Heuristic optimization techniques for voltage stability enhancement of radial distribution network with simultaneous consideration of network reconfiguration and DG sizing and allocations

Abstract

In this paper, heuristic optimization techniques, such as integrated particle swarm optimization (IPSO),teaching–learning-based optimization (TLBO), and Jaya optimization, were applied effectively for the first time tooptimize the radial distribution network (RDN) by simultaneously considering reconfiguration of the network andallocation and sizing of the distributed generations (DG). The objectives were to maximize the voltage stability andto minimize the power loss of the network without violating the system constraints. In standard PSO technique, themovement of current particle depends upon global best position and its own best position up to current step. However,if the particle lies too close to any of these positions, the guiding role highly decreases and even vanishes. To resolvethis problem and to find the global best solution, IPSO was utilized to optimize the network reconfiguration and DGallocation and sizing problem in the RDN. Also, the optimization techniques, such as TLBO and Jaya optimization, whichdo not require any tuning of parameters, unlike other heuristic optimization techniques, were implemented successfullyin this paper. Seven test cases were generated from different combinations of network reconfiguration and DG allocationand sizing. Moreover, for comparison, the optimization techniques, such as particle swarm optimization (PSO), adaptivecuckoo search algorithm (ACSA), harmony search algorithm (HSA), and fireworks algorithm (FWA), were also appliedto IEEE 33- and 69-bus distribution test networks. The comparison results prove overall superiority of Jaya optimizationwhen applied on the two IEEE bus systems with seven test cases undertaken.