Research Information System
Thesis Type: Postgraduate
Institution Of The Thesis: Akdeniz University, Institute of Science, Institute of Science, Turkey
Approval Date: 2023
Thesis Language: Turkish
Student: TURAN ALAKBAR
Supervisor: Halil İbrahim Burgan
Abstract:
Hydropower is a clean and environmentally friendly energy source that is powered by water and is sustainable even in scenarios of energy demand driven by future population growth. The development of hydropower is not only an effective response to the energy crisis, but also a positive way to tackle climate change in many countries. Moreover, as environmentally friendly energy sources, they have a higher energy intensity than other alternative energy sources.
According to the purpose of hydroelectric energy potential determination studies, in addition to physical data about the study area, long-term measurement data (discharge, temperature, evaporatranspration, etc.) should be known as much as possible. Various methods to determine the hydroelectric energy potential in the region with missing data have been developed in the previous studies. One of these methods is the power duration curve method. This method has a field of use in solving the problem of determining hydroelectric energy potential.
In this study, the determination of the hydroelectric energy potential of the intermittent rivers in the Antalya basin with the power duration curve model was investigated. The discharges were determined by current observation stations established by the relevant institutions on the rivers. In Turkey, discharge measurements are carried out by the General Directorate of State Hydraulic Works (DSİ). The independent variables of catchment area (A) and basin relief (H), which express the characteristics of the region, were obtained from the discharge observation stations. Precipitation (P) values were obtained from CHRS RainSphere data. Flow and power duration curves were constructed using the discharge and basin relief data of the calibration stations. Then, six models from the results of quadratic and linear regression analyses were used to find the best regional model. The regression coefficients in the regional model were determined from the basin characteristics. The obtained regional power duration curves and annual total power (MW) values were checked with performance criteria such as R2, NSE, MAE, RMSE, MSE, VE, BiasPHV, SPDC and BiasPLV.