In recent years, smart grid (SG) has been introduced as a solution to enhance efficiency of distribution networks. SGs facilitate utilization of distributed generation, especially renewable resources. Demand response (DR) is known as one of the key elements of SGs. Demand response coordination (DRC) for residential loads is one of the most challenging problems to gain the advantages of SGs. Usually, in literature, the main focus have been on the economic aspect of DR while distribution network constraints and the static load modeling and their impacts on DR are neglected. In this thesis, the DRC for residential customers considering static load modeling in the presence of distributed wind generation is discussed. In this thesis, in the first step, we define demand response mismatch (DRM) which is caused by the dependency of loads to their supply voltage. Then, the impact of the effective parameters (Load reduction amount and power factor) on DRM is evaluated by simulation. The results show that the mismatch in residential DR can greatly affect the utilization of DR and could lead to ineffective utilization of these programs. Therefore, in this thesis we proposed an iterative procedure for residential DRC considering the static load modeling. In our method, the customers optimize their electricity demand, according to the signals received from the operator (energy price, desired level of consumption and incentives for each customer) and then they submit their scheduled demand to the operator. The operator fines the customers using penalty factors based on the amount of the deviation from the scheduled demand, and consequently for each customer calculates incentive according to the improvement of the total system load profile, at each iteration of the proposed mechanism. In order to eliminate DRM, in the proposed method, the voltage magnitudes are sent to the customers. Thus, they would be able to respond to the load reduction, requested by the operator, more accurate through the exact determination of their consumption using static load models in the calculations. The results of simulations demonstrate the efficiency of the proposed algorithm for DRM elimination. An increase in the wind power generation integration in distribution networks, considering stochastic nature of wind, may cause challenges for DRC implementation in distribution networks. Since the aforementioned DRC algorithm is performed under deterministic prices, it is necessary to announce the prices to the customers under the uncertainties of wind generation resources and real time electricity market prices. To do so, the proposed mechanism expanded to take into account some uncertainties. The operator deals with the uncertainties using stochastic programing to determine the optimized power purchased from both day-ahead and real-time electricity markets. To calculate the risk of this pricing method, the proposed one day algorithm is simulated for a one month study time horizon. The results demonstrate the efficiency of our proposed algorithm in the presence of wind power generation resources. Keywords : 1-Demand Response, 2-Static Load Modeling, 3-Wind Generation, 4-Stochastic Programing, 5-Optimization