Two-phase neural network based solution technique for short term hydrothermal scheduling
Two-phase neural network based solution technique for short term hydrothermal scheduling
- Author(s): R. Naresh and J. Sharma
- DOI: 10.1049/ip-gtd:19990855
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- Author(s): R. Naresh 1 and J. Sharma 2
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View affiliations
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Affiliations:
1: Department of Electrical Engineering, Regional Engineering College, Hamirpur, India
2: Department of Electrical Engineering, University of Roorkee, Roorkee, India
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Affiliations:
1: Department of Electrical Engineering, Regional Engineering College, Hamirpur, India
- Source:
Volume 146, Issue 6,
November 1999,
p.
657 – 663
DOI: 10.1049/ip-gtd:19990855 , Print ISSN 1350-2360, Online ISSN 1359-7051
A two-phase neural network based optimisation method for short-term scheduling of a hydrothermal power system is proposed. The method is based on the solution of a set of differential equations obtained from transformation of an augmented lagrangian energy function. A multireservoir cascaded hydroelectric system with a nonlinear power generation function of water discharge rate and storage volume is considered for implementation. The water transportation delay between cascaded reservoirs is taken into account. Results from this method are compared with those obtained from the augmented lagrangian method. It is shown that the proposed solution technique is capable of yielding good optimal solution with proper selection of control parameters.
Inspec keywords: hydrothermal power systems; neural nets; power generation scheduling; differential equations; power system analysis computing
Other keywords:
Subjects: Differential equations (numerical analysis); Hydroelectric power stations and plants; Power systems; Numerical analysis; Differential equations (numerical analysis); Thermal power stations and plants; Power engineering computing; Neural computing techniques
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