NDLI: Neural Network Based Optimum Model for Cascaded Hydro Power Generating System

Content Provider	IEEE Xplore Digital Library
Author	Gunasekara, C.G.S. Udawatta, L. Witharana, S.
Copyright Year	2006
Description	Author affiliation: Ceylon Electr. Board, Kandy (Gunasekara, C.G.S.)
Abstract	The objective of this research is to model a cascaded hydro power generating reservoir system in order to get the maximum usage of the stored hydro potential to generate electricity. In this study, two models have been developed. First model to schedule the generator loads and the second model to, predict the water levels of the ponds. Then, both models have been integrated to dynamically simulate the variation of pond levels and to explore the feasibility of maximizing generation electricity under the given circumstances. In this research a range of historical data available, have been used to investigate and to evaluate the correlation between inputs and outputs. As this is a multi dimensional, non-linear multi input/output (MIMO) system, application of Artificial Neural Network (ANN) technology to model this system is explored by discovering a working mechanism of the system from the examples of past behavior. Then, by coupling the above two neural network models, developed for generator load scheduling and pond water level monitoring, system was dynamically simulated to explore the feasibility of maximum electrical power generation, while keeping the pond water levels stable, within the feasible operating constraints.
Starting Page	51
Ending Page	56
File Size	2023842
Page Count	6
File Format	PDF
ISBN	1424405548
DOI	10.1109/ICINFA.2006.374150
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electric potential predicting and scheduling Artificial neural networks Predictive models non linear system modeling Dynamic scheduling Power system modeling optimum model Neural networks Cascaded hydro-power system Reservoirs MIMO Power generation Monitoring
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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
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