Modernized Planning of Smart Grid Based on Distributed Power Generations and Energy Storage Systems Using Soft Computing Methods

The modest objective is to check the integrated effect of energy storage systems (ESSs) and distributed generations (DGs) and compare the optimization of the size and location of ESS and DG to explore its challenges for smart grids (SGs) modernization. The research enlisted different algorithms for...

Full description

Autores:
Rajagopalan, Arul
Swaminathan, Dhivya
Alharbi, Meshal
Sengan, Sudhakar
Montoya, Oscar Danilo
El-Shafai, Walid
. Fouda, Mostafa M
Aly, Moustafa H.
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12389
Acceso en línea:
https://hdl.handle.net/20.500.12585/12389
Palabra clave:
Placement;
Active Distribution Network;
Voltage Stability
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description
Summary:The modest objective is to check the integrated effect of energy storage systems (ESSs) and distributed generations (DGs) and compare the optimization of the size and location of ESS and DG to explore its challenges for smart grids (SGs) modernization. The research enlisted different algorithms for cost-effectiveness, security, voltage control, and less power losses. From this perspective, optimization of the distribution network’s energy storage and capacity are being performed using a variety of methods, including the particle swarm, ant-lion optimization, genetic, and flower pollination algorithms. The experimental outcomes demonstrate the effectiveness of these techniques in lowering distribution network operating costs and controlling system load fluctuations. The efficiency and dependability of the distribution network (DN) are both maximized by these strategies. © 2022 by the authors.