Stochastic simulation framework for estimating characteristic hydrological and energy variables

I. Ntouxi, Stochastic simulation framework for estimating characteristic hydrological and energy variables, Postgraduate Thesis, 95 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2016.



The optimization of the hydrosystems for the hydropower production involves many challenges due to the stochastic nature of the inflows, the uncertainty of the values of the parameters and the non-linear dynamics of the hydrosystems. However the continuous reduction of the available resources and the pressure for a shift to renewable energy resources, require investigation and deepening of the scope of hydropower production. Earlier optimization approaches were limited to simple topologies and discovery rules, but now the approach of optimization-simulation of reservoir combined operation is being developed. The combined operation of the system is represented through simulation and stochastic forecasts of all water and energy flows are conducted. On the other hand, optimization is applied to determine the operational policy of the hydroelectric project, during which the risk is minimized and the economic performance of the system is maximized. The aim of this thesis is to find the optimum mean value of the profit made of hydropower production. The energy target per time step is being searched, which will yield the maximum potential profit and which will be valid as many times as possible. In the same time the respective average failure percentage is calculated for the year of study. After that, investigation of the two structural parts of the system is conducted, namely the flow capacity of the flow line and the capacity of the reservoir. Emphasis is given to capture the stochastic nature of the problem by relevant investigations under stochastic inflow models that maintain different autocorrelation structures. Finally necessary sensitivity analyses are performed with respect to the length of the time-series of the inflows.

PDF Full text (2533 KB)

PDF Additional material: