Locating Hybrid Fuel Cell–Turbine Power Generation Units under Uncertainty

Abstract

Hybrid gas turbine–solid oxide fuel cell power generation has the potential to create a positive economic and environmental impact. Annually, the U.S. spends over $235 billion on electricity, and electric utilities emit 550 million metric tons of carbon. The integration of distributed hybrid generation can reduce these emissions and costs through increased efficiencies. In this paper, a model is presented that minimizes the costs of distributed hybrid generation while optimally locating the units within the existing electric infrastructure. The model utilizes data from hybrid generation modules, and includes uncertainty in customer demand, weather, and fuel costs.