Machine Learning Approaches to Non-Intrusive Load Monitoring

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Publisher : Springer Nature
ISBN 13 : 3030307824
Total Pages : 135 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Machine Learning Approaches to Non-Intrusive Load Monitoring by : Roberto Bonfigli

Download or read book Machine Learning Approaches to Non-Intrusive Load Monitoring written by Roberto Bonfigli and published by Springer Nature. This book was released on 2019-11-01 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on Smart Grids has recently focused on the energy monitoring issue, with the objective of maximizing the user consumption awareness in building contexts on the one hand, and providing utilities with a detailed description of customer habits on the other. In particular, Non-Intrusive Load Monitoring (NILM), the subject of this book, represents one of the hottest topics in Smart Grid applications. NILM refers to those techniques aimed at decomposing the consumption-aggregated data acquired at a single point of measurement into the diverse consumption profiles of appliances operating in the electrical system under study. This book provides a status report on the most promising NILM methods, with an overview of the publically available dataset on which the algorithm and experiments are based. Of the proposed methods, those based on the Hidden Markov Model (HMM) and the Deep Neural Network (DNN) are the best performing and most interesting from the future improvement point of view. One method from each category has been selected and the performance improvements achieved are described. Comparisons are made between the two reference techniques, and pros and cons are considered. In addition, performance improvements can be achieved when the reactive power component is exploited in addition to the active power consumption trace.

Machine Learning for Non-intrusive Load Monitoring

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (116 download)

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Book Synopsis Machine Learning for Non-intrusive Load Monitoring by : Matthias Kahl

Download or read book Machine Learning for Non-intrusive Load Monitoring written by Matthias Kahl and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Non-Intrusive Load Monitoring (NILM)

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Non-Intrusive Load Monitoring (NILM) by : Timo Bernard

Download or read book Non-Intrusive Load Monitoring (NILM) written by Timo Bernard and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Smart Grids – Fundamentals and Technologies in Electricity Networks

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Author :
Publisher : Springer
ISBN 13 : 3642451209
Total Pages : 412 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Smart Grids – Fundamentals and Technologies in Electricity Networks by : Bernd M. Buchholz

Download or read book Smart Grids – Fundamentals and Technologies in Electricity Networks written by Bernd M. Buchholz and published by Springer. This book was released on 2014-07-08 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient transmission and distribution of electricity is a fundamental requirement for sustainable development and prosperity. The world is facing great challenges regarding the reliable grid integration of renewable energy sources in the 21st century. The electric power systems of the future require fundamental innovations and enhancements to meet these challenges. The European Union’s “Smart Grid” vision provides a first overview of the appropriate deep-paradigm changes in the transmission, distribution and supply of electricity. The book brings together common themes beginning with Smart Grids and the characteristics of new power plants based on renewable energy and /or highly efficient generation principles. It covers the advanced technologies applied today in the transmission and distribution networks and innovative solutions for maintaining today’s high power quality under the challenging conditions of large-scale shares of volatile renewable energy sources in the annual energy balance. Besides considering the new primary and secondary technology solutions and control facilities for the transmission and distribution networks, prospective market conditions allowing network operators and the network users to gain benefits are also discussed. The growing role of information and communication technologies is investigated. The importance of new standards is underlined and the current international efforts in developing a consistent set of standards are described in detail. The presentation of international experiences to apply novel Smart Grid solutions to the practice of network operation concludes this book. The authors of the book worked for many years to develop Smart Grid solutions within national and international projects and to introduce them in the practice of network operations.

Adaptive and Natural Computing Algorithms

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Publisher : Springer Science & Business Media
ISBN 13 : 3642202667
Total Pages : 418 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Adaptive and Natural Computing Algorithms by : Andrej Dobnikar

Download or read book Adaptive and Natural Computing Algorithms written by Andrej Dobnikar and published by Springer Science & Business Media. This book was released on 2011-03-03 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 6593 and 6594 constitutes the refereed proceedings of the 10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The 83 revised full papers presented were carefully reviewed and selected from a total of 144 submissions. The second volume includes 41 papers organized in topical sections on pattern recognition and learning, soft computing, systems theory, support vector machines, and bioinformatics.

