An advanced double-layer adaptive energy management system for short-term microgrid operation planning is developed and presented in the thesis. The double-layer energy management system consists of two interconnected optimization problems (layers). The higher layer is realized as a mixed integer linear optimization problem implemented within the rolling horizon strategy with reactive scheduling and the objective function of maximizing the profit of the microgrid. The lower layer is realized as a nonlinear optimization problem in a cosimulation environment that integrates the electrical limitations of the power grid, and has the technical objective of minimizing deviations from the planned values of the higher layer (minimisation of corrective measures) in near real time. The energy management system has implemented an advanced model of battery energy storage system consisting of combining the load-dependent efficiency of a bidirectional power converter unit, battery energy charging model, modeling cycle and calendar aging of the battery and valorization of stored energy in the battery. The input data to the optimization problems are predicted using different methods, depending on the layer of the energy management system and the size that is predicted. The methods used include numerical weather prediction models and artificial neural networks with long short-term memory. An advanced double-layer adaptive energy management system was applied to the shortterm operation planning of the test microgrid, based on which general conclusions were made that the accuracy of forecasts that serve as input data greatly affects the optimality of microgrid operation. The installed power of microgrid sources of electricity greatly contributes to the degree of self-sufficiency of the microgrid and the reduction of operating costs. The level of complexity (reality) of the battery energy storage system model enables the microgrid operator to manage different operation strategies as a compromise between reducing operating costs and extending equipment life.