Robust optimization of a battery-supercapacitor microgrid under load demand uncertainty

Rising energy demand and global threats from fossil fuels necessitate the adoption of renewable energy sources (RES) to harness free resources and reduce carbon emissions. The optimal size and power exchange of grid-connected RES and hybrid energy storage systems are investigated with the primary optimization objective for a city in Bangladesh. The total number of solar photovoltaic panels, wind turbines, supercapacitors, and lithium-ion batteries is considered a decision factor in the proper size of the hybrid renewable system. A probability density function combines the uncertainty with the previously gathered load demand. One of the primary constraints is accounting for load demand intermittency while optimizing the per-unit cost of energy. By utilizing an energy management system, the energy balance between the microgrid and the conventional grid is controlled under a supervised approach. A mathematically designed objective function is used to optimally design the hybrid system, with 3 objectives in mind: net present cost, levelized cost of energy (LCoE), and renewability. The LCoE is found to be $0.11∕kWh for the proposed system. The results show that although the per-unit cost of energy is lower in the conventional grid, the proposed microgrid model can fulfill the energy demand solely using renewable generation.