Short-Term Load Forecasting by Artificial Intelligent Technologies

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Publisher : MDPI
ISBN 13 : 3038975826
Total Pages : 445 pages
Book Rating : 4.0/5 (389 download)

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Book Synopsis Short-Term Load Forecasting by Artificial Intelligent Technologies by : Wei-Chiang Hong

Download or read book Short-Term Load Forecasting by Artificial Intelligent Technologies written by Wei-Chiang Hong and published by MDPI. This book was released on 2019-01-29 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Short-Term Load Forecasting by Artificial Intelligent Technologies" that was published in Energies

Short-Term Load Forecasting by Artificial Intelligent Technologies

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Publisher :
ISBN 13 : 9783038975830
Total Pages : 1 pages
Book Rating : 4.9/5 (758 download)

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Book Synopsis Short-Term Load Forecasting by Artificial Intelligent Technologies by : Guo-Feng Fan

Download or read book Short-Term Load Forecasting by Artificial Intelligent Technologies written by Guo-Feng Fan and published by . This book was released on 2019 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency analysis, load flow analysis, planning, and maintenance of power systems. There are lots of forecasting models proposed for STLF, including traditional statistical models (such as ARIMA, SARIMA, ARMAX, multi-variate regression, Kalman filter, exponential smoothing, and so on) and artificial-intelligence-based models (such as artificial neural networks (ANNs), knowledge-based expert systems, fuzzy theory and fuzzy inference systems, evolutionary computation models, support vector regression, and so on). Recently, due to the great development of evolutionary algorithms (EA) and novel computing concepts (e.g., quantum computing concepts, chaotic mapping functions, and cloud mapping process, and so on), many advanced hybrids with those artificial-intelligence-based models are also proposed to achieve satisfactory forecasting accuracy levels. In addition, combining some superior mechanisms with an existing model could empower that model to solve problems it could not deal with before; for example, the seasonal mechanism from the ARIMA model is a good component to be combined with any forecasting models to help them to deal with seasonal problems.

Short-Term Load Forecasting 2019

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Publisher : MDPI
ISBN 13 : 303943442X
Total Pages : 324 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Short-Term Load Forecasting 2019 by : Antonio Gabaldón

Download or read book Short-Term Load Forecasting 2019 written by Antonio Gabaldón and published by MDPI. This book was released on 2021-02-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these research areas. The deployment of enabling technologies (e.g., smart meters) has made high-granularity data available for many customer segments and to approach many issues, for instance, to make forecasting tasks feasible at several demand aggregation levels. The first challenge is the improvement of STLF models and their performance at new aggregation levels. Moreover, the mix of renewables in the power system, and the necessity to include more flexibility through demand response initiatives have introduced greater uncertainties, which means new challenges for STLF in a more dynamic power system in the 2030–50 horizon. Many techniques have been proposed and applied for STLF, including traditional statistical models and AI techniques. Besides, distribution planning needs, as well as grid modernization, have initiated the development of hierarchical load forecasting. Analogously, the need to face new sources of uncertainty in the power system is giving more importance to probabilistic load forecasting. This Special Issue deals with both fundamental research and practical application research on STLF methodologies to face the challenges of a more distributed and customer-centered power system.

Recurrent Neural Networks for Short-Term Load Forecasting

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Author :
Publisher : Springer
ISBN 13 : 3319703382
Total Pages : 72 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Recurrent Neural Networks for Short-Term Load Forecasting by : Filippo Maria Bianchi

Download or read book Recurrent Neural Networks for Short-Term Load Forecasting written by Filippo Maria Bianchi and published by Springer. This book was released on 2017-11-09 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series.

Forecasting and Assessing Risk of Individual Electricity Peaks

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Publisher : Springer Nature
ISBN 13 : 303028669X
Total Pages : 108 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Forecasting and Assessing Risk of Individual Electricity Peaks by : Maria Jacob

Download or read book Forecasting and Assessing Risk of Individual Electricity Peaks written by Maria Jacob and published by Springer Nature. This book was released on 2019-09-25 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general.

2020 2nd International Conference on Computer and Information Sciences (ICCIS)

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Publisher :
ISBN 13 : 9781728154688
Total Pages : pages
Book Rating : 4.1/5 (546 download)

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Book Synopsis 2020 2nd International Conference on Computer and Information Sciences (ICCIS) by : IEEE Staff

Download or read book 2020 2nd International Conference on Computer and Information Sciences (ICCIS) written by IEEE Staff and published by . This book was released on 2020-10-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ICCIS will provide a forum for researchers, scientists and engineers to exchange and share their experiences, and research results about all aspects of computer and information science

Artificial Intelligence Technologies and Applications

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Publisher : IOS Press
ISBN 13 : 164368485X
Total Pages : 1158 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Artificial Intelligence Technologies and Applications by : C. Chen

Download or read book Artificial Intelligence Technologies and Applications written by C. Chen and published by IOS Press. This book was released on 2024-02-15 with total page 1158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is rapidly becoming an inescapable part of modern life, and the fact that AI technologies and applications will inevitably bring about significant changes in many industries and economies worldwide means that this field of research is currently attracting great interest. This book presents the proceedings of ICAITA 2023, the 5th International Conference on Artificial Intelligence Technologies and Applications, held as a hybrid event from 30 June to 2 July 2023 in Changchun, China. The conference provided an international forum for academic communication between experts and scholars in the field of AI, promoting the interchange of scientific information between participants and establishing connections which may lead to collaboration, research, and development activities in related fields. The 126 papers included here were selected following a thorough review process and are divided into 4 sections, covering AI simulation and mechatronics; intelligent network architecture and system monitoring; intelligent algorithm modeling and numerical analysis; and intelligent graph recognition and information processing. Topics addressed include artificial neural networks, computational theories of learning, intelligent system architectures, pervasive computing and ambient intelligence, and fuzzy logic and methods. Covering a wide range of topics and applications current in AI research, the book will be of interest to all those working in the field.

