This paper proposes a novel adaptive optimization algorithm to solve the network reconfiguration and distributed generation (DG) placement problems with objective functions including power loss minimization and voltage stability index (VSI) improvement. The proposed technique called Adaptive Shuffled Frogs Leaping Algorithm (ASFLA) was performed for solving network reconfiguration and DG installation in IEEE 33-and 69-bus distribution systems with seven different scenarios. The performance of ASFLA was compared to that of other algorithms such as Fireworks Algorithm (FWA), Adaptive Cuckoo Search Algorithm (ACSA) and Shuffled Frogs Leaping Algorithm (SFLA). It was found that the power loss and VSI provided by ASFLA were better than those given by FWA, ACSA and SFLA in both 33-and 69-bus systems. The best solution of power loss reduction and VSI improvement of both 33-and 69-bus systems was achieved when the network reconfiguration with optimal sizing and the location DG were simultaneously implemented. From our analysis, it was indicated that the ASFLA could provide better solutions than other methods since the generating process, local and global searching of this algorithm were significantly improved from a conventional method. Hence, the ASFLA becomes another effective algorithm for solving network reconfiguration and DG placement problems in electrical distribution systems.

A novel optimization algorithm called the Salp Swarm Algorithm (SSA) has recently been found to be effective for solving optimization problems; however solving optimal system reconfiguration using SSA has not been reported in the literature. Thus, this paper proposes a network reconfiguration of an electrical distribution system based on the SSA for power loss reduction. The 33 and 69 bus distribution systems are focused on for the network reconfiguration. Simulation results obtained by SSA are compared with those of the Genetic Algorithm and Simulated Annealing, which are well-known algorithms. It is found that the performance of an electrical distribution system reconfigured by SSA is reconfigured better than by other methods, in terms of the quality of the solutions and the average elapsed time. Thus SSA becomes a good choice for power loss reduction in an electrical distribution system.

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Network reconfiguration of an electrical distribution system is an outstanding technique to improve the performance of a distribution system. The main factors indicating the performance of the system are the electrical power loss and the system reliability. In this paper, the multi-objective reconfiguration of a large-scale electrical distribution system located in Khon Kaen province, Thailand is proposed by using the Enhanced Genetic Algorithm. The total electrical power loss, system average interruption frequency index, system average interruption duration index, energy not supplied and the total cost are analyzed as the objective functions. The results show that the power loss of the illustrative system is significantly reduced as compared to the initial configuration. Furthermore, the reliability indices of the distribution system can be improved, while the total cost is decreased. Thus, it is indicated that the overall performance of the particular distribution system is significantly improved after network reconfiguration, which can be utilized for distribution system expansion planning.