| Article ID: | iaor2017528 |
| Volume: | 46 |
| Issue: | 6 |
| Start Page Number: | 503 |
| End Page Number: | 521 |
| Publication Date: | Dec 2016 |
| Journal: | Interfaces |
| Authors: | Zeng Bo, Danandeh Anna, Caldwell Brent, Buckley Brian |
| Keywords: | supply & supply chains, decision, geography & environment, combinatorial optimization, simulation |
Tampa Electric Company (TECO), which serves 687,000 customers in Florida, generates 60 percent of its electricity using coal‐fired generators. To meet environmental regulations on the emission of coal combustion, it must carefully mix several fuels of different qualities to make safe, environmentally friendly, and affordable blends that are generator specific. We worked with the management and engineering teams at TECO to develop a decision support platform, which centers around a mixed‐integer programming (MIP) model to comprehensively capture system specifications, requirements, and operations in all key aspects of TECO’s fuel supply chain. This platform enables TECO to make optimal procurement, transportation, blending, and burn decisions and satisfy all environmental regulations. We estimate that the implementation of this model can provide TECO with annual fuel‐cost savings of 2–3 percent, which translate to millions of dollars of savings in total fuel costs.