Abstract
In this paper, we propose an energy management model for grid-connected hybrid systems. This model is based on the coupling of a multiple input multiple output (MIMO) AutoRegressive Moving Average with eXogenous inputs (ARMAX) model with generalized predictive control (GPC). The ARMAX model performs input–output mapping of the electrical system data in terms of energy costs and power values. The GPC system receives the input–output mapping provided by the ARMAX model and performs energy management by minimizing the consumed energy cost in the load. Cost minimization is accomplished by optimizing the use of renewable energy sources, thus consuming less energy from the grid. The effectiveness of the proposed model is verified, comparing its computational and experimental results to those of a conventional control model and a model predictive control approach presented in the literature.
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