Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm

Prabha, D. Rama; Jayabarathi, T.

doi:10.1016/j.asej.2015.05.014

Cited by 153 publications

(81 citation statements)

References 27 publications

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“…Known as a population-based meta-heuristic algorithm, particle swarm optimization (PSO) works in two steps, of which, calculating the particle velocity and then updating the position [34]. PSO requires little memory and reduces the computation time, however, based on [34], a study by [35], [36] and [37] indicate that PSO easily suffers from partial optimization. Genetic algorithm (GA) on the other optimization technique, can be used to solve the nondimensional, non-differential and non-continuous problems which also easy to understand [34].…”

Section: Optimization Approach For Loss Reduction Elementmentioning

confidence: 99%

“…PSO requires little memory and reduces the computation time, however, based on [34], a study by [35], [36] and [37] indicate that PSO easily suffers from partial optimization. Genetic algorithm (GA) on the other optimization technique, can be used to solve the nondimensional, non-differential and non-continuous problems which also easy to understand [34]. There is a limitation in GA applications in real time performance due to less convergence speed and random solutions approach [38].…”

Section: Optimization Approach For Loss Reduction Elementmentioning

confidence: 99%

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Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

Amran¹,

Muhtazaruddin²

2018

IJET

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This paper presents an optimization solution for renewable Distributed Generation (DG), as imposed in the Green Building Rati ng System (GBRS) for a public hospital. Solar photovoltaic DG unit (PV-DG) is identified as a type of DG used in this paper. The proposed optimization via PV-DG coordination will improve the sustainable energy performance of the green building by power loss reduction within accepted lower losses region using Artificial Bee Colony (ABC) algorithm. The setup input data from one of Malaysian public hospitals' power distribution system is been adopted and simulation results via MATLAB programming show that the optimization of DG forming into bigger-scale imposed system provides a better outcome in minimization of total power losses within appropriate voltage profile as compared to current PV-DG imposed in GBRS. The objective function representing total power losses which also supported by related literature give a measure that forming sufficient and optimal PV-DG assessment criteria is highly important, thus, current PV-DG assessment in GBRS is proposed to be reviewed into new parameter setting for public hospital due to its' high energy demand and distinctive electrical load profile.

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Section: Optimization Approach For Loss Reduction Elementmentioning

confidence: 99%

Section: Optimization Approach For Loss Reduction Elementmentioning

confidence: 99%

Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

Amran¹,

Muhtazaruddin²

2018

IJET

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“…Esfahani et al [313] Optimisation (GWO) [345], Krill Herd Algorithm (KHA) [338], Invasive Weed Optimisation (IWO) [346], and Cat Swarm Optimisation (CSO) [344] are introduced with enhanced optimisation performance. Hybridisation of modern mathematical modelling optimisation methods is another strategy for performance improvement.…”

Section: Maleki and Askarzadehmentioning

confidence: 99%

Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods

Theo

Lim

et al. 2017

Renewable and Sustainable Energy Reviews

232

105

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“…In [15], SOS (symbiotic organisms search) algorithm, Stud krill herd algorithm [16], grey wolf optimization [17] were employed for multi-DG allocation in radial DNs. Multiple DG placements under different load models using invasive weed optimization algorithm was proposed [18].…”

Section: Related Workmentioning

confidence: 99%

Application of Bird Swarm Algorithm for Allocation of Distributed Generation in an Indian Practical Distribution Network

Sabarinath¹,

Manohar²

2019

IJISA

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This article addresses an optimal allocation of multi Distributed Generation (DG) units in an Indian practical radial distribution network (RDN) for minimization of network loss and voltage deviation. For this work, combined sensitivity index (CSI) is utilized to identify the appropriate positions/locations of DG units. However, the appropriate size of DG is determined through a nature-inspired; population-based Bird Swarm Algorithm (BSA). Secondly, the influence of DG penetration level on network loss and voltage profile is investigated and presented. In this regard, two types of DG technologies (solar and biomass) are considered for loss reduction and voltage deviation reduction. The performance of CSI and BSA methodology is successfully evaluated on an Indian practical 52-bus RDN.

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Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm

Cited by 153 publications

References 27 publications

Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

Assessment of Renewable Distributed Generation in Green Building Rating System for Public Hospital

Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods

Application of Bird Swarm Algorithm for Allocation of Distributed Generation in an Indian Practical Distribution Network

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