A Model for Short Term Electric Load Forecasting

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Publisher :
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4.:/5 (66 download)

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Book Synopsis A Model for Short Term Electric Load Forecasting by : John Robert Tigue

Download or read book A Model for Short Term Electric Load Forecasting written by John Robert Tigue and published by . This book was released on 1975 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Electrical Load Forecasting

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Publisher : Elsevier
ISBN 13 : 0123815444
Total Pages : 441 pages
Book Rating : 4.1/5 (238 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 441 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

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.

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

Recurrent Neural Networks for Short-Term Load Forecasting

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Publisher : Springer
ISBN 13 : 3319703382
Total Pages : 74 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 74 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.

Applied Mathematics for Restructured Electric Power Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 0387234713
Total Pages : 345 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Applied Mathematics for Restructured Electric Power Systems by : Joe H. Chow

Download or read book Applied Mathematics for Restructured Electric Power Systems written by Joe H. Chow and published by Springer Science & Business Media. This book was released on 2006-06-03 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence consists of chapters based on work presented at a National Science Foundation workshop organized in November 2003. The theme of the workshop was the use of applied mathematics to solve challenging power system problems. The areas included control, optimization, and computational intelligence. In addition to the introductory chapter, this book includes 12 chapters written by renowned experts in their respected fields. Each chapter follows a three-part format: (1) a description of an important power system problem or problems, (2) the current practice and/or particular research approaches, and (3) future research directions. Collectively, the technical areas discussed are voltage and oscillatory stability, power system security margins, hierarchical and decentralized control, stability monitoring, embedded optimization, neural network control with adaptive critic architecture, control tuning using genetic algorithms, and load forecasting and component prediction. This volume is intended for power systems researchers and professionals charged with solving electric and power system problems.

Short-term Electric Load Forecasting Using Neural Network Models

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Publisher :
ISBN 13 :
Total Pages : 142 pages
Book Rating : 4.:/5 (347 download)

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Book Synopsis Short-term Electric Load Forecasting Using Neural Network Models by : Yasser Al-Rashid

Download or read book Short-term Electric Load Forecasting Using Neural Network Models written by Yasser Al-Rashid and published by . This book was released on 1995 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Comparative Models for Electrical Load Forecasting

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Publisher :
ISBN 13 :
Total Pages : 256 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Comparative Models for Electrical Load Forecasting by : Derek W. Bunn

Download or read book Comparative Models for Electrical Load Forecasting written by Derek W. Bunn and published by . This book was released on 1985 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takes a practical look at how short-term forecasting has actually been undertaken and is being developed in public utility organizations.

Functional and Shape Data Analysis

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Publisher : Springer
ISBN 13 : 1493940201
Total Pages : 454 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Functional and Shape Data Analysis by : Anuj Srivastava

Download or read book Functional and Shape Data Analysis written by Anuj Srivastava and published by Springer. This book was released on 2016-10-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges. Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.

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.

Electric Power Systems

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Publisher : CRC Press
ISBN 13 : 1439893969
Total Pages : 462 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Electric Power Systems by : João P. S. Catalão

Download or read book Electric Power Systems written by João P. S. Catalão and published by CRC Press. This book was released on 2017-12-19 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electric Power Systems: Advanced Forecasting Techniques and Optimal Generation Scheduling helps readers develop their skills in modeling, simulating, and optimizing electric power systems. Carefully balancing theory and practice, it presents novel, cutting-edge developments in forecasting and scheduling. The focus is on understanding and solving pivotal problems in the management of electric power generation systems. Methods for Coping with Uncertainty and Risk in Electric Power Generation Outlining real-world problems, the book begins with an overview of electric power generation systems. Since the ability to cope with uncertainty and risk is crucial for power generating companies, the second part of the book examines the latest methods and models for self-scheduling, load forecasting, short-term electricity price forecasting, and wind power forecasting. Toward Optimal Coordination between Hydro, Thermal, and Wind Power Using case studies, the third part of the book investigates how to achieve the most favorable use of available energy sources. Chapters in this section discuss price-based scheduling for generating companies, optimal scheduling of a hydro producer, hydro-thermal coordination, unit commitment with wind generators, and optimal optimization of multigeneration systems. Written in a pedagogical style that will appeal to graduate students, the book also expands on research results that are useful for engineers and researchers. It presents the latest techniques in increasingly important areas of power system operations and planning.

Smart Meter Data Analytics

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Publisher : Springer Nature
ISBN 13 : 9811526249
Total Pages : 306 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Smart Meter Data Analytics by : Yi Wang

Download or read book Smart Meter Data Analytics written by Yi Wang and published by Springer Nature. This book was released on 2020-02-24 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.

Advances in Electric Power and Energy Systems

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Publisher : John Wiley & Sons
ISBN 13 : 1118171349
Total Pages : 324 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Advances in Electric Power and Energy Systems by : Mohamed E. El-Hawary

Download or read book Advances in Electric Power and Energy Systems written by Mohamed E. El-Hawary and published by John Wiley & Sons. This book was released on 2017-07-12 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial arenas. Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every maximization strategy. This book fills a gap in the literature on this increasingly important topic. Following an introductory chapter offering background information necessary for a full understanding of the forecasting issues covered, this book: Introduces advanced methods of time series forecasting, as well as neural networks Provides in-depth coverage of state-of-the-art power system load forecasting and electricity price forecasting Addresses river flow forecasting based on autonomous neural network models Deals with price forecasting in a competitive market Includes estimation of post-storm restoration times for electric power distribution systems Features contributions from world-renowned experts sharing their insights and expertise in a series of self-contained chapters Advances in Electric Power and Energy Systems is a valuable resource for practicing engineers, regulators, planners, and consultants working in or concerned with the electric power industry. It is also a must read for senior undergraduates, graduate students, and researchers involved in power system planning and operation.

Smart Energy and Electric Power Systems

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Publisher : Elsevier
ISBN 13 : 0323916856
Total Pages : 227 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Smart Energy and Electric Power Systems by : Sanjeevikumar Padmanaban

Download or read book Smart Energy and Electric Power Systems written by Sanjeevikumar Padmanaban and published by Elsevier. This book was released on 2022-09-17 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing. Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector. Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand

Short Term Electric Load Forecasting

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Publisher :
ISBN 13 :
Total Pages : 157 pages
Book Rating : 4.:/5 (686 download)

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Book Synopsis Short Term Electric Load Forecasting by : Tao Hong

Download or read book Short Term Electric Load Forecasting written by Tao Hong and published by . This book was released on 2010 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modeling and Forecasting Electricity Loads and Prices

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Publisher : John Wiley & Sons
ISBN 13 : 0470059990
Total Pages : 192 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Modeling and Forecasting Electricity Loads and Prices by : Rafal Weron

Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by John Wiley & Sons. This book was released on 2007-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.