Electrical Load Forecasting

Produk Detail:
  • Author : S.A. Soliman
  • Publisher : Elsevier
  • Pages : 440 pages
  • ISBN : 9780123815446
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Electrical Load Forecasting

Download or Read online Electrical Load Forecasting full in PDF, ePub and kindle. this book written by S.A. Soliman and published by Elsevier which was released on 26 May 2010 with total page 440 pages. We cannot guarantee that Electrical Load Forecasting book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Electrical Load Forecasting

Electrical Load Forecasting
  • Author : S.A. Soliman,Ahmad Mohammad Al-Kandari
  • Publisher : Elsevier
  • Release : 26 May 2010
GET THIS BOOK Electrical Load Forecasting

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

Spatial Electric Load Forecasting

Spatial Electric Load Forecasting
  • Author : H. Lee Willis
  • Publisher : CRC Press
  • Release : 09 August 2002
GET THIS BOOK Spatial Electric Load Forecasting

Containing 12 new chapters, this second edition offers increased coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of

Short term Electrical Load Forecasting for an Institutional industrial Power System Using an Artificial Neural Network

Short term Electrical Load Forecasting for an Institutional industrial Power System Using an Artificial Neural Network
  • Author : Eric Lynn Taylor
  • Publisher : Unknown
  • Release : 03 July 2022
GET THIS BOOK Short term Electrical Load Forecasting for an Institutional industrial Power System Using an Artificial Neural Network

For optimal power system operation, electrical generation must follow electrical load demand. The generation, transmission, and distribution utilities require some means to forecast the electrical load so they can utilize their electrical infrastructure efficiently, securely, and economically. The short-term load forecast (STLF) represents the electric load forecast for a time interval of a few hours to a few days. This thesis will define STLF as a 24-hour-ahead load forecast whose results will provide an hourly electric load forecast in kilowatts (

Spatial Electric Load Forecasting

Spatial Electric Load Forecasting
  • Author : H. Lee Willis
  • Publisher : CRC Press
  • Release : 09 August 2002
GET THIS BOOK Spatial Electric Load Forecasting

Containing 12 new chapters, this second edition offers increased coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of

Short Term Load Forecasting 2019

Short Term Load Forecasting 2019
  • Author : Antonio Gabaldón,María Carmen Ruiz-Abellón,Luis Alfredo Fernández-Jiménez
  • Publisher : MDPI
  • Release : 26 February 2021
GET THIS BOOK Short Term Load Forecasting 2019

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

Neural Network Computing for the Electric Power Industry

Neural Network Computing for the Electric Power Industry
  • Author : Dejan J. Sobajic
  • Publisher : Psychology Press
  • Release : 17 June 2013
GET THIS BOOK Neural Network Computing for the Electric Power Industry

Power system computing with neural networks is one of the fastest growing fields in the history of power system engineering. Since 1988, a considerable amount of work has been done in investigating computing capabilities of neural networks and understanding their relevance to providing efficient solutions for outstanding complex problems of the electric power industry. A principal objective of a power utility is to provide electric energy to its customers in a secure, reliable and economic manner. Toward this aim, utility personnel

Soft Computing

Soft Computing
  • Author : Devendra K. Chaturvedi
  • Publisher : Springer Science & Business Media
  • Release : 20 August 2008
GET THIS BOOK Soft Computing

This book is an introduction to some new fields in soft computing with its principal components of fuzzy logic, ANN and EA. The approach in this book is to provide an understanding of the soft computing field and to work through soft computing using examples. It also aims to integrate pseudo-code operational summaries and Matlab codes, to present computer simulation, to include real world applications and to highlight the distinctive work of human consciousness in machine.

Electric Load Forecasting Using an Artificial Neural Networks

Electric Load Forecasting Using an Artificial Neural Networks
  • Author : Natalia Gotman,Galina Shumilova,Tatiana Starceva
  • Publisher : LAP Lambert Academic Publishing
  • Release : 01 March 2014
GET THIS BOOK Electric Load Forecasting Using an Artificial Neural Networks

Electric load forecasting is an important research field in electric power industry. It plays a crucial role in solving a wide range of tasks of short-term planning and operating control of electric power system operating modes. Load forecasting is carried out in different time spans. Load forecasting within a current day - operating forecasting; one-day-week-month-ahead load forecasting - short-term load forecasting; one-month-quarter-year-ahead load forecasting - long-term load forecasting. So far a great number of both conventional and non-conventional electric load

Intelligent Data Engineering and Automated Learning IDEAL 2007

Intelligent Data Engineering and Automated Learning   IDEAL 2007
  • Author : Hujun Yin,Peter Tino,Xin Yao,Emilio Corchado,Will Byrne
  • Publisher : Springer Science & Business Media
  • Release : 10 December 2007
GET THIS BOOK Intelligent Data Engineering and Automated Learning IDEAL 2007

This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007, held in Birmingham, UK, in December 2007. The 170 revised full papers presented were carefully reviewed and selected from more than 270 submissions. The papers are organized in topical sections on learning and information processing, data mining and information management, bioinformatics and neuroinformatics, agents and distributed systems, financial engineering and modeling, agent-based approach to service sciences, as well as neural-evolutionary fusion algorithms and their