Open AccessSolar Hydrogen System Configuration Using Genetic Algorithms
Author(s) -
Ikram Ahamed Mohamed
Publication year - 2021
Publication title -
al-ṭāqaẗ al-s̆amsiyyaẗ wa-al-tanmiyyaẗ al-mustadāmaẗ/solar energy and sustainable development
Language(s) - English
Resource type - Journals
eISSN - 2414-6013
pISSN - 2411-9636
DOI - 10.51646/jsesd.v1i1.29
Subject(s) - photovoltaic system , genetic algorithm , stack (abstract data type) , computer science , generator (circuit theory) , algorithm , code (set theory) , power (physics) , electronic engineering , electrical engineering , engineering , physics , set (abstract data type) , quantum mechanics , machine learning , programming language
For standalone power supply systems based on solar hydrogen technology to work efficiently, the photovoltaic generator and electrolyser stack have to be con?gured so that they produce the needed amount of hydrogen in order for the fuel cell to produce sufficient power to operate the load. This paper discusses how genetic algorithms were applied to optimise the design of the photovoltaic generator and electrolyser combination by searching for the best con?guration in terms of number parallel and series PV modules, number of electrolyser cells, and cell surface area. First, a mathematical simulation model based on the current-voltage PV characteristics and the polarisation characteristics of the electrolyser was developed. The models parameters were obtained by ?tting the mathematical models to experimental data. A genetic algorithm code was then developed. The code is based on the PV and electrolyser models as an evaluation measure for the ?tness of the solutions generated. Results are presented con?rming the effectiveness of using the genetic algorithm technique for solar hydrogen system con?guration.