A scenario-based economic-stochastic model predictive control for the management of microgrids

MARTIN ALARCON; RODRIGO ALARCON; GONZÁLEZ, ALEJANDRO HERNÁN; FERRAMOSCA, ANTONIO

Sustainable Energy, Grids and Networks

ELSEVIER

Año: 2023 vol. 36

2352-4677

The world’s electricity generation is heavily dependent on the consumption of fossil fuels. Electric generationfrom renewable resources is necessary due to the imperative need to reduce greenhouse gases to avoid a climatecrisis. These resources exhibit random and intermittent behaviour. Therefore, there is a need to develop newmanagement and control tools for these insertions into the current electricity system. Microgrids have becomean effective tool to solve this problem, where these control systems play a principal role. For this reason,an optimal control structure consisting of two Model Predictive Control strategies is proposed for a microgridEnergy Management System. The first controller aims to optimise the microgrid’s economic performance underan established criterion, using nominal forecasts of the disturbances on the system, such as the energy generatedby renewable resources. The second is a stochastic approach using scenario-based methods to consider forecasterrors in the nominal predictions used for the disturbances. The simulations were carried out on a microgridmodel corresponding to the National Technological University, Reconquista Regional Faculty, highlighting thatactual samples of energy consumption are available. It is worth noting that with the proposed structure, optimalsolutions are obtained considering the random behaviour of the disturbances, without making assumptionsabout the distribution functions of the random variables. Moreover, it applies to different scales of microgrids.