Towards Digital Twins of Small Productive Processes in Microgrids

Abstract

In microgrids (MGs), energy management systems (EMSs) have been using increasingly detailed models of generation units, loads, and networks to make decisions on the power/energy contribution of each available unit to meet the electrical energy demand. This work aims to investigate the use of digital twins (DT) of small productive processes (SPPs) to regulate endogenous process variables to ensure final product quality, while the expected power consumption is estimated and communicated to the EMS so that it can make its decisions on the participation of each power source in meeting the electrical energy demand. The literature review reveals that this is one of the first attempts, in the context of MGs, to generate DT for SPPs that combine not only the electrical energy consumption, but also link it with the energy/mass balances taking place in the SPPs, highlighting the complexity that SPPs have as electrical loads. The results demonstrate that environmental conditions significantly influence the final electrical consumption of the SPPs. Additionally, the MG exhibits better economic performance when the SPP DT supports EMS decision-making, which is of great importance in MGs due to the special conditions they have for electric power generation, being more challenging in isolated MGs.