Title :
Hydro system scheduling using ANN approach
Author :
Naresh, R. ; Sharma, J.
Author_Institution :
Dept. of Electr. Eng., Roorkee Univ., India
fDate :
2/1/2000 12:00:00 AM
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;
Journal_Title :
Power Systems, IEEE Transactions on
