The penetration of renewable energy sources is increasing every year and that poses a lot of challenges in the distribution system. Since they are intermittent in nature, they cannot serve the energy demand as stand alone sources without the help of storage technologies or stable energy sources. As the RES, especially the Photo Voltaic generation units are often connected in the distribution system, their intermittent nature may result in a sudden rise or fall in overall generation. Hence the voltage has to be kept within limits to prevent the failure of the system. Storage technologies plays an important role in keeping the voltage levels under control. From the consumer perspective, the usage of electric vehicles is steadily increasing and most of the vehicles are connected to public charging stations to charge the vehicle battery. Hence there is an interaction between the EVs and distribution grids, which is utilized as a storage option here. In this research, the voltage changes due to the penetration of renewable energy sources in the distribution system is regulated by using the electric vehicles as a storage option. This thesis tries to give an understanding on the strategy applied towards regulation of voltage in the distribution system using electric vehicles. The strategy will serve as a platform for regulating voltage using electric vehicles and it can be adapted to any such distribution network. This strategy takes into account the size and capacity of the battery, battery state of charge and the availability of electric vehicles for a given day. Consensus algorithm serves as the communication platform for information interchange between the electric vehicles connected in the network. Average consensus algorithm estimates the average state of charge of the electric vehicles connected in the distributed network and that has been used to ensure equitable contribution of power among the electric vehicles. Markov model is used to simulate the travel pattern of the electric vehicles. This provides a more realistic and accurate pattern of travel. Markov model is implemented with and without considering time of occurrence and the results shows that the pattern is more accurate when time is considered as a parameter. Considering the generated travel pattern, voltage level of the buses in the network and the output from the consensus algorithm, the voltage has been regulated. The Electric vehicles are used for regulating the voltage when the voltage level is beyond the tolerance limits, and during other times, the electric vehicles charge their batteries. This is executed by controlling the charging and discharging cycles of the electric vehicles. The results are discussed based on different cases and the advantages and limitations of each case is explained in detail. The simulation is not robust since the availability of electric vehicles is uncertain. To make it more robust, monte carlo simulations are used. The probability of occurrence of several events has been estimated using monte carlo simulations and through the results, the availability is predicted to a certain extent. Different cases are implemented and analysed and the results shows that the availability depends on the bus, the location of the bus and the travel behaviour of the electric vehicles. Each case is discussed separately and the degree of uncertainty is reduced at the end.