Abstract

Network reconfiguration and installation of Distributed Generation (DG) are widely used for loss minimization and betterment of the voltage profile. The major identifiers in the DG installation are the position and size of the DG. In this research, network reconfiguration and DG installation are solved using a hybrid Binary Particle Swarm Optimization with Ant Lion Optimizer (BPSO-ALO). Four different cases of the system with only reconfiguration, the system with the installation of a single DG unit, the system with reconfiguration and a single DG unit, and the system with reconfiguration and multiple DG units are considered to assess the performance of the hybrid BPSO-ALO method. The hybrid BPSO-ALO approach was tested on an IEEE 33-bus test system. The results were compared to those of the Modified Sequential Switch Opening (MSSO), Ant Lion Optimizer (ALO) Algorithm, Strength Pareto Evolutionary Algorithm (SPEA), and the Adaptive Cuckoo Search Algorithm (ACSA). By applying the hybrid BPSO-ALO approach, the power loss in the IEEE 33 test bus system was decreased to 45.71 kW for case IV, which is smaller than MSSO 57.7 kW, ALO 58.34 kW, SPEA 58.55 kW, and ACSA 53.21 kW.

Keyword

Ant lion optimizer, Binary particle swarm optimization, Distributed generation, Network reconfiguration, Power loss, Radial distribution system.

Cite this article

Rao GP, Babu PR

Refference

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