Nested algorithms for optimal reservoir operation and their embedding in a decision support platform

1. Auflage 2018
ISBN: 978-1-138-37346-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 156 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 454 g

Reihe: IHE Delft PhD Thesis Series

Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation, named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO) variants, correspondingly MOnDP, MOnSDP and MOnRL.
The idea is to include a nested optimization algorithm into each state transition, which reduces the initial problem dimension and alleviates the curse of dimensionality. These algorithms can solve multi-objective optimization problems, without significantly increasing the algorithm complexity or the computational expenses. It can additionally handle dense and irregular variable discretization. All algorithms are coded in Java and were tested on the case study of the Knezevo reservoir in the Republic of Macedonia.
Nested optimization algorithms are embedded in a cloud application platform for water resources modeling and optimization. The platform is available 24/7, accessible from everywhere, scalable, distributed, interoperable, and it creates a real-time multiuser collaboration platform.
This thesis contributes with new and more powerful algorithms for an optimal reservoir operation and cloud application platform. All source codes are available for public use and can be used by researchers and practitioners to further advance the mentioned areas.

Autoren/Hrsg.

Delipetrev, Blagoj

Fachgebiete

• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Wasserversorgung, Wasseraufbereitung
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik

Inhaltsverzeichnis

1. Introduction. 2. Optimal reservoir operation: the main approaches relevant for this study. 3. Nested optimization algorithms. 4. Case study: Zletovica hydro system optimization problem. 5. Algorithms implementation issues.
6. Experiments, results and discussion. 7. Cloud decision support platform. 8. Conclusions and recommendations.

Über Autor(innen)

Blagoj Delipetrev was bornin 1980 in Shtip, Republic of Macedonia. He graduated from the Faculty of Electrical Engineering and Information Technologies, at University Ss. Cyril and Methodius in Skopje in 2003. Blagoj conducted his Master studies 2004-2007 at the same university, working on his thesis "Geo-model of the Republic of Macedonia," which focused on information systems technologies, Geographical Information Systems (GIS), Spatial Data Infrastructures (SDI), and their potential applications in Macedonia.In January 2010 Blagoj started his PhD research at UNESCO-IHE. This publication presents his PhD thesis, entitled "Nested algorithms for optimal reservoir operation and their embedding in a decision support platform." It focusses on novel algorithms for optimal Reservoir Operation and development of cloud decision support systems.Currently Blagoj is currently working as an assistant professor at Faculty of Computer Science, University Goce Delcev in Shtip, Republic of Macedonia.