Despite traditional power generation based on fossil fuel, renewable energies like wind have primary uncontrollable energies including wide speed. In line with increasing the number of wind turbines connected to distribution system, the grid operator pays much attention to how these accidental resources can affect grid loss. To this end, Common methods are according to certain analysis which is not capable of appropriately assessing the performance of the system in permanent status. It is possible to have a better assessment through analyzing probabilities and considering the accidental behavior of grid data including wind power and consuming load. In this paper, it is attempted to determine the reactive power market and its pricing with a look at economic, technical concerns. Firstly, reactive power market model will be introduced; wind power and accidental models of consuming load will be represented. Then, the performance of power system in permanent status, the performance of productive units in short-term markets of reactive power will be taken into consideration. It is worth mentioning that a huge amount of represented articles talking around this matter mostly have focused on pricing the reactive power. Therefore, the main focus of the present study is on reactive power market and its development in a way that simultaneous analysis of uncertainty parameters (load and wind power demanded from the grid) and their influences on reactive power market will be performed. To model accidental behavior of productive power of wind turbines, limited ARIMA (LARIMA) method is adopted. The important point of using this special method to reach precise results and getting a more realistic model is mutual correlation between wind farms located in neighboring sites and the model. Further, to model behavioral changes of grid consuming load, AR(12) method is used followed by Monte-Carlo method in order to build power generation scenarios. By implementing suggested method on the sample grid, it is possible to assess the algorithm influence.