Multi-culture diversity based self adaptive particle swarm optimization for optimal floorplanning

This paper presents the minimization of the voltage deviation and power loss, which is related to ORPD in unbalanced conditions. Moreover, a hybridization of two techniques (i.e.,) PSO and WOA termed Hybrid (PSO-WOA) algorithm is developed in this paper. Here, this proposed technique works on the control variables namely transformer tap settings, voltage, and load reactance that are diverse to attain optimum outcomes. The complete experimentation is performed on two IEEE bus systems, such as the IEEE 39 and 14 bus systems. The simulation outcomes of the proposed PSO-WOA technique are analyzed with conventional techniques to assure the proposed technique.

Section: Hybrid Optimization Algorithms Adopted For Orpd 41 Conventimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid PSO-WOA for Solving ORPD Problem under Unbalanced Conditions

Dr.D.Susitra¹

2019

“…This section clearly describes the organization of the proposed Hybridization of PSOSSA method. It is the combination of the PSO [23] and the SSA methods. The fundamental organization of the SSA method is modified by enhancing the updating stage of the position of population's.…”

Section: Proposed Hpsossa Algorithmmentioning

confidence: 99%

HPSOSSA: Enhancement of Dynamic Stability by Optimal Placement of UPFC

Tapre¹,

Singh²,

Paraskar³

2019

This paper proposes a hybrid approach on the basis of the Optimal Positioning and Sizing (OPAS) to enhance the dynamic stability for Unified Power Flow Controller (UPFC). Moreover, the maximum power loss bus is recognized during the optimum positioning by putting the UPFC, as the generator outage have effects on the power flow constraints namely voltage, real and reactive power flow, and loss of power. By exploiting the Particle Swarm Optimization (PSO) method, the optimum position is determined. According to violated power flow quantities, the Salp Swarm Algorithm (SSA) optimizes, which is necessary for UPFC quantity in order to get better initial operating circumstance. Subsequently, the proposed and conventional methods are simulated in the MATLAB platform and the performance of the proposed approach is examined by comparing conventional approaches like Genetic Algorithm (GA), PSO, and Artificial Bee Colony (ABC). Finally, the results revealed that the performance of the proposed approach is enhanced and validate it's possible to resolve the crisis.

“…Moreover, these approaches can be categorized into types such as existing, intelligent and hybrid techniques. Additionally, researchers have examined several optimization techniques in order to find the optimal positioning and sizing for distribution generators like PSO [13], GA [15] as well as its enhanced versions, ACO, HS approach, FF [14]. Last decades, artificial intelligence-based techniques have been extensively exploited in order to solve the optimal positioning and sizing issue with attained propitious outcomes.…”

Section: Introductionmentioning

confidence: 99%

Optimal Positioning of Distributed Generator using Hybrid Optimization algorithm in Radial Distribution System

Ravikumar¹,

Vennila²,

Deepak³

2019

In distribution systems, the distributed generator is renowned as a feasible solution in order to control the line losses, voltage stability, and bus voltage, etc. This paper concentrates on an advanced technique in order to position the distributed generator. It is exploited for minimization of the energy loss and active power loss for the distribution lines when concerning the voltage stability index and bus voltage. Based on the optimal positioning and sizing of the DGs, the optimization is performed. Here, a hybrid ABC and Bat Algorithm (HABC-BA) is presented to solve the optimal distributed generators allocation issue of distribution networks. The proposed HABC-BA method experimented on standard 33-bus, 69bus in radial distribution networks to examine the possibility and efficiency. Hence, the experimental analysis shows that placement of distributed generators in the optimal position can extensively minimize the power loss in a DS Finally, the proposed method is compared with other meta-heuristic approaches such as GWO, WOA and PSO and the analysis exhibit that the proposed technique has the capability to find enhanced quality solutions.