Neural Approximation for the Optimal Control of a Hydroplant with Random Inflows and Concave Revenues-Reference-Cited by-同舟云学术

Neural Approximation for the Optimal Control of a Hydroplant with Random Inflows and Concave Revenues

Published:2005-04 Issue:1 Volume:131 Page:72-95
ISSN:0733-9402
Container-title:Journal of Energy Engineering
language:en
Short-container-title:J. Energy Eng.

Author:

Lamond Bernard F.¹²,Boukhtouta Abdeslem¹²

Affiliation:

1. Département Opérations et Systèmes de Décision, Faculté des Sciences de l’Administration, Université Laval, Quebec, PQ, Canada G1K 7P4.

2. Defence Research and Development Canada–Valcartier, 2459 Pie-XI Blvd. North, Val-Bélair Quebec, PQ, Canada G3J 1X5.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9402%282005%29131%3A1%2872%29

Reference23 articles.

1. Nested Benders decomposition and dynamic programming for reservoir optimisation

2. An aggregate stochastic dynamic programming model of multireservoir systems

3. Applying Experimental Design and Regression Splines to High-Dimensional Continuous-State Stochastic Dynamic Programming

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