Operation of a system having both hydro and thermal plants is far more complex than the system having only thermal plants. The hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem of minimizing the operating cost of a hydrothermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraints of water availability (storage and inflows) for hydro generation over a given period of operation several AI methods, such as Genetic Algorithm, Evolutionary programming, Particle swarm Optimization and Differential Evolution are utilized to find out the optimal solution of constrained optimization problem but, because of certain drawbacks such as drastic growth of computational and dimensional requirements and insecure convergence properties, these optimization technique are not suitable for such problem. Thus Artificial Fish Swarm Algorithm (AFSA) a new optimization technique has been adopted for solving the hydro thermal scheduling problems.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Operation of a system having both hydro and thermal plants is far more complex than the system having only thermal plants. The hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem of minimizing the operating cost of a hydrothermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraints of water availability (storage and inflows) for hydro generation over a given period of operation several AI methods, such as Genetic Algorithm, Evolutionary programming, Particle swarm Optimization and Differential Evolution are utilized to find out the optimal solution of constrained optimization problem but, because of certain drawbacks such as drastic growth of computational and dimensional requirements and insecure convergence properties, these optimization technique are not suitable for such problem. Thus Artificial Fish Swarm Algorithm (AFSA) a new optimization technique has been adopted for solving the hydro thermal scheduling problems. 68 pp. Englisch. N° de réf. du vendeur 9783659943744
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock. N° de réf. du vendeur 3659943746
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Prusty Ramesh ChandraDr. Ramesh Chandra Pusty and Santosh Kumar Majhi are working as Asst Professor in V.S.S University of Technology, Burla, India and Shovan Mondal is working as Asst Engineer for West Bengal Government.Operatio. N° de réf. du vendeur 158606907
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Operation of a system having both hydro and thermal plants is far more complex than the system having only thermal plants. The hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem of minimizing the operating cost of a hydrothermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraints of water availability (storage and inflows) for hydro generation over a given period of operation several AI methods, such as Genetic Algorithm, Evolutionary programming, Particle swarm Optimization and Differential Evolution are utilized to find out the optimal solution of constrained optimization problem but, because of certain drawbacks such as drastic growth of computational and dimensional requirements and insecure convergence properties, these optimization technique are not suitable for such problem. Thus Artificial Fish Swarm Algorithm (AFSA) a new optimization technique has been adopted for solving the hydro thermal scheduling problems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. N° de réf. du vendeur 9783659943744
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Operation of a system having both hydro and thermal plants is far more complex than the system having only thermal plants. The hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem of minimizing the operating cost of a hydrothermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraints of water availability (storage and inflows) for hydro generation over a given period of operation several AI methods, such as Genetic Algorithm, Evolutionary programming, Particle swarm Optimization and Differential Evolution are utilized to find out the optimal solution of constrained optimization problem but, because of certain drawbacks such as drastic growth of computational and dimensional requirements and insecure convergence properties, these optimization technique are not suitable for such problem. Thus Artificial Fish Swarm Algorithm (AFSA) a new optimization technique has been adopted for solving the hydro thermal scheduling problems. N° de réf. du vendeur 9783659943744
Quantité disponible : 1 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Short Term Hydro Thermal Scheduling by Artificial Fish Swarm Algorithm | Ramesh Chandra Prusty (u. a.) | Taschenbuch | 68 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659943744 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 102880285
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