Artificial Intelligence supported Power Quality Prediction and Mitigation PDF Download
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Author: Adrian Eisenmann
Publisher: BoD – Books on Demand
ISBN: 3758390591
Category : Technology & Engineering
Languages : en
Pages : 195
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Book Description
This thesis introduces a fully data driven approach for the prediction and optimization of critical electrical grid states due to poor power quality. Therefore, a nonvolatile memory model for time series forecasting, designed to profit especially from big data bases and complex pattern use cases as well as an Artificial Intelligence based Smart Demand Side Management framework to enable system inherent resources / components for minimization of harmonic disturbances is applied to measured power grid scenarios.
Author: Adrian Eisenmann
Publisher: BoD – Books on Demand
ISBN: 3758390591
Category : Technology & Engineering
Languages : en
Pages : 195
Get Book Here
Book Description
This thesis introduces a fully data driven approach for the prediction and optimization of critical electrical grid states due to poor power quality. Therefore, a nonvolatile memory model for time series forecasting, designed to profit especially from big data bases and complex pattern use cases as well as an Artificial Intelligence based Smart Demand Side Management framework to enable system inherent resources / components for minimization of harmonic disturbances is applied to measured power grid scenarios.
Author: Adrian Eisenmann
Publisher: BoD – Books on Demand
ISBN: 3756812332
Category :
Languages : en
Pages : 196
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Book Description
This thesis introduces a fully data driven approach for the prediction and optimization of critical electrical grid states due to poor power quality. Therefore, a nonvolatile memory model for time series forecasting, designed to profit especially from big data bases and complex pattern use cases as well as an Artificial Intelligence based Smart Demand Side Management framework to enable system inherent resources / components for minimization of harmonic disturbances is applied to measured power grid scenarios.
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3031224566
Category : Computers
Languages : en
Pages : 255
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Book Description
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.
Author: Surender Reddy Salkuti
Publisher: Springer Nature
ISBN: 9819920663
Category : Technology & Engineering
Languages : en
Pages : 584
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Book Description
This book provides a brief insight of various challenges and its mitigation techniques in microgrid due to power quality (PQ) issues. The central concept of this book revolves around the PQ issues in microgrid. The main objective of this book is to make aware of the power and control engineers with different innovative techniques to mitigate the challenges due to PQ issues in microgrid. The topics covered in this book are PQ disturbances in microgrid and different recent and innovative schemes to mitigate them. The book emphasizes technical issues, theoretical background, and practical applications that drive postgraduates, researchers, and practicing engineers with right advanced skills, vision, and knowledge in finding microgrid power quality issues, various technical challenges and providing mitigation techniques for the future sustainable microgrids.
Author: Neelu Nagpal
Publisher: CRC Press
ISBN: 1000963977
Category : Computers
Languages : en
Pages : 250
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Book Description
In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI business models.
Author: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35
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Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Author: Hasmat Malik
Publisher: Springer Nature
ISBN: 9811575711
Category : Technology & Engineering
Languages : en
Pages : 830
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Book Description
This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.
Author: Ilias Maglogiannis
Publisher: Springer Nature
ISBN: 3030791572
Category : Computers
Languages : en
Pages : 507
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Book Description
This book constitutes the refereed proceedings of six International Workshops held as parallel events of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, virtually and in Hersonissos, Crete, Greece, in June 2021: the 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021; Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021; Workshop on Defense Applications of AI, DAAI 2021; Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021; Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021; and the 10th Mining Humanistic Data Workshop, MHDW 2021. The 24 full papers and 16 short papers presented at these workshops were carefully reviewed and selected from 72 submissions. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and AI in modern 5G-oriented telecommunications infrastructures. The papers chosen for AI-BIO 2021 present research on the subject of AI, in its broadest sense, in biomedical engineering and health informatics. The DAAI 2021 papers aim at presenting recent evolutions in artificial intelligence applicable to defense and security applications. The papers selected for DARE 2021 address a variety of pertinent and challenging topics within the scope of distributed AI for resource-constrained platforms. The papers presented at EEAI 2021 aim to bring together interdisciplinary approaches that focus on the application of AI-driven solutions for increasing and improving energy efficiency of residential and tertiary buildings and of occupant behavior. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series.
Author: Wojciech Zamojski
Publisher: Springer Nature
ISBN: 3031618572
Category :
Languages : en
Pages : 375
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Book Description
Author: Alaa El Din Mahmoud
Publisher: CRC Press
ISBN: 100082974X
Category : Technology & Engineering
Languages : en
Pages : 311
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Book Description
Artificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.
