Optimization of Microgrid Performance and Emission Reduction Through Incentive Based and TOU Demand Response Models

The global reliance on fossil fuels for power generation contributes significantly to greenhouse gas emissions and environmental degradation, driving the need for cleaner, more sustainable energy solutions. This paper proposes a microgrid system that integrates distributed energy resources, diesel generators, and demand-side resources, focusing on two demand response (DR) models: incentive-based (IBDR) and time-of-use (TOU). The IBDR model incentivizes consumers to shift usage away from peak times, enhancing grid stability and reducing diesel reliance, while the TOU model shifts demand to off-peak periods, minimizing operational cost and reducing emissions. A multi-objective optimization approach assesses the models, revealing that IBDR effectively manages loads, while TOU is more cost-efficient in emissions reduction. Overall, the combined strategies improve grid sustainability, reduce costs, and lower emissions, demonstrating the microgrid’s viability for integrating renewable energy. Simulation results validate the models’ effectiveness in enhancing microgrid sustainability and operational performance.