Optimal location and sizing of Distributed Generators using a hybrid methodology and considering different technologies

Grisales, Luis Fernando; Grajales, Alejandro; Montoya, Oscar Danilo; Isaza, Ricardo Alberto Hincapié; Echeverri, Mauricio Granada

doi:10.1109/lascas.2015.7250486

Cited by 15 publications

(12 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…• Grisales et al en [15] implementan un GA para la ubicación y el algoritmo PSO para el dimensionamiento de tres tipos diferentes de tecnologías de GD. Presentan una función multi-objetivo ponderada, a partir de las pérdidas de energía, el error cuadrático de tensión y los costos de los generadores.…”

Section: Métodos Híbridosunclassified

Ubicación y dimensionamiento de generación distribuida: Una revisión

Grisales

Cuestas

Jaramillo

2017

Cien.Ing.Neogranadina

View full text Add to dashboard Cite

La generación distribuida (GD) se presenta como un apoyo para suplir la demanda del sistema de forma localizada, lo que permite además como alternativas de generación el uso de fuentes de energía renovables a pequeña escala. Como aporte principal, este artículo presenta las consideraciones que se deben tener en cuenta al momento de analizar, modelar y solucionar el problema de ubicación y dimensionamiento de GD en la red eléctrica de distribución. Inicialmente, se enuncian los aspectos técnicos de la red, el modelado de las cargas e impactos de la GD; seguido de la formulación del modelo matemático del problema, principales técnicas de solución y metodologías aplicadas en la literatura; finalmente, se muestran las investigaciones futuras en este campo de estudio. Todo lo anterior en busca de mejorar las condiciones operativas de la red. Dentro de la revisión de los trabajos presentados por los diferentes autores, se encontró que una gran parte de los estudios se enfocan en los aspectos técnicos, sin tener en cuenta los costos asociados a la integración de GD, ni los incentivos económicos a los que puede ser susceptibles este tipo de proyectos, que son de vital importancia para evaluar la viabilidad de la propuesta de integración.

show abstract

Section: Métodos Híbridosunclassified

Ubicación y dimensionamiento de generación distribuida: Una revisión

Grisales

Cuestas

Jaramillo

2017

Cien.Ing.Neogranadina

View full text Add to dashboard Cite

show abstract

“…The introduction of DGs into distribution network has economic and environmental implications depending on the type of energy sources employed. This has prompted researchers such as Liu et al (2011), Grisales et al (2015); Mohamed et al (2015); Adefarati and Bansal (2017a, 2017b) to assess the economic effects of introducing DGs into distribution network. The economic evaluation by Liu et al (2011) was based on the cost of transmission loss.…”

Section: Introductionmentioning

confidence: 99%

“…The economic evaluation by Liu et al (2011) was based on the cost of transmission loss. On the other hand, the economic assessment by Grisales et al (2015), Mohamed et al (2015); Olatomiwa et al (2015); Adefarati and Bansal (2017a, 2017b) were based on the cost of generation from various energy sources. Additionally, the cost of energy (COE) was included in the assessment by Mohamed et al (2015); Adefarati and Bansal (2017a, 2017b).…”

Section: Introductionmentioning

confidence: 99%

A framework for the techno-economic and reliability analysis of grid connected microgrids

Amewornu

Nwulu

2020

JEDT

View full text Add to dashboard Cite

Purpose This research studies the impact of introducing distributed generators (DGs) into a distribution network. The aim of this paper is to optimally site DGs based on economic, environmental and reliability indices are presented. Design/methodology/approach The considered network was modelled by using the network’s line parameters and capacity of the load bus with the help of Power System Analysis Toolbox. The location of the DG is based on voltage stability index and power loss reduction index. The DG energy sources considered are the diesel generator, solar photo-voltaic (PV) and wind generator, and the objectives were to minimize cumulative cost while maximizing reliability of the network. The Advanced Interactive Multidimensional Modelling System was used for the mathematical modelling. Findings The obtained results in the cases of introducing renewable energy into a network improves network performance. The benefits of renewable energy on the distribution network measured in terms of electricity production cost, gas emission cost, fuel cost and value of energy not supplied were positive. The research also showed that the total benefit of renewable energy reduces as the price of the renewable generators increases. Originality/value This paper introduces a new approach to determining the optimal location of DG for reducing line losses and improved voltage profile. A new cost modelling function based on external grid power transfer cost, technical losses and cost because of the various energies source is also introduced.

show abstract

“…Genetic Algorithm was proposed in [10] to obtain the optimum location and size of DGs for power losses minimization of IEEE 14-bus system. In [11], a combination of PSO and Chu-Beasly genetic algorithm was proposed to determine the optimal size and location of DGs so that the power losses are minimized in IEEE 33-bus and IEEE 69-bus systems. Another combination of tabu search and branch exchange optimization techniques was presented in [12] to determine the optimal location and size of DGs so that the power losses are minimized.…”

Section: Introductionmentioning

confidence: 99%

Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer

Kamel¹,

Awad²,

Abdel-Mawgoud³

2019

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

High penetration of photovoltaic and wind turbine-based distributed generators (DGs) can help reduce carbon emissions which is an important goal for the whole world. DG can be used to improve the voltage stability, present generation reserve/emergency, and consequently, the system power quality can be improved. However, it is very important to select the right size and location of a DG so that the power system can increase the gained benefits of such an installation to the maximum. In this paper, a hybrid optimization technique is proposed to determine the optimal allocation of DG in the standard IEEE 33-bus radial distribution system in order to improve the voltage stability and minimize the total power loss. The proposed hyprid technique is based on the gray wolf optimizer algorithm with loss sensitivity factor. The performance of the system is analyzed without DG installation, then it is compared with the performance of the system when DGs are installed with the predefined optimal sizes and locations. The study is performed by MATLAB M-Files and NEPLAN software.

show abstract

Optimal location and sizing of Distributed Generators using a hybrid methodology and considering different technologies

Cited by 15 publications

References 8 publications

Ubicación y dimensionamiento de generación distribuida: Una revisión

Ubicación y dimensionamiento de generación distribuida: Una revisión

A framework for the techno-economic and reliability analysis of grid connected microgrids

Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer

Contact Info

Product

Resources

About