Long-short term memory applied to energy management systems in microgrids

In this research paper, we implemented a Long-Short Term Memory neural network for climate variable prediction and employed the interior point method to optimize the energy management of a microgrid. Our objective was to reduce the dependence on diesel generators and minimize the associated costs. By prioritizing technological alternatives over exclusive reliance on diesel generators, we achieved a substantial 10
^%
reduction in diesel generator costs in comparison to the energy management-free model.