Advances in Artificial Intelligence, Big Data and Algorithms

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Publisher : IOS Press
ISBN 13 : 1643684450
Total Pages : 1224 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Advances in Artificial Intelligence, Big Data and Algorithms by : G. Grigoras

Download or read book Advances in Artificial Intelligence, Big Data and Algorithms written by G. Grigoras and published by IOS Press. This book was released on 2023-12-19 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms.

Intelligent Renewable Energy Systems

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Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Intelligent Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and published by John Wiley & Sons. This book was released on 2022-01-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023)

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Author :
Publisher : Springer Nature
ISBN 13 : 9819969565
Total Pages : 381 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023) by : Roumen Kountchev

Download or read book Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023) written by Roumen Kountchev and published by Springer Nature. This book was released on with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hybrid Intelligent Technologies in Energy Demand Forecasting

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Publisher : Springer Nature
ISBN 13 : 3030365298
Total Pages : 179 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Hybrid Intelligent Technologies in Energy Demand Forecasting by : Wei-Chiang Hong

Download or read book Hybrid Intelligent Technologies in Energy Demand Forecasting written by Wei-Chiang Hong and published by Springer Nature. This book was released on 2020-01-01 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.

Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021)

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Publisher : Springer Nature
ISBN 13 : 3030763463
Total Pages : 857 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) by : Aboul Ella Hassanien

Download or read book Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2021-05-28 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco. This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation, AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.

Electrical Load Forecasting

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Publisher : Elsevier
ISBN 13 : 9780123815446
Total Pages : 440 pages
Book Rating : 4.8/5 (154 download)

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Book Synopsis Electrical Load Forecasting by : S.A. Soliman

Download or read book Electrical Load Forecasting written by S.A. Soliman and published by Elsevier. This book was released on 2010-05-26 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Succinct and understandable, this book is a step-by-step guide to the mathematics and construction of electrical load forecasting models. Written by one of the world’s foremost experts on the subject, Electrical Load Forecasting provides a brief discussion of algorithms, their advantages and disadvantages and when they are best utilized. The book begins with a good description of the basic theory and models needed to truly understand how the models are prepared so that they are not just blindly plugging and chugging numbers. This is followed by a clear and rigorous exposition of the statistical techniques and algorithms such as regression, neural networks, fuzzy logic, and expert systems. The book is also supported by an online computer program that allows readers to construct, validate, and run short and long term models. Step-by-step guide to model construction Construct, verify, and run short and long term models Accurately evaluate load shape and pricing Creat regional specific electrical load models

Advanced Computing and Intelligent Technologies

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Publisher : Springer Nature
ISBN 13 : 9819719615
Total Pages : 649 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Advanced Computing and Intelligent Technologies by : Rabindra Nath Shaw

Download or read book Advanced Computing and Intelligent Technologies written by Rabindra Nath Shaw and published by Springer Nature. This book was released on with total page 649 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence and Soft Computing, Part I

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Publisher : Springer Science & Business Media
ISBN 13 : 3642132073
Total Pages : 695 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Artificial Intelligence and Soft Computing, Part I by : Leszek Rutkowski

Download or read book Artificial Intelligence and Soft Computing, Part I written by Leszek Rutkowski and published by Springer Science & Business Media. This book was released on 2010-06 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNAI series reports state-of-the-art results in artificial intelligence research, development, education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelligent information processing including interdisciplinary topics in a variety of application fields.

Intelligent Energy Demand Forecasting

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Publisher : Springer Science & Business Media
ISBN 13 : 1447149688
Total Pages : 203 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Intelligent Energy Demand Forecasting by : Wei-Chiang Hong

Download or read book Intelligent Energy Demand Forecasting written by Wei-Chiang Hong and published by Springer Science & Business Media. This book was released on 2013-03-12 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.

Computational Intelligence and Information Technology

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Publisher : Springer Science & Business Media
ISBN 13 : 364225733X
Total Pages : 900 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Computational Intelligence and Information Technology by : Vinu Das

Download or read book Computational Intelligence and Information Technology written by Vinu Das and published by Springer Science & Business Media. This book was released on 2013-01-02 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First International Conference on Computational Intelligence and Information Technology, CIIT 2011, held in Pune, India, in November 2011. The 58 revised full papers, 67 revised short papers, and 32 poster papers presented were carefully reviewed and selected from 483 initial submissions. The papers are contributed by innovative academics and industrial experts in the field of computer science, information technology, computational engineering, mobile communication and security and offer a stage to a common forum, where a constructive dialog on theoretical concepts, practical ideas and results of the state of the art can be developed.