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Wageningen Universiteit (1998)

Multiunit water resource systems management by decomposition, optimization and emulated evolution : a case study of seven water supply reservoirs in Tunisia

Milutin, D.

Titre : Multiunit water resource systems management by decomposition, optimization and emulated evolution : a case study of seven water supply reservoirs in Tunisia

Auteur : Milutin, D.

Université de soutenance : Wageningen Universiteit

Grade : Doctor of Philosophy (PhD) 1998

Résumé partiel
Being one of the essential elements of almost any water resource system, reservoirs are indispensable in our struggle to harness, utilize and manage natural water resources. Consequently, the derivation of appropriate reservoir operating strategies draws significant attention in water resources planning and management. These operational issues become even more important with the ever increasing scale and complexity of water resource systems. In this respect, the primary obstacle in the analysis of a multiple-reservoir-multiple-user water supply system operation is the dimensionality of the problem. Namely, being a sequential decision making process, the operation of a complex reservoir system over a certain period of time can adequately be described only if all the relevant variables and parameters related to possible system state and decision realizations are taken into account. Clearly, this requirement tends to grow rapidly with the size of the system considered. The computational burden expands even more drastically if the processes involved bear unavoidable stochastic characteristics which are, in this study, assumed to be attributed only to reservoir inflows. With regard to the problem in hand, the methods proposed and analyzed in the study can be divided into three major groups. The first group of methods falls into the family of system decomposition approaches within the optimization and/or simulation of the operation of complex systems. The second one involves the assessment of the impact various simulation alternatives may have on the performance of the adopted iterative decomposition algorithms. Finally, the third part includes the application of genetic algorithms for the derivation of the best water allocation patterns within a multiple-reservoir-multiple-user water supply system. The decomposition models proposed and analyzed in this study are known as sequential decomposition methods. Essentially, to reduce the dimensionality of an optimization problem, they split up a complex system into its elementary units (i.e. reservoirs). Subsequently, the operating strategy of the system is derived in an iterative fashion by applying successive optimization, simulation and release allocation analyses to individual system elements. The optimization method employed within all the decomposition models is stochastic dynamic programming (SDP). Due to the inherent discrete nature of SDP operating policies, the iterative, decomposition-based optimization models have a certain "inaccuracy threshold" which directly affects the performance of the system. Therefore, three different simulation alternatives have been employed to assess the possibility of reducing this negative impact of discretization. It is shown that, by allowing limited policy violations within simulation, the system performance can improve significantly relative to the case when the operating policies are strictly followed.

Mots clés : dams / lakes / water storage / reservoirs / operations research / tunisia / water

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