Stochastic energy scheduling in microgrid with real-time and day-ahead markets in the presence of renewable energy resources

Renewable resources are a crucial component in power system research within contemporary intelligent power systems. It is imperative that they are given meticulous consideration. Microgrids (MGs) have emerged as a solution to facilitate the integration of renewable energy sources on a large scale. The incorporation of power production innovations that exhibit high levels of unpredictability in their generation would have a notable impact on the management of power resource planning within microgrids. Therefore, it is imperative to implement efficient power management mechanisms in microgrids. This study introduces a scheduling arrangement for a microgrid (MG) that includes a solar power unit (PV), which operates on a day-ahead basis. This paper explores the effects of various weather variables on the power generated by photovoltaic units and the optimum scheduling of microgrids. The present study employs the modified fluid search optimization algorithm to address the challenge of optimum management of energy in a microgrid connected to the grid that is characterized by a high level of unpredictability. The simulation results of the study indicate that the implementation of a photovoltaic model in an actual setting enhances the precision of the system for managing energy and reduces the overall operational costs of the interconnected microgrid. The algorithm under focus has been evaluated on a standard MG. The method under consideration has been executed on the MATLAB/Simulink computational environment and its efficacy has been evaluated.