Voltage dip and long duration interruption (LDI) are among the most costly power quality phenomena. In this study, a Monte-Carlo based approach is proposed to consider the cost of sensitive loads disruption caused by dip and LDI in the optimal planning of synchronous distributed generations (SDGs). The idea is to link between trip probability due to dip and LDI and their yearly costs by employing Monte-Carlo simulation and acquiring their total costs during the planning horizon. The addition of disruption cost along with the traditional planning objectives like network upgrade cost and loss cost allows utilities to include the customer's perception during planning. A formula for the probability of disruption due to dip is derived and a modified Monte-Carlo approach is proposed. The methodology is illustrated on the distribution level of the IEEE 30-bus system and the optimisation problem is solved by particle swarm optimisation algorithm. The results demonstrate that the sensitive loads performance is improved from the dip standpoint in the presence of SDGs. However, the LDI cost is either not affected or aggravated by the presence of SDGs depending on the protection model. The total disruption cost is decreased.