The development of smart grid technology has received a lot of attention in recent years to enhance the conventional power distribution system. This includes incorporating distributed generations (DGs) to meet growing demand and enhance network efficiency. Alongside DGs, the integration of shunt capacitors (SCs) and network reconfiguration can also contribute significantly to improving network performance. Distribution companies must deploy DGs and SCs in the best possible locations to operate the distribution network in optimal circumstances. The intersect mutation differential evolution (IMDE) method is a new differential evolution (DE) algorithm with intersect mutation operation that is proposed in this research for simultaneous optimal size and allocation of DGs and SCs in distribution networks. As long as the bus voltage and branch current do not exceed their restrictions, the objective function is thought to be reducing power loss and improving the voltage profile. IEEE 33 and 69-bus distribution networks to test and evaluate the performance of the suggested technique in the MATLAB environment. When the suggested method is compared with other strategies described in the literature, results from the simulations indicate that this algorithm not only achieves faster convergence but also performs better than previous methods in this field. The findings demonstrate a significant reduction loss reduction of 83.05 and 89.716% as well as the worst bus voltage of 0.9804 and 0.9903pu in the simultaneous presence of DGs and SCs while voltages of bus voltages and line currents keep within their limits.