Adaptation of methodological framework parameterization - simulation - optimization to hydroelectric reservoir systems: Computational challenges, new operation rules and implementation within Hydronomeas 2020 software

S. Manouri, Adaptation of methodological framework parameterization - simulation - optimization to hydroelectric reservoir systems: Computational challenges, new operation rules and implementation within Hydronomeas 2020 software, Postgraduate Thesis, 132 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2020.

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[Greek]

The management of multiple hydroelectric reservoirs which are primarily used to cover an overall energy target is a complex and multidimensional topic of study, which can be formulated as a parameterization - simulation - optimization problem. The study of such problems is strongly facilitated by the use of appropriate operational rules, adapted to the system constraints. A crucial factor in the management of hydropower systems is the simulation time step chosen, which clearly affects the derived results. Having an overview of the complexity of the management of hydropower systems, a new simulation model for hydroelectric reservoir systems is developed, in which an innovative operational rule was implemented to optimize the required energy quantities from each reservoir. The target energy of each reservoir is expressed as a percentage of the total energy demand that the system is required to meet; these can also be considered as control variables within the optimization of performance measures such as the firm energy and the total economic benefit of the system. The new model handles any reservoir topology, by allowing for reallocating the target sharing among the reservoirs, in the case of inability to meet the demand or when surplus energy is produced in a specific component. The new framework was tested in theoretical problems as well as in two cases of real - world systems in Greece, by employing a comparative analysis of the same systems by using the water management software and decision support system Hydronomeas. The results indicate that the proposed methodological framework offers a more accurate representation of the energy fluxes across the system and better solutions with respect to the distribution of the energy production targets.

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