Hydro system scheduling using ANN approach

Author

Naresh, R. ; Sharma, J.

Author_Institution

Dept. of Electr. Eng., Roorkee Univ., India

Volume

15

Issue

1

fYear

2000

fDate

2/1/2000 12:00:00 AM

Firstpage

388

Lastpage

395

Abstract

This paper presents a two-phase artificial neural network approach for ending optimal scheduling of interconnected hydropower plants. In this approach the objective is to maximize hydropower generation and to satisfy the irrigation requirement as far as possible. A case study considering scheduling of Bhakra-Beas interconnected reservoir system is also presented in this paper. The proposed technique is compared with augmented penalty function methodology and demonstrates the potential of achieving better results

Keywords

hydroelectric power stations; neural nets; power engineering computing; power generation scheduling; ANN approach; Bhakra-Beas interconnected reservoir system; Lagrange multipliers; augmented penalty function; hydro system scheduling; hydropower generation maximisation; interconnected hydropower plants; minimum energy; operation planning; optimal scheduling ending; two-phase artificial neural network; two-phase neural network; Artificial neural networks; Dynamic programming; Hydroelectric power generation; Job shop scheduling; Linear programming; Neural networks; Optimal scheduling; Power system planning; Reservoirs; Water resources;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.852149

Filename

852149