DG placement in radial distribution network by symbiotic organisms search algorithm for real power loss minimization

Das, B. N.; Mukherjee, V.; Das, Debapriya

doi:10.1016/j.asoc.2016.09.015

Cited by 87 publications

(54 citation statements)

References 56 publications

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“…5,6 Because of the increment of load demand in the recent time, DG can be used as an active power support that can also offer substantial advantages, such as line loss reduction, voltage profile enhancement, and greenhouse gas emission reduction. 1,2 The expansion of an existing network or the construction of new centralized generation units is not practically feasible because of various restrictions.…”

Section: Introductionmentioning

confidence: 99%

“…3 However, for the stable and secure operation of the power system, the enhancement of stability margin is essential in the context of restructured power market. 5,6 Because of the increment of load demand in the recent time, DG can be used as an active power support that can also offer substantial advantages, such as line loss reduction, voltage profile enhancement, and greenhouse gas emission reduction. 5,6 Because of the increment of load demand in the recent time, DG can be used as an active power support that can also offer substantial advantages, such as line loss reduction, voltage profile enhancement, and greenhouse gas emission reduction.…”

Section: Introductionmentioning

confidence: 99%

“…4 These issues divert the attention of distribution system planners towards distributed generation (DG) and distributed static compensator (DSTATCOM). [6][7][8][9] On the contrary, to enhance the stability and power quality, DSTATCOM is also used in radial distribution system (RDS) that can automatically compensate the reactive power according to system's variable load. [6][7][8][9] On the contrary, to enhance the stability and power quality, DSTATCOM is also used in radial distribution system (RDS) that can automatically compensate the reactive power according to system's variable load.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy logic–based rooted tree optimization algorithm for strategic incorporation of DG and DSTATCOM

Sannigrahi

Ghatak

Acharjee

2019

Int Trans Electr Energ Syst

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Summary In this study, a hybrid approach based on fuzzy logic and rooted tree optimization (RTO) algorithm is proposed for the strategic incorporation of distributed generation (DG) and distributed static compensator (DSTATCOM) in radial distribution system (RDS) to improve voltage profile, reduce losses, and maximize economic and environmental benefits. Fuzzy logic is applied to bring the objectives in the same range, and using RTO technique, the optimal site and size of the devices are determined. Considering the uncertainty in DG's output and time‐varying system load, the proposed technique is tested on 69‐bus and 118‐bus RDSs, and to check the accuracy and feasibility, the simulation results are compared with other existing techniques. The Wilcoxon signed rank test (WSRT) is applied to confirm the superiority of the proposed algorithm. Furthermore, comparative performance analysis is conducted between different planning schemes for facilitating the distribution system planner to select the most suitable one.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy logic–based rooted tree optimization algorithm for strategic incorporation of DG and DSTATCOM

Sannigrahi

Ghatak

Acharjee

2019

Int Trans Electr Energ Syst

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“…Banerjee and Chattopadhyay presented a novel modified SOS to design an improved three-dimensional turbo code [53]. Das et al used SOS to determine the optimal size and location of distributed generation (DG) in radial distribution network (RDN) for the reduction of network loss [54]. Dosoglu et al utilized SOS for economic/emission dispatch problem in power systems [55].…”

Section: Introductionmentioning

confidence: 99%

Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

Zhou

Luo

et al. 2016

Computational Intelligence and Neuroscience

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Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs). In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

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“…In distribution network voltage profile improvement and voltage stability issues have been taken as objectives in Aman et al (2012), Sultana et al (2016) and Singh and Parida (2016). Das et al (2016) proposed symbiotic organisms search algorithm for DG placement. Zeinalzadeh et al (2015), Khodabakhshian and Andishgar (2016) and Rahmani-andebili (2016) proposed simultaneous DGs and capacitors placement in distribution networks.…”

Section: Open Accessmentioning

confidence: 99%

Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

2017

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Distributed generator (DG) resources are small scale electric power generating plants that can provide power to homes, businesses or industrial facilities in distribution systems. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Whale optimization algorithm (WOA), a novel metaheuristic algorithm, is used to determine the optimal DG size. WOA is modeled based on the unique hunting behavior of humpback whales. The WOA is evaluated on IEEE 15, 33, 69 and 85-bus test systems. WOA was compared with different types of DGs and other evolutionary algorithms. When compared with voltage sensitivity index method, WOA and index vector methods gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf.

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DG placement in radial distribution network by symbiotic organisms search algorithm for real power loss minimization

Cited by 87 publications

References 56 publications

Fuzzy logic–based rooted tree optimization algorithm for strategic incorporation of DG and DSTATCOM

Fuzzy logic–based rooted tree optimization algorithm for strategic incorporation of DG and DSTATCOM

Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

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