NDLI: An application of ANN in scheduling pumped-storage

Content Provider	IEEE Xplore Digital Library
Author	Li Ruomei Chen Yunping Guo Jianbo
Copyright Year	1995
Description	Author affiliation: Univ. of Manchester Inst. of Sci. & Technol., UK (Li Ruomei)
Abstract	An artificial neural network (ANN) based optimization method in scheduling pumped-storage is proposed in the paper. Short-term scheduling as well as real-time dispatch of a pumped-storage station is a constrained optimization problem. It becomes more complicated when coordinated with other generation resources. The computation time is often long and the operation conditions may change unpredictably. A fast and practical way is expected. The ANN is used as a signal processing device, which represents mapping functions from input space to output space. Through a training process, multi-layered feedforward and neural networks can be used to approximate the continuous functions with a given accuracy and real-time solution can be achieved. In this paper three layer feedforward ANN and improved BP algorithm are adopted to solve the problem of pumped-storage scheduling. A set of ANN training data are obtained by running an optimization software. The paper describes how to select and organize the input data and how to train the ANN. A work example is presented and a comparison with traditional method is made. It shows that a fast and accurate solution for pumped-storage scheduling can be achieved with ANN.
Starting Page	85
Ending Page	90
File Size	418499
Page Count	6
File Format	PDF
ISBN	0780329813
DOI	10.1109/EMPD.1995.500705
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-11-21
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Processor scheduling Signal processing algorithms Optimization methods Constraint optimization Signal mapping Neural networks Multi-layer neural network Feedforward neural networks Scheduling algorithm
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

An algorithm for the automatic generation of neural network structures

A neural network's learning algorithm based on interval optimization

Handling precedence constraints with neural network based real-time scheduling algorithms

Topology and parameter optimization of ANN using genetic algorithm for application of textiles

A Novel Hybrid Evolutionary Algorithm Based on PSO and AFSA for Feedforward Neural Network Training

Research and Application of PSO-Based BP Neural Network in the Project Estimate of Government Investment

Application of artificial neural network in optimal design of step motor

Fast global optimization neural network and its application in data fusion

Dynamic node creation and fast learning algorithm for a hybrid feedforward neural network

An application of ANN in scheduling pumped-storage

Similar Documents

An algorithm for the automatic generation of neural network structures

A neural network's learning algorithm based on interval optimization

Handling precedence constraints with neural network based real-time scheduling algorithms

Topology and parameter optimization of ANN using genetic algorithm for application of textiles

A Novel Hybrid Evolutionary Algorithm Based on PSO and AFSA for Feedforward Neural Network Training

Research and Application of PSO-Based BP Neural Network in the Project Estimate of Government Investment

Application of artificial neural network in optimal design of step motor

Fast global optimization neural network and its application in data fusion

Dynamic node creation and fast learning algorithm for a hybrid feedforward neural network

An application of ANN in scheduling pumped-storage