Skip to main content

Advanced Search

Projected result for your current search: 0

Search Operators:

You can use operators in your search query to narrow down your results even more. Click on the search operator to see an explanation of how it works.
Finds documents with exactly this word group, in exactly this word order and spelling (e.g. "employer branding").
Finds documents with both search terms (e.g. sales AND bonus).
Finds documents with one or the other search term (e.g. porsche OR volkswagen).
Finds documents with all search terms. Blank space is understood as AND (e.g. man robot production).
Finds documents with no appearance of the word behind NOT (e.g. ford NOT "harrison ford").
Finds documents where the search term is mentioned at least "n" times."n" may be any number (e.g. COUNT(gear)>8).
Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Finds documents with the search term in different spellings. "?" allows only one character (e.g. organi?ation).
Special characters are understood as AND (e.g. Miller Bros. & Sons).

Semantic Search

powered by (Link opens in a new window)
loading …
Log in
Top
Electrical Engineering

Hybrid optimization for energy management in smart grids using Golden Jackal algorithm and deep convolutional neural networks

  • 02-02-2025
  • Original Paper
Published in:
Authors
S. Chithra
C. Arunachalaperumal
R. Rajagopal
P. Meenalochini
Published in
Electrical Engineering | Issue 6/2025

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The article introduces a hybrid optimization method for energy management in smart grids using Golden Jackal Optimization (GJO) and Tree Hierarchical Deep Convolutional Neural Networks (THDCNN). This innovative approach aims to enhance power balance, efficiency, and stability in microgrids by effectively integrating renewable energy sources and battery storage systems. The study addresses challenges such as optimal unit commitment, generator dispatch, and the unpredictability of renewable energy sources. The proposed GJO-THDCNN technique demonstrates improved performance in both fixed and variable load scenarios, outperforming existing methods like Giza Pyramid Construction, fuzzy logic, and Convolutional Neural Networks. The article provides detailed simulations and comparative analyses, highlighting the superior stability and efficiency of the GJO-THDCNN method in managing energy within smart grids.
AI Generated

This summary of the content was generated with the help of AI.

Please log in to get access to your license.

Log in Register for free

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Business + Economics & Engineering + Technology"

Online-Abonnement

Springer Professional "Business + Economics & Engineering + Technology" gives you access to:

  • more than 102.000 books
  • more than 537 journals

from the following subject areas:

  • Automotive
  • Construction + Real Estate
  • Business IT + Informatics
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Mechanical Engineering + Materials
  • Insurance + Risk


Secure your knowledge advantage now!

inform now

Springer Professional "Engineering + Technology"

Online-Abonnement

Springer Professional "Engineering + Technology" gives you access to:

  • more than 67.000 books
  • more than 390 journals

from the following specialised fileds:

  • Automotive
  • Business IT + Informatics
  • Construction + Real Estate
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Mechanical Engineering + Materials





 

Secure your knowledge advantage now!

inform now

Springer Professional "Business + Economics"

Online-Abonnement

Springer Professional "Business + Economics" gives you access to:

  • more than 67.000 books
  • more than 340 journals

from the following specialised fileds:

  • Construction + Real Estate
  • Business IT + Informatics
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Insurance + Risk



Secure your knowledge advantage now!

inform now
previous article Research on fault diagnosis method for photovoltaic array based on model fusion
next article Research on the improvement of dynamic and steady-state performance of grid-connected inverters based on fuzzy adaptive control under weak grid conditions
Title
Hybrid optimization for energy management in smart grids using Golden Jackal algorithm and deep convolutional neural networks
Authors
S. Chithra
C. Arunachalaperumal
R. Rajagopal
P. Meenalochini
Publication date
02-02-2025
Publisher
Springer Berlin Heidelberg
Published in
Electrical Engineering / Issue 6/2025
Print ISSN: 0948-7921
Electronic ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-025-02958-3
This content is only visible if you are logged in and have the appropriate permissions.

Other articles of this Issue 6/2025

Comparative analysis of methods for obtaining equivalent capacitance in single-layer EMI filter inductors

  • Original Paper

Study on the longitudinal protection of low-frequency transmission lines for offshore wind power based on the difference of the absolute value of the imaginary part of the integrated impedance

  • Original Paper

Reliable solar PV on-site generation for EV charging management in commercial buildings using LBO-DTRSRN approach

  • Original Paper

Research on the improvement of dynamic and steady-state performance of grid-connected inverters based on fuzzy adaptive control under weak grid conditions

  • Original Paper

Sustainable microgrid operations: multi-objective hybrid optimization for combined economic emission dispatch

  • Original Paper

A second-order cone programming-based microgrid bidding strategy considering real-time market price correlation

  • Original Paper