Allocation of Distributed Generation in Radial Distribution Networks Using an Efficient Hybrid Optimization Algorithm

Gradual increase in demand loads is considered a natural process in electrical distribution systems that leads to increase the power losses and decrease the buses voltage. In general, the installing distribution generation (DG) units in non-optimum allocations may cause high energy loss, low power quality, voltage imbalance, and high operating costs. This paper proposes the application of hybrid optimization (TLABC) technique based on teaching-learning based optimization (TLBO) and artificial bee colony (ABC) to determine the optimal location and size of DG in radial distribution networks. In order to reduce the search space, some candidate buses are determined using the Loss Sensitivity Factor (LSF). Then TLABC is applied to identify the allocation of DG between the selected buses. The proposed algorithm is applied for the standard 33-bus test system to check its effectiveness and superiority compared with other well-known optimization techniques in terms of real power loss and maximum cost savings. The results proved that the proposed algorithm has superior characteristics, steady convergence characteristics, and good computational efficiency.