Sustainable Microgrids: TLBO Driven Multi Objective Optimization Modeling for Cost Effective Emission-Embedded Solution

This research integrates renewable energy resources into microgrid systems to address cost, emissions, and reliability concerns. Employing multi-objective optimization, the Teaching-Learning-Based Optimization (TLBO) algorithm emerges as highly effective, achieving substantial cost and greenhouse gas reductions. TLBO showcases rapid convergence and superior performance for the proposed microgrid architecture, offering valuable insights for sustainable energy planning. The proposed microgrid architecture includes micro-turbine (MT), a solar photovoltaic (PV) system, a wind turbine (WT), and a battery energy storage system (BESS). The numerical results of the proposed system compared with load supplied by main grid. The achieved cost savings of the proposed system is 66.85 % and GHG cost savings is 67.77% compared to load supplied by grid.