Total Pages: 218

ISBN-13: 9783039362196

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Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

Intelligent Data Analytics for Power and Energy Systems
Intelligent Data Analytics for Power and Energy Systems

Author: Hasmat Malik

Publisher: Springer Nature

Published: 2022-02-17

Total Pages: 649

ISBN-13: 9811660816

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This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.

Energy for Development
Energy for Development

Author: Ferenc L. Toth

Publisher: Springer Science & Business Media

Published: 2012-05-02

Total Pages: 253

ISBN-13: 9400741626

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This collection of contributions from a diverse group of prominent international scientists and policy makers brings together their in-depth analyses and innovative ideas about how to resolve the ‘energy for development’ predicament. It includes studies quantifying the role of energy in socioeconomic development, analysis of the interplay between supranational and national institutions in policy implementation, the energy implications of demographic trends such as urbanisation, and exploration of supply-side issues such as the potential role of nuclear energy and ‘cleaning’ fossil fuel energy generation through carbon capture.

Introduction to Energy Analysis
Introduction to Energy Analysis

Author: Kornelis Blok

Publisher: Routledge

Published: 2020-11-17

Total Pages: 282

ISBN-13: 1000214435

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This textbook provides an introduction to energy analysis for those students who want to specialise in this challenging field. In comparison to other textbooks, this book provides a balanced treatment of complete energy systems, covering the demand side, the supply side, and the energy markets that connect these. The emphasis is very much on presenting a range of tools and methodologies that will help students find their way in analysing real world problems in energy systems. This new edition has been updated throughout and contains additional content on energy transitions and improvements in the treatment of several energy systems analysis approaches. Featuring learning objectives, further readings and practical exercises in each chapter, Introduction to Energy Analysis will be essential reading for upper-level undergraduate and postgraduate students with a background in the natural sciences and engineering. This book may also be useful for professionals dealing with energy issues, as a first introduction into the field.

Data Analytics for Smart Grids Applications—A Key to Smart City Development
Data Analytics for Smart Grids Applications—A Key to Smart City Development

Author: Devendra Kumar Sharma

Publisher: Springer Nature

Published: 2024-01-03

Total Pages: 466

ISBN-13: 3031460928

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This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.

Simulation Science
Simulation Science

Author: Nina Gunkelmann

Publisher: Springer Nature

Published: 2020-04-06

Total Pages: 201

ISBN-13: 3030457184

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This book constitutes the refereed proceedings of the Second International Workshop on Simulation Science, held in Clausthal-Zellerfeld, in May 2019. The 12 full papers were carefully reviewed and selected from 47 submissions. The papers are organized according to the following topics: optimization and distributed simulations; simulation of materials; self-organized and porous structures; simulation of materials: finite element and multiscale methods.

Analytics and Optimization for Renewable Energy Integration
Analytics and Optimization for Renewable Energy Integration

Author: Ning Zhang

Publisher: CRC Press

Published: 2019-02-21

Total Pages: 372

ISBN-13: 042984770X

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The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration.The first part presents mathematical theories of stochastic mathematics; the second presents modeling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.