Inflows and Energy Demands of Dokan Hydropower Reservoir Operation under Stochastic Conditions

This paper presents a method of obtaining certain operating rules based on time steps for the management of the operation of a large reservoir combined with a peak hydropower plant. The operating rules link a decision variable, such as the water volume in the reservoir at the end of the time step, to several affecting parameters. The rules are formulated in the form of non-linear regression equations. This paper considers Dokan hydropower plant in Sulaymaniyah, Kurdistan of Iraq due to the availability of its operation data. The operation data shows that both the monthly average inflows and the monthly power demands are random variables. A deterministic dynamic programming model is developed and used in the study for different annual scenarios of inflows and monthly energy demands. The model optimizes the reservoir operation through minimizing the total amount of the squares differences between the energy demand and the energy supply. The obtained results shows that the operating rules allow efficient and safe management of the hydropower reservoir operation. The developed model can be used as an accurate tool to estimate the inflow and the energy demand on the next time step.