The renewable resources that are used to support the increasing consumption of the electricity and improve the efficiency level , impose complexities to the power system. The increasing trend of complexity in the power system needs new procedures to improve the performance of the power systems from the economic and the technical aspects . Nowadays, the challenge in power systems planning and operation is attaining the optimal economic performance while the increase of utilization of renewable resources is acceptably improved . In order to achieve to this goal , in this thesis , we proposed a model to obtain an economically optimal performance of a power system using fluctuations in wind power generation in different geographical areas . The proposed model is considered so that to obtain appropriate cooperation options in different geographical wind farms based on knowledge of these wind farms as a dynamic and complex systems. Accordingly , as the first step we discovered hidden characteristic of wind speed time series in different wind farms to achieve preliminary data for stochastic optimization model using RP method. As the next step, in order to propose a model for wind farms cooperation,we model balance responsible parties for a dual purpose procedure as the power system operators assistant to reduce power system operational cost and the wind power producers assistant to reduce their benefit variance. As the last step of modeling , the proposed model is solved considering uncertainties caused by wind power generation and their inter-correlations . The cooperation optimization problem for the wind farms is modeled in the context of a Mixed Integer Linear Programming (MILP) and the simulations of the proposed model implemented on the numerical case studies have been solved by GAMS v.24.1.3 using the solver CPLEX v.12 . The numerical case studies of this thesis are conducted on a modified versions of the IEEE 24-bus benchmark and wind data related to six windy areas in Iran . The analysis conducted on the results of the proposed model under different operational conditions such that both economically optimal performance and flatness of the benefit variation of the wind power plants are achieved , simultaneously . The results of this study , due to the adoption of a holistic approach may help the power system operators and decision makers adopt more economically efficient procedures in order to improve the operational status and issues pertaining to the entire system . Key Words : Wind Power Generation , Wind Farms in Different Geographical Areas , Dynamic and Complex System , Optimal Planning , Fluctuations in Wind Power Generation , Inter-Correlations, RP and CRP.