Microgrid Technologies

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Publisher : John Wiley & Sons
ISBN 13 : 1119710790
Total Pages : 562 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Microgrid Technologies by : C. Sharmeela

Download or read book Microgrid Technologies written by C. Sharmeela and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microgrid technology is an emerging area, and it has numerous advantages over the conventional power grid. A microgrid is defined as Distributed Energy Resources (DER) and interconnected loads with clearly defined electrical boundaries that act as a single controllable entity concerning the grid. Microgrid technology enables the connection and disconnection of the system from the grid. That is, the microgrid can operate both in grid-connected and islanded modes of operation. Microgrid technologies are an important part of the evolving landscape of energy and power systems. Many aspects of microgrids are discussed in this volume, including, in the early chapters of the book, the various types of energy storage systems, power and energy management for microgrids, power electronics interface for AC & DC microgrids, battery management systems for microgrid applications, power system analysis for microgrids, and many others. The middle section of the book presents the power quality problems in microgrid systems and its mitigations, gives an overview of various power quality problems and its solutions, describes the PSO algorithm based UPQC controller for power quality enhancement, describes the power quality enhancement and grid support through a solar energy conversion system, presents the fuzzy logic-based power quality assessments, and covers various power quality indices. The final chapters in the book present the recent advancements in the microgrids, applications of Internet of Things (IoT) for microgrids, the application of artificial intelligent techniques, modeling of green energy smart meter for microgrids, communication networks for microgrids, and other aspects of microgrid technologies. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of microgrids, this is a must-have for any library.

2019 IEEE Power & Energy Society General Meeting (PESGM).

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Publisher :
ISBN 13 : 9781728119816
Total Pages : pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis 2019 IEEE Power & Energy Society General Meeting (PESGM). by :

Download or read book 2019 IEEE Power & Energy Society General Meeting (PESGM). written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Smart and Sustainable Energy Systems and Applications

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Author :
Publisher : MDPI
ISBN 13 : 303928889X
Total Pages : 258 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Artificial Intelligence for Smart and Sustainable Energy Systems and Applications by : Miltiadis D. Lytras

Download or read book Artificial Intelligence for Smart and Sustainable Energy Systems and Applications written by Miltiadis D. Lytras and published by MDPI. This book was released on 2020-05-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.

Machine Learning Classification Techniques for Non-intrusive Load Monitoring

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Machine Learning Classification Techniques for Non-intrusive Load Monitoring by : Jefferson Chung

Download or read book Machine Learning Classification Techniques for Non-intrusive Load Monitoring written by Jefferson Chung and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-intrusive load monitoring is the concept of determining the operational loads using single-point sensing. The features contained within the electrical load's signal are used to identify a unique signature which is used by a machine learning classifier to automate the load identification process. In this thesis, existing machine learning classification techniques are reviewed within the context of the non-intrusive load monitoring application. A non-intrusive load monitoring algorithm is developed in this to extract the prominent hidden features contained within the electrical load's signal which helps identify the operation of different appliances from a single point of an electrical circuit. Decision tree and Naïve Bayes classifiers are used as the machine learning classification technique to automate the load classification process. The co-testing of machine learning classifiers was introduced in this work to improve the classification accuracy of previously seen methods when applying the one-against-the-rest testing approach. When the proposed NILM algorithm was applied to a real test system, a classification accuracy of 99.61% for decision tree and 99.38% for Naïve Bayes was obtained. When compared to previous methods in literature utilizing one-against-the-rest testing approach, a classification accuracy of 76.31% for decision tree and 67.44% for Naïve Bayes was obtained. The results demonstrate the effectiveness of the proposed non-intrusive load monitoring approach through the notable significant increase in the observed classification accuracies.

Artificial Intelligence Techniques for a Scalable Energy Transition

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Publisher : Springer
ISBN 13 : 9783030427283
Total Pages : 382 pages
Book Rating : 4.4/5 (272 download)

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Book Synopsis Artificial Intelligence Techniques for a Scalable Energy Transition by : Moamar Sayed-Mouchaweh

Download or read book Artificial Intelligence Techniques for a Scalable Energy Transition written by Moamar Sayed-Mouchaweh and published by Springer. This book was released on 2021-06-21 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).

