Locating Hybrid Fuel Cell–Turbine Power Generation Units under Uncertainty

Abstract

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.

Moment calculations for piecewise-defined functions: an application to stochastic optimization with coherent risk measures

“…3 Tomazi (2004), Shah and Madhavan (2004) apply SP in the optimization of batch reactions to address the presence of uncertainty. 4 Chaton and Doucet (2003) utilize an SP model to support decision making in "new investments in generation and transmission capacity"; Schaefer and Schaefer (2004) present a model to minimize the costs of distributed hybrid generation while incorporating "uncertainty in customer demand, weather, and fuel costs" in the analysis.…”