Static and dynamic environmental economic dispatch using tournament selection based ant lion optimization algorithm

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

  • H. Vennila
  • Nimay Chandra Giri
  • Pampa Sinha
  • Mohit Bajaj
  • Mohamad Abou Houran
  • Salah Kamel

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number972069
Journal / PublicationFrontiers in Energy Research
Volume10
Online published7 Sep 2022
Publication statusPublished - 2022

Link(s)

Abstract

The static and dynamic economic dispatch problems are solved by creating an enhanced version of ant lion optimisation (ALO), namely a tournament selection-based ant lion optimisation (TALO) method. The proposed algorithm is presented to solve the combined economic and emission dispatch (CEED) problem with considering the generator constraints such as ramp rate limits, valvepoint effects, prohibited operating zones and transmission loss. The proposed algorithm’s efficiency was tested using a 5-unit generating system in MATLAB R2021a during a 24-hour time span. When compared to previous optimization methods, the suggested TALO reduces the costs of fuel and pollution by 9.01 and 4.7 percent, respectively. Furthermore, statistical analysis supports the suggested TALO optimization superiority over other methods. It is observed that the renewable energy output can be stabilized in the future by combining a hybrid dynamic economic and emission dispatch model with thermal power units, wind turbines, solar and energy storage devices to achieve the balance between operational costs and pollutant emissions.

Research Area(s)

  • ant lion optimizer, tournament selection ant lion optimization, combined static and dynamic economic emission dispatch, valve point loading, optimization

Citation Format(s)

Static and dynamic environmental economic dispatch using tournament selection based ant lion optimization algorithm. / Vennila, H.; Giri, Nimay Chandra; Nallapaneni, Manoj Kumar; Sinha, Pampa; Bajaj, Mohit; Abou Houran, Mohamad; Kamel, Salah.

In: Frontiers in Energy Research, Vol. 10, 972069, 2022.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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