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.

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.

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.

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

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.

Download or read book Artificial Intelligence Based Forecasting and Analytic Techniques for Environment and Economics Management written by Wendong Yang and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download or read book Lecture Notes in Data Engineering Computational Intelligence and Decision Making written by Sergii Babichev and published by Springer Nature. This book was released on 2022-09-13 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains of 39 scientific papers which include the results of research regarding the current directions in the fields of data mining, machine learning and decision-making. This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning create the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Hybrid Systems and Processes" contains of 11 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 11 ones too. There are 17 papers in the third section "Data Engineering, Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.

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:

Download or read book ECML PKDD 2020 Workshops written by Irena Koprinska and published by Springer Nature. This book was released on 2021-02-01 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the workshops which complemented the 20th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2020. Due to the COVID-19 pandemic the conference and workshops were held online. The 43 papers presented in volume were carefully reviewed and selected from numerous submissions. The volume presents the papers that have been accepted for the following workshops: 5th Workshop on Data Science for Social Good, SoGood 2020; Workshop on Parallel, Distributed and Federated Learning, PDFL 2020; Second Workshop on Machine Learning for Cybersecurity, MLCS 2020, 9th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2020, Workshop on Data Integration and Applications, DINA 2020, Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning, EDML 2020, Second International Workshop on eXplainable Knowledge Discovery in Data Mining, XKDD 2020; 8th International Workshop on News Recommendation and Analytics, INRA 2020. The papers from INRA 2020 are published open access and licensed under the terms of the Creative Commons Attribution 4.0 International License.

Download or read book Computational Intelligence in Power Engineering written by Bijaya Ketan Panigrahi and published by Springer Science & Business Media. This book was released on 2010-09-20 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume deals with different computational intelligence (CI) techniques for solving real world power industry problems. It will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

Download or read book Computational Intelligence in Time Series Forecasting written by Ajoy K. Palit and published by Springer Science & Business Media. This book was released on 2006-01-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.

Download or read book Theory and Applications of Time Series Analysis written by Olga Valenzuela and published by Springer Nature. This book was released on 2020-11-20 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of peer-reviewed contributions on the latest advances in time series analysis, presented at the International Conference on Time Series and Forecasting (ITISE 2019), held in Granada, Spain, on September 25-27, 2019. The first two parts of the book present theoretical contributions on statistical and advanced mathematical methods, and on econometric models, financial forecasting and risk analysis. The remaining four parts include practical contributions on time series analysis in energy; complex/big data time series and forecasting; time series analysis with computational intelligence; and time series analysis and prediction for other real-world problems. Given this mix of topics, readers will acquire a more comprehensive perspective on the field of time series analysis and forecasting. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.

Download or read book Analysis of Energy Systems written by Vincenzo Bianco and published by CRC Press. This book was released on 2017-05-12 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of energy systems is of paramount importance in modern societies, since it is fundamental to guarantee a sustainable economic development. It combines technical and economic research with a specific focus on quantitative modelling, in order to optimize the modalities of energy demand and supply globally. The book covers major advanced topics related to the analysis of energy by considering different aspects, namely management, planning and policies. The most recent trends, such as smart grids, transition from fossil fuels to renewables based energy systems and distributed generation, are also discussed in this book. Intended to be a collection of various contributions from experts all around the world, it includes latest research results, innovations and methodologies about the analysis of energy systems. The book also focuses to contribute to the current debate related to the evolution of energy systems, by discussing in an open way the pro’s and con’s without any pre-constitute point of view. Title is aimed to be a reference for the academic community, students and professionals with a wider interdisciplinary background. Key Features: Presents integration of renewable sources with conventional energy systems. Topic is addressed from a multidisciplinary point of view, i.e. economy, technical, modelling, planning. Investigates management and planning aspects of future energy supplies. Multidimensional nature of energy systems is highlighted and discussed. Contributes towards implementing policy measures to reduce primary energy consumptions and carbon footprint.

Download or read book Machine Learning Techniques for Space Weather written by Enrico Camporeale and published by Elsevier. This book was released on 2018-05-31 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book is a unique and important resource for space physicists, space weather professionals and computer scientists in related fields. - Collects many representative non-traditional approaches to space weather into a single volume - Covers, in an accessible way, the mathematical background that is not often explained in detail for space scientists - Includes free software in the form of simple MATLAB® scripts that allow for replication of results in the book, also familiarizing readers with algorithms

Download or read book Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch written by Yuanzheng Li and published by Springer Nature. This book was released on 2023-05-05 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.

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.