Deep Learning Applications in Non-intrusive Load Monitoring

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Publisher :
ISBN 13 :
Total Pages : 72 pages
Book Rating : 4.:/5 (131 download)

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Book Synopsis Deep Learning Applications in Non-intrusive Load Monitoring by : Alon Harell

Download or read book Deep Learning Applications in Non-intrusive Load Monitoring written by Alon Harell and published by . This book was released on 2020 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Intrusive Load Monitoring (NILM) is a technique for inferring the power consumption of each appliance within a home from one central meter, aiding in energy conservation. In this thesis I present several Deep Learning solutions for NILM, starting with two preliminary works - A proof of concept project for multisensory NILM on a Raspberry Pi; and a fully developed NILM solution named WaveNILM. Despite their success, both methods struggled to generalize outside their training data, a common problem in NILM. To improve generalization, I designed a framework for synthesizing truly novel appliance level power signatures based on generative adversarial networks (GAN) - the main project of this thesis. This generator, named PowerGAN, is trained using a variety of GAN techniques. I present a comparison of PowerGAN to other data synthesis work in the context of NILM and demonstrate that PowerGAN is able to create truly synthetic, realistic, diverse, appliance power signatures.

Neural Fuzzy Control Systems With Structure And Parameter Learning

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Publisher : World Scientific Publishing Company
ISBN 13 : 9813104708
Total Pages : 152 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Neural Fuzzy Control Systems With Structure And Parameter Learning by : Chin-teng Lin

Download or read book Neural Fuzzy Control Systems With Structure And Parameter Learning written by Chin-teng Lin and published by World Scientific Publishing Company. This book was released on 1994-02-08 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

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Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Active Learning Framework for Non-Intrusive Load Monitoring: Preprint by :

Download or read book Active Learning Framework for Non-Intrusive Load Monitoring: Preprint written by and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically request user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.

2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

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Publisher :
ISBN 13 : 9781665449670
Total Pages : pages
Book Rating : 4.4/5 (496 download)

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Book Synopsis 2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE) by : IEEE Staff

Download or read book 2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE) written by IEEE Staff and published by . This book was released on 2021-11-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Control and Systems, Energy and Environment, Industrial Informatics and Computational Intelligence, Power Electronics, Signal and Information Processing

Non-intrusive Load Monitoring

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Author :
Publisher : Springer Nature
ISBN 13 : 9811518602
Total Pages : 288 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Non-intrusive Load Monitoring by : Hui Liu

Download or read book Non-intrusive Load Monitoring written by Hui Liu and published by Springer Nature. This book was released on 2019-12-12 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on non-intrusive load monitoring techniques in the area of smart grids and smart buildings, this book presents a thorough introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load monitoring techniques are highly promising in terms of their energy-saving and carbon emission reduction potential. The book is structured clearly and written concisely. It introduces each aspect of these techniques with a number of examples, helping readers to understand and use the corresponding results. It provides latest strengths on the non-intrusive load monitoring techniques for engineers and managers of relevant departments. It also offers extensive information and a source of inspiration for researchers and students, while outlining future research directions.

Improved Non-intrusive Load Monitoring Approaches Using the Multi-gate Mixture of Expert System and the Transformer Deep Learning Model

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (138 download)

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Book Synopsis Improved Non-intrusive Load Monitoring Approaches Using the Multi-gate Mixture of Expert System and the Transformer Deep Learning Model by : Yi Jing

Download or read book Improved Non-intrusive Load Monitoring Approaches Using the Multi-gate Mixture of Expert System and the Transformer Deep Learning Model written by Yi Jing and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

2021 6th Asia Conference on Power and Electrical Engineering (ACPEE)

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Publisher :
ISBN 13 : 9781728191607
Total Pages : pages
Book Rating : 4.1/5 (916 download)

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Book Synopsis 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE) by : IEEE Staff

Download or read book 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE) written by IEEE Staff and published by . This book was released on 2021-04-08 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of ACPEE 2021 includes all the topics related to smart grid, Power Market , Power Disaster and Protection, New Energy, Energy IOT and Electrical engineering equipments