Optimization of Turkey's wind power regional allocation

In the thesis study, a stochastic mixed integer nonlinear programming model that minimizes the need of spinning reserves is developed for reducing negative effects of intermittent nature of wind power on transmission systems. Also a heuristic approach for simplifying nonlinear constraints in the nonlinear programming model is developed, with this heuristic approach objective function converges. The problem handled is novel in literature, and both the stochastic mixed integer nonlinear programming model and the heuristic approach is developed within the scope of this study. Parameters used for the solution approach are gathered from real life data sets which are provided from Turkish State Meteorological Service, Energy Exchange Istanbul (EXIST), Turkish Electricity Transmission Corporation and General Directorate of Renewable Energy. With the data set gathered from Turkish State Meteorological Service which contains data for a 10 year period of 357 measurement stations, wind power production data are estimated after editing the data set. With the aim of calculating correlation coefficients from the estimated power production data, a simulation algorithm is constructed, and then the correlation coefficients are estimated with this algorithm. In addition, correlation analysis is performed with 47 homogeneously selected meteorology measurement stations which represents Turkey. As a result of the correlation analysis, positive correlation structure is observed in Turkey, on the other hand no negative correlation structure is observed. With the solution approach developed, wind power distributions of 2016 and 2023 are obtained. Wind power distribution of 2016 which is obtained with the solution approach is compared with the existing installed wind power distribution. As a result of this comparison, the similarities and differences between these two power distributions are determined. Furthermore, when the results obtained are examined, it is observed that a large ratio of the existing installed wind power and a large ratio of the wind power obtained with the solution approach is in a small portion of Turkey. For obtaining power distributions of 2023 two different electricity demand forecasting scenarios are used. The first scenario used is from one of the reports of Republic of Turkey Ministry of Energy and Natural Resources, and the second scenario used is from a successful demand forecasting study in literature. Taking into account the results obtained and the wind power foreseen to be completed by 2023, regions with investment potentials are determined. Encouraging investors for these regions which are determined within the scope of this study may help to reduce negative effects of intermittent wind power.