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 language | English |
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Title of host publication | 2021 6th International Symposium on Environment Friendly Energies and Applications |
Publisher | IEEE Explore |
Number of pages | 6 |
ISBN (Electronic) | 978-1-7281-7011-4 |
ISBN (Print) | 978-1-7281-7012-1 |
DOIs | |
Publication status | Published - 21 Apr 2021 |
Event | 6th International Symposium on Environment Friendly Energies and Applications - Vitosha Park Hotel/Technical University of Sofia, Sofia, Bulgaria Duration: 24 Mar 2021 → 26 Mar 2021 Conference number: 6th http://efeaconf.com/ |
Publication series
Name | |
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ISSN (Print) | 2641-5925 |
ISSN (Electronic) | 2688-2558 |
Conference
Conference | 6th International Symposium on Environment Friendly Energies and Applications |
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Abbreviated title | EFEA 2021 |
Country/Territory | Bulgaria |
City | Sofia |
Period | 24/03/21 → 26/03/21 |
Internet address |
Keywords
- hybrid renewable energy system
- size and configuration optimisation
- ant colony algorithm
- MOHRES