Cite as: Shariati, Omid (2024): Elitist Genetic Algorithm (EGA)-based Energy Storage System (ESS)-facilitated Heavy Good Electric Vehicle (HGEV) charging station Designer. University of Reading. Software. https://doi.org/10.17864/1947.000526

Copyright 2024 University of Reading. This code is made available under the terms of the GNU General Public License 3.0: https://www.gnu.org/licenses/gpl-3.0.html. The accompanying documentation is issued under a Creative Commons Attribution 4.0 International License: https://creativecommons.org/licenses/by/4.0/.


%-------------------Introduction to Elitist Genetic Algorithm (EGA)-based Energy Storage System (ESS)-Facilitated--------------- 
%--------------------------------------Heavy Good Electric Vehicle (HGEV) Charging Station Designer----------------------------- 
% Introducing the "HGEV Charging Station EGA-based Design Package": 
% This solution leverages an Elitist Genetic Algorithm (EGA) to tackle interconnected challenges in Energy Storage System (ESS) 
% design and demand-side management, particularly focusing on battery scheduling. It addresses these concerns simultaneously for 
% diverse styles of Heavy Goods Electrical Vehicle (HGEV) Depots and on-route charging stations. The ESS design encompasses 
% considerations like battery capacity and power electronic board rating power, while demand-side management involves a series of 
% battery charging/discharging power scheduling within the evaluation time window.
%------------------------------------------------------------------------------------------------------------------------------
%---Note: Before proceeding, please unzip the folder "HGEV_ChargingStation_EGADesigner" and carefully follow the 
% instructions provided in the Application Guide file located within.----------------------------------------------------------