Multi-objective long-term reconfiguration of autonomous microgrids through controlled mutation differential evolution algorithm

Multi-objective long-term reconfiguration of autonomous microgrids through controlled mutation differential evolution algorithm

This study provides a solution for the feeder reconfiguration of autonomous microgrids (MGs). The objective is to minimise power loss, switching costs, and enhance voltage stability index, considering time-variations of loads. The daily load profiles for different seasons (spring, summer, fall, and...

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Bibliographic Details
Main Authors: Khalil Gholami, Saeed Jazebi
Format: Article
Language:English
Published: Wiley 2020-10-01
Series:IET Smart Grid
Subjects:
power generation control
optimisation
distributed power generation
evolutionary computation
smart power grids
power system stability
power distribution control
voltage control
multiobjective long-term reconfiguration
autonomous microgrids
feeder reconfiguration
daily load profile
dynamic network reconfiguration
long-term reconfiguration problem
invasive weed optimisation algorithm
controlled mutation differential evolution algorithm
power loss minimisation
switching costs
voltage stability index
optimisation problem
k-means algorithm
33-bus autonomous mg
69-bus autonomous mg
smart grid environment
Online Access:https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0328

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https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2019.0328

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