Short Term Electric Load Forecasting Using Neural Networks

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Short Term Electric Load Forecasting Using Neural Networks

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Author :
language : en
Publisher:
Release Date : 1993

Short Term Electric Load Forecasting Using Neural Networks written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.

Recurrent Neural Networks For Short Term Load Forecasting

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Author : Filippo Maria Bianchi
language : en
Publisher: Springer
Release Date : 2017-11-09

Recurrent Neural Networks For Short Term Load Forecasting written by Filippo Maria Bianchi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Computers categories.

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.

Short Term Electric Load Forecasting Using Artificial Neural Networks

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Author : Eric Lee Daugherty
language : en
Publisher:
Release Date : 1994

Short Term Electric Load Forecasting Using Artificial Neural Networks written by Eric Lee Daugherty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.

Short Term Electric Load Forecasting Using Neural Network Models

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Author : Yasser Al-Rashid
language : en
Publisher:
Release Date : 1995

Short Term Electric Load Forecasting Using Neural Network Models written by Yasser Al-Rashid and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Electric power consumption categories.

Short Term Load Forecasting By Artificial Intelligent Technologies

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Author : Wei-Chiang Hong
language : en
Publisher: MDPI
Release Date : 2019-01-29

Short Term Load Forecasting By Artificial Intelligent Technologies written by Wei-Chiang Hong and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with categories.

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 Electric Load Forecasting Using Neural Network With Fuzzy Set Based Classification

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Author : Gumpanart Bumroonggit
language : en
Publisher:
Release Date : 1995

Short Term Electric Load Forecasting Using Neural Network With Fuzzy Set Based Classification written by Gumpanart Bumroonggit and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with categories.

Electric Load Forecasting Using An Artificial Neural Networks

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Author : Natalia Gotman
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2014-03

Electric Load Forecasting Using An Artificial Neural Networks written by Natalia Gotman and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03 with categories.

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 forecasting methods and models have been developed. The work presents research results of electric load forecasting for electrical power systems using artificial neural networks and fuzzy logic as one of the most advanced and perspective directions of solving this task. A theoretical approach to the issues discussed is combined with the data of experimental studies implemented with application of load curves of regional electrical power systems. The book is addressed to specialists and researchers concerned with operational control modes of electric power systems.

Short Term Electric Load Forecasting By Using Multi Layer Feed Forward Neural Network

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Author : Marvin Herbert Wibisono
language : en
Publisher:
Release Date : 2004

Short Term Electric Load Forecasting By Using Multi Layer Feed Forward Neural Network written by Marvin Herbert Wibisono and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.

Electrical Load Forecasting

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Author : S.A. Soliman
language : en
Publisher: Elsevier
Release Date : 2010-05-26

Electrical Load Forecasting written by S.A. Soliman and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-26 with Business & Economics categories.

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

Short Term Electrical Load Forecasting For An Institutional Industrial Power System Using An Artificial Neural Network

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Author : Eric Lynn Taylor
language : en
Publisher:
Release Date : 2013

Short Term Electrical Load Forecasting For An Institutional Industrial Power System Using An Artificial Neural Network written by Eric Lynn Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.

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 (kW) for the future 24 hours (a 24-hour load profile). This thesis will use the method of Artificial Neural Networks (ANN) to create a STLF algorithm for the U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL). ORNL’s power system can be described as an institutional/industrial-type electrical load. The ANN is a mathematical tool that mimics the thought processes of the human brain. The ANN can be created and trained to receive historical load and future weather forecasts as input and produce a load forecast as its output. Most ANNs in the literature are used to forecast the next day 24-hour load profile for a transmission-level system with resulting load forecast errors ranging from approximately 1 % to 3 %. This research will show that an ANN can be used to forecast the smaller, more chaotic load profile of an institutional/industrial-type power system and results in a similar forecast error range. In addition, the operating bounds of the ORNL electric load will be analyzed along with the weather profiles for the site. Correlations between load and weather and load and calendar descriptors, such as day of week and month, will be used as predictor inputs to the ANN to optimize is size and accuracy.