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Maximizing capacity of distributed generations (DGs) embed into distribution network is a solution to attract investment for DGs installation on the distribution system. This paper introduces a approach of optimizing location and capacity of DGs for maximizing DGs capacity and minimizing the system’s power loss based on cuckoo search algorithm (CSA). The proposed problem and method are simulated on two test systems including the 33-node and 69-node networks. The numerical results have demonstrated that the proposed method not only reduces power losses but also maximizes the power of DGs embed into the distribution network. The results also introduce that the proposed CSA method is better performance that some previous methods in terms of power loss and DGs capacity. The results obtained in many independent runs for two test systems indicate that CSA in one of the reliable methods for the DGs placement problems.

In this paper, an effective method to determine an initial searching point (ISP) of the network reconfiguration (NR) problem for power loss reduction is proposed for improving the efficiency of the continuous genetic algorithm (CGA) to the NR problem. The idea of the method is to close each initial open switch in turn and solve power flow for the distribution system with the presence of a closed loop to choose a switch with the smallest current in the closed loop for opening. If the radial topology constraint of the distribution system is satisfied, the switch opened is considered as a control variable of the ISP. Then, ISP is attached to the initial population of CGA. The calculated results from the different distribution systems show that the proposed CGA using ISP could reach the optimal radial topology with better successful rate and obtained solution quality than the method based on CGA using the initial population generated randomly and the method based on CGA using the initial radial configuration attached to the initial population. As a result, CGA using ISP can be a favorable method for finding a more effective radial topology in operating distribution systems.

Increasing the possible capacity of distributed generations (DGs) supplying to distribution system (DS) is a highly effective solution to attract the investment of distributed generation (DG) installation in the DS. However, the presence of DGs will affect the technical indicators of the DS. This paper determines solutions of the DG placement problem for maximizing the size of distributed generations (DGs) and improving the technical indicators consisting of power loss reduction, increasing of balance among feeders and balance among branches, and voltage deviation reduction. A max-min method is proposed to combine the membership objective functions. The location and size of DGs are optimized based on an improved cuckoo search algorithm (ICSA). The simulation results for the 84-node system show that the proposed multiobjective problem not only helps to increase the capacity of DGs but also improves the technical factors. Moreover, the DG’s uncertainty is also validated to show its negative impacts on the technical indicators of the DS. Furthermore, ICSA is worthy for finding the optimal solution for the DG placement problem.