Franklin

Advances in electric power and energy systems : load and price forecasting / edited by Mohamed E. El-Hawary.

Publication:
Hoboken, New Jersey : Wiley, 2017.
Format/Description:
Book
1 online resource (310 pages) : illustrations.
Series:
IEEE Press series on power engineering.
IEEE Press series on power engineering
Distribution:
[Piscataqay, New Jersey] : IEEE Xplore, [2017]
Status/Location:
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Other records:
Subjects:
Electric power systems.
Form/Genre:
Electronic books.
System Details:
Mode of access: World Wide Web
Summary:
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.
Contents:
Introduction / Mohamed E El-Hawary
Univariate Methods for Short-Term Load Forecasting / James W Taylor, Patrick E McSharry
Application of the Weighted Nearest Neighbor Method to Power System Forecasting Problems / Antonio Gâomez-Expâosito, Alicia Troncoso, Jesâus M Riquelme-Santos, Catalina Gâomez-Quiles, Josâe L Martâinez-Ramos, Josâe C Riquelme
Electricity Prices as a Stochastic Process / Yunhe Hou, Chen-Ching Liu, Harold Salazar
Short-Term Forecasting of Electricity Prices Using Mixed Models / Carolina Garcâia-Martos, Julio Rodrâiguez, Marâia Jesâus Sâanchez
Electricity Price Forecasting Using Neural Networks and Similar Days / Paras Mandal, Anurag K Srivastava, Tomonobu Senjyu, Michael Negnevitsky
Estimation of Post-Storm Restoration Times for Electric Power Distribution Systems / Rachel A Davidson, Haibin Liu, Tatiyana V Apanasovich
A Nonparametric Approach for River Flow Forecasting Based on Autonomous Neural Network Models / Vitor Hugo Ferreira, Alexandre P Alves da Silva.
Notes:
Includes index.
Includes bibliographical references at the end of each chapters and index.
Description based on online resource; title from PDF title page (ebrary, viewed July 15, 2017).
Contributor:
El-Hawary, M. E., editor.
ISBN:
1-119-30896-8
1-119-26029-9
OCLC:
992577142
Publisher Number:
10.1002/9781119260295 doi
Access Restriction:
Restricted to subscribers or individual electronic text purchasers.