Efficient Management of Renewable Microgrids with Uncertainty Considerations

The present research investigates the best management practices for microgrids (MGs) that use a variety of distributed generation technologies, including storage devices, fuel cells, photovoltaics, microturbines, and wind turbines. Stochastic optimization based on scenario development is suggested to overcome the uncertainties in utility pricing, load consumption, and wind and solar power output. The issue becomes nonlinear due to the complexity introduced by the combination of storage systems and renewable energy sources. For optimization, a Harmony Search (HS) algorithm is used, which successfully strikes a balance between local and global searches. As a test scenario, a grid-connected MG is used to confirm how well the suggested method performs. The outcomes of the simulation demonstrate how well the stochastic framework incorporates uncertainty and improves the MG’s overall operating strategy. Furthermore, the HS algorithm has a robust search capability, yielding solutions that maximize the microgrid system’s energy distribution and storage management.