An Ant Colony Algorithm for HRES Size and Configuration Optimisation

Mohammed Hussain A Althani, Alireza Maheri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An Ant colony algorithm (ACO) is proposed for hybrid renewable energy system size and configuration optimisation using continuous search space approach. In the proposed algorithm the pheromone distribution across search space is determined by gaussian distribution, and the probabilistic path selection is performed based on pheromone deposit value via roulette wheel principle. The ACO algorithm is implemented in the software tool MOHRES and three case studies are conducted to optimise the size and configuration of standalone hybrid renewable energy system derived from the full configuration wind-PV-battery-diesel-FC Electrolyser system. To evaluate the performance of the proposed ACO, the optimum solutions are compared with the solutions obtained by the genetic algorithm (GA) optimisation algorithm implemented in MOHRES.
Original languageEnglish
Title of host publication6th International Symposium on Environment Friendly Energies and Applications
PublisherIEEE Explore
Number of pages6
Publication statusAccepted/In press - 30 Nov 2020
Event6th International Symposium on Environment Friendly Energies and Applications - Vitosha Park Hotel/Technical University of Sofia, Sofia, Bulgaria
Duration: 24 Mar 202126 Mar 2021
Conference number: 6th
http://efeaconf.com/

Conference

Conference6th International Symposium on Environment Friendly Energies and Applications
Abbreviated titleEFEA 2021
CountryBulgaria
CitySofia
Period24/03/2126/03/21
Internet address

Keywords

  • hybrid renewable energy system
  • size and configuration optimisation
  • ant colony algorithm
  • MOHRES

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