Multi-Objective Optimal Placement and Sizing of DGs by Hybrid Fuzzy TOPSIS and Taguchi Desirability Function Analysis Approach

Galgali, Varsha S.; Ramachandran, M; Vaidya, G. A.

doi:10.1080/15325008.2021.1925377

Cited by 5 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, there are two techniques for optimal locating and size of DG units (Memarzadeh and Keynia 2020), which are: The 53 first methods based on optimization (El-Fergany 2015; Ali et al 2017;Wang et al 2014;Singh et al 2020;ChithraDevi et al 2017;Abdelaziz et al 2015;Galgali et al 2021;Ismael et al 2018;Diaaeldin et al 2019;Manna and Goswami 2020;Kumar et al 2020;Huy et al 2020;García and Mena 2013). For example, Ali et al (2017) proposed Ant Lion Optimization Method (ALOA) for optimal location and sizing of DG based renewable sources for various Distribution Networks.…”

Section: Introductionmentioning

confidence: 99%

“…1 Benefits with DG integration optimal planning of dispatchable DG. Galgali et al (2021) proposed an optimal placement of DG as a multi-criteria decision-making (MCDM) case and candidate buses are systematically evaluated by applying Fuzzy TOPSIS. Ismael et al (2018) proposed the Crow Search Method (CSA) for the sizing and placement of DG in distribution networks.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new optimal allocation of DGs in distribution networks by using coot bird optimization method

Memarzadeh,

Arabzadeh,

Keynia

2023

Energy Inform

View full text Add to dashboard Cite

Energy is one of the most important topics in the world today and is considered as one of the most effective factors for the development of countries. Due to the limitation of non-renewable energy sources and undesirable effects of consuming these resources on the environment, the strategy of countries has changed towards the use of renewable energy. Renewable energy sources do not decrease over time and operate independently of price fluctuations and are more available, thus being able to play a greater role in modern power systems. Therefore, the optimal location and use of these resources will have an impact on modifying the parameters of the power grid. In this paper an analytical approach for optimal placement and sizing of distributed generation (DG) in power distribution networks to minimize the power loss, bus voltage limits, DG capacity limits, current limits, and DG penetration limit. In the first step, determines the DG capacity causing maximum benefit at different buses, and then selects the best location for DG placement which corresponds to highest benefit in the buses. This method is applicable for sizing and siting of single as well as multiple DG units. The coot bird optimization method (CBOM) is proposed for solving optimal placement, size, and power factor (PF) of DG in distribution network. The suggested method is tested on the IEEE 33-bus, 69-bus, Distribution Networks. The proposed CBOM method has good performance to find optimal placement, size, and PF of DG and it can be applied for various distribution system.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new optimal allocation of DGs in distribution networks by using coot bird optimization method

Memarzadeh,

Arabzadeh,

Keynia

2023

Energy Inform

View full text Add to dashboard Cite

show abstract

“…Distributed generator (DG) is a possible substitute for installing a new centralized generation station, particularly in the era of deregulation and it has several benefits such as low investment risk and short installation period (Gissey et al, 2021;Khaligh and Buygi, 2020;Martinez-Bolanos et al, 2020;Moret et al, 2020;Yang et al, 2020), modules with small capacity that can monitor variations in load very closely (Jiang et al, 2020;Mahmud et al, 2020;Somefun et al, 2020), small physical size suitable for installation at proximity to users' end, and availability of a large range of DG technologies (Nagaballi and Kale, 2020;Yang et al, 2021). However, it is important to note that when DGs are to be introduced into a distribution network, consideration should be to optimally site and size DG units otherwise, there will be an increase in power losses and a decrease in reliability levels (Balu and Mukherjee, 2020;Deb et al, 2020;Farzinfar et al, 2020;Galgali et al, 2021;Kizito et al, 2020;Manna and Goswami, 2020;Shuaibu et al, 2020;Truong et al, 2020). In recent time, there have been rise in the study of distributed generation in power system analysis.…”

Section: Introductionmentioning

confidence: 99%

Review of Different Methods for Siting and Sizing Distributed Generator

Somefun

Popoola

Abdulkareem

et al. 2022

IJEEP

View full text Add to dashboard Cite

Distributed generator has been confirmed to be a means by which installation of a new centralized generator can be delayed or postponed in the era of deregulation. It helps to minimize line losses and improve voltage profile. the benefits associated with distributed generator can be greatly harnessed when DG is optimally sited and sized within power system network. In this study, different methods used by previous researchers were extensively reviewed. The summary of the methodologies from previous works were itemized one after the other. This was done under the impact of distributed generator in a network. These methodologies are summaries under three categories namely; analytical, meta-heuristic and hybrid optimization methods. All the methods are based on solving non-linear load flow solution except the Inherent Structural Network Topology. In this review work, the inherent structural network topology is recommended for further studies to solve power system problems.

show abstract

Decision-making in multi-objective DG planning for distribution system via Shannon’s entropy

Gupta,

Yadav,

Singh

et al. 2024

Electr Eng

View full text Add to dashboard Cite

Multi-Objective Optimal Placement and Sizing of DGs by Hybrid Fuzzy TOPSIS and Taguchi Desirability Function Analysis Approach

Cited by 5 publications

References 30 publications

A new optimal allocation of DGs in distribution networks by using coot bird optimization method

A new optimal allocation of DGs in distribution networks by using coot bird optimization method

Review of Different Methods for Siting and Sizing Distributed Generator

Decision-making in multi-objective DG planning for distribution system via Shannon’s entropy

Contact Info

Product

Resources

About