Optimal mathematical operation of a hybrid microgrid in islanded mode for improving energy efficiency using deep learning and demand side management
Deep learning method is used to predict the future value of load demand. Based on obtained results, a new model based on the forward-backward load shifting and unnecessary load shedding is presented. As well, to increase energy efficiency, excess renewable energy has been used to produce green hydrogen. For this purpose, GAMS optimization software has been used for optimal operation of the microgrid in the presence of renewable energy sources, battery, diesel generator, aqua electrolyzer, and fuel cell considering demand side management (DSM) restrictions. The obtained results from the proposed model of the considered microgrid show that the huge amount of excess electricity can be saved to enhance energy efficiency. This issue increases green hydrogen production that can be used for fuel cell consumption. As well, the proposed model provides lower cost of operation cost. In addition, the diesel generator consumes lower diesel fuel.
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