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OverviewReservoir 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. Full Product DetailsAuthor: Blagoj DelipetrevPublisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.453kg ISBN: 9781138373464ISBN 10: 113837346 Pages: 156 Publication Date: 27 September 2018 Audience: College/higher education , Tertiary & Higher Education Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1. 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.ReviewsAuthor Information"Blagoj Delipetrev was born in 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." Tab Content 6Author Website:Countries AvailableAll regions |
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