A novel decision-making approach based on a decision tree for micro-grid energy management

Abstract

Environmental challenges such as climate change have accelerated humanity's need for renewable alternative energy sources. For this reason, we propose in this paper a decision-making strategy that allows controlling the flows of energy into a micro-grid (MG) compound of solar energy, batteries, and diesel generator (DG), and connected to the distributed network (DN). Therefore, the power supply to the loads is obtained either from the energy produced by solar sources, from the batteries, from the DN, or from the DG when renewable energy (RE) and batteries are depleted. To make the final decision, we consider four parameters at the same time: the energy produced by solar energy, the requested load, the state of charge of batteries (SoC), and the purchase or sale price. Decision tree (DT) is used to build the energy management strategy to ensure the availability of power on demand by making logical decisions about charging batteries, discharging batteries, buying necessary energy from DN, selling excess energy to DN, and recovering necessary energy from DG. The suggested DT approach is applied to a real MG to minimize the cost-benefit balance, and the comparison analysis demonstrates good results when compared to related works.

Support vector regression-based state of charge estimation for batteries: cloud vs non-cloud

“…The use of batteries offers significant advantages in energy management strategies. Batteries play a crucial role in storing excess energy during periods of low demand and releasing it when demand is high, contributing to load balancing and grid stability [4]- [8]. They serve as a valuable tool in optimizing the integration of renewable energy sources, allowing for better management of intermittent energy production [9]- [12].…”