High Stress Economic Scenario on Renewable Energy Integration with Genetic-Firework Hybrid Algorithm

Abstract

This work models a hard economic scenario in which inflation rate is set to 7%, the price of diesel is increasing, the price of electricity purchased from the power grid is inflated and there is a top limit for daily purchasable electricity on a region, in which there is an attempt to introduce renewable energy on a private property of the size of a residential house of 5 people. The optimal microgrid configuration is approximated by the new Hybrid Genetic-Fireworks Algorithm working in conjunction with a Monte Carlo simulation to find the annual worth, and comparing results with a Genetic Algorithm and a Fireworks Algorithm. The components considered are: solar panels, wind turbines, diesel generators, electric batteries, converters, and a connection to the power grid. The objective is to maximize annual worth. The results show that a cost of energy (COE) of 2.0603 USD per kWh is achievable in such scenario, and recommends the further use of the Hybrid Genetic-Fireworks Algorithm for this type or Renewable Energy Integration studies, as it outperformed their 2 counterparts in this work.
 
 Received: 12 January 2024 / Accepted: 19 February 2024 / Published: 5 March 2024