Loss Minimization by Reconfiguration along with Distributed Generator Placement at Radial Distribution System with Hybrid Optimization Techniques

Abstract

In this paper a new methodology is used to reconfigure the topology of distribution system and placement of Distributed generators (DG) optimally. This methodology is adopted from the three optimization techniques which are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Blue Whale Optimization (BWO). The basic principles of the GA is used the optimal switching, the foundation for the swarm searching techniques, PSO is used to find the optimal placement and latest optimization technique, BWO is used to find the size of the type-III DG. The major objective of the paper is to minimize the losses through optimal reconfiguration and optimal placement of DG in balanced radial distribution system.

An Enhanced Control Procedure for that DVR to accomplish both LVRT and HVRT in the DFIG Wind Turbine

“…jω s e jω s t ≥ t 0 (10) As the continuous quantity, a stator flux cannot track a voltage step function. Assuming _ire = 0, due to its low impact on a rotor voltage, a differential equation ( 11) may be solved for that an evolution of stator flux.…”

“…When a crowbar is triggered, a machine consumes a copious of wattless power from the network, which is unsuitable while considering real mesh code demands, resulting in a significant short circuit current, as detailed in [9]. Different protection methods must be investigated in order to safely navigate the grid faults and comply with grid regulations for that fault ride-through of the DFIG, extra hardware such as the series dynamic resistance in a rotor [10] or a stator in the [11] or employing the series line side converter (LSC) architecture as in the [12] have been proposed. [12]Changing an RSC control to prevent a need for that extra hardware can reduce rotor currents during transient grid voltage fluctuations.…”

Modified sunflower optimization for network reconfiguration and distributed generation placement

“…The results show that its performance has been higher than that of EO. In [17], the combination of genetic algorithm (GA), WOA and PSO has been proposed for the NR-DGP problem. However, in this work the effectiveness of the combination algorithm has not been compared to the original version of the algorithms.…”

Effective Automation of Distribution Systems With Joint Integration of DGs/ SVCs Considering Reconfiguration Capability by Jellyfish Search Algorithm

“…The DSR and CBs placement were concurrently presented in literature based on fuzzy binary gravitational search algorithm [30]; ant colony algorithm [31]. Also, DSR functionality and DGs allocation were concurrently presented using various methods, for example, dataset approach with marine predators algorithm [32]; coyote algorithm [33]; hybrid genetic algorithm, particle swarm optimization and blue whale optimization [34]. In addition, optimal placement of CBs and DGs have been solved using particle swarm optimization [3], water cycle algorithm [35], enhanced grey wolf algorithm [36].…”