Optimal placement of distributed generation using firefly algorithm

Lakshmi, G. V. Naga; Jayalaxmi, A.; Veeramsetty, Venkataramana

doi:10.1088/1757-899x/981/4/042060

Cited by 18 publications

(4 citation statements)

References 20 publications

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“…3. [14] 33,69 Minimization of losses GA Haesen et al [15] 69 Minimization of losses GA Singh and Goswami [16] 33 Minimization of losses GA Singh et al [17] 16,37 Minimization of losses GA Veeramsetty et al [18] 69 Minimization of losses GA Prommee and Ongsakul [19] 69 Minimization of energy losses PSO El-Zonkoly [20] 30 Minimization of power losses PSO Wang and Singh [21] 13,33 Multiple objectives ACO Abu-Mouti and El-Hawary [22] 69 Maximize voltage limit ABC Rao et al [23] 33,69 Maximize EG Capasity HS Ghosh et al [24] 6,14,30 Maximize EG Capasityt PH Koutroumpezis and Safigianni [25] 31 Minimization of energy losses PH Mohd Ikhwan et al [26] 11/0.4kV Reliability improvement MCS Lakshmi et al [27] 15,69 Minimization of power losses FA Fathi and Ghiasi [28] 33 Minimum DG investment cost GA, PSO Generation capacity of DG unit i.e. P g and location are the decision variables.…”

Section: Mathematical Modeling Of Dg Placement Optimization Problemmentioning

confidence: 99%

Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm

Lakshmi

Jayalaxmi

Veeramsetty

2021

Technol Econ Smart Grids Sustain Energy

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Optimal placement of distributed generation (DG) is an essential task for distribution companies in order to operate the distribution network in good operating conditions. Optimal placement of DG units is an optimization problem where minimization of active power losses in the network is considered as an objective function. In this paper, hybrid genetic dragonfly algorithm is used as an optimization technique to find the optimal location and size of distributed generation units. The proposed algorithm is implemented on IEEE 15 and PG & E 69 bus distribution systems in MATLAB environment. Based on the simulation results it has been observed that with proper placement and size of DG units, distribution network can be operated with less active power losses.Keywords Distributed generation • Optimal placement • Hybrid genetic dragonfly algorithm • Active power loss Nomenclature ΔY t+1 Step vector for dragonflies A iAlignment value of dragonfly i C i Cohesion value of dragonfly i E iEnemy source of dragonfly i F iFood source of dragonfly i I k i Current at bus 'i' and iteration 'k' I k LR Current injecting at receiving node of line 'L' at iteration 'k' I l Current flowing through line l I k L Current through line 'L' at iteration 'k' I max l

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Section: Mathematical Modeling Of Dg Placement Optimization Problemmentioning

confidence: 99%

Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm

Lakshmi

Jayalaxmi

Veeramsetty

2021

Technol Econ Smart Grids Sustain Energy

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“…The present conventional overcurrent protection scheme adopted is only modeled to operate for a radial distribution network with only directional power flow. To fully reap the benefits of DG integration, the appropriate allocation of the DG to be integrated into distribution networks are required [2]. The integration of DG optimally reduces system losses by up to 47%, power purchase costs by up to 92%, and energy not supplied costs by 40% [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal Location and Sizing of Dg in Distribution Network: Impact on Overcurrent Distribution Protection Scheme

Adeleye,

Ajewole,

Momoh

2024

UJEES

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The integration of distributed generation (DG) into the existing distribution networks minimizes active power losses and improves the voltage profile. The recent improvement in the development of DG technology has caused increase in the penetration of DG from different sources. The optimal location and sizing of DG is very challenging and introduces different protection issues. This is caused by penetration of current flow from different source which is contrary to the principles of operation of the conventional overcurrent scheme. This paper presents optimal method of DG placement and sizing using firefly algorithm and its impact of DG penetration on overcurrent protection scheme. Low voltage distribution network is modelled and simulated in PSCAD/EMTDC and DigSilent power factory software using IEEE 33 and Ayepe 34 standard bus. False tripping of feeders, Nuisance tripping, blinding of the protection scheme and unintentional islanding caused as result of Photovoltaic penetration into the distribution network were simulated. Coordination of overcurrent relays with and without DG penetration were analyzed and possible mitigation algorithm were proposed. The simulation result obtained showed that the proposed methods significantly improve the protection scheme coordination..

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“…Restructuring electrical power utilities, increasing load demand, technical innovation, concern for greenhouse gas emissions, improving voltage and loss reduction are some of the key reasons for increasing the penetration of Distributed Generator (DG) units into the distribution network [1][2][3]. In addition, DG Units can provide customers with freedom and flexibility in planning and developing installations according to load criticality [4].…”

Section: Introductionmentioning

confidence: 99%

Shapley value cooperative game theory-based locational marginal price computation for loss and emission reduction

Veeramsetty

2021

Prot Control Mod Power Syst

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An iterative method based on Shapley Value Cooperative Game Theory is proposed for the calculation of local marginal price (LMP) for each Distributed Generator (DG) bus on a network. The LMP value is determined for each DG on the basis of its contribution to reduce loss and emission reduction, which is assessed using the Shapley Value approach. The proposed approach enables the Distribution Company (DISCO) decision-maker to operate the network optimally in terms of loss and emission. The proposed method is implemented in the Taiwan Power Company distribution network 7 warnings consisting of 84 buses and 11 feeders in the MATLAB environment. The results show that the proposed approach allows DISCO to operate the network on the basis of its priority between the reduction of active power loss and emission in the network

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Optimal placement of distributed generation using firefly algorithm

Cited by 18 publications

References 20 publications

Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm

Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm

Optimal Location and Sizing of Dg in Distribution Network: Impact on Overcurrent Distribution Protection Scheme

Shapley value cooperative game theory-based locational marginal price computation for loss and emission reduction

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