Power generating stations are under continuous pressure to achieve maximum availability, highest efficiency, and minimum environmental emissions at the lowest possible cost. In recent years, increased fuel flexibility has become more critical financially and operationally than ever before. Colorado Springs Utilities (CSU) has been very progressive in adopting and implementing benchmark technologies and operating strategies to help achieve these goals across their diversified generation portfolio, and in particular at four operating coal units representing 462 megawatts in the system. One key strategy employed at CSU’s Martin Drake Station has been to continuously evaluate and test alternative coal feedstocks which have potential to reduce cost while maintaining capacity, fuel supply security, availability, and efficiency. These tests would not have been possible without the use of Fuel Tech’s Targeted In-Furnace Injection™ (TIFI®) technology to control slagging and fouling, reduce forced outages and load drops, and enhance unit efficiency. The TIFI process involves the use of two different forms of fluid dynamics modeling coupled with a virtual reality engine. Together, these simulation methods create a running duplicate of a given furnace with injection overlays and dosage maps to predict the precise trajectory of an injected chemical, helping to ensure as close to 100% coverage of the targeted zones as possible. With TIFI installed on Units 6 and 7 at Martin Drake Station, the operators were able to blend Powder River Basin coal with design fuel up to double the percentages previously achievable. Using TIFI, the plant was able to maintain full load generation, better control slagging deposits, show improvements in heat absorption, and reduce attemperator spray flows over previous blend trials. Including the cost of the TIFI program, the station has demonstrated a potential annual operating cost reduction approaching $4.9 million. Effective return on TIFI program investment is 4:1.
Enhancement of Power System Flexibility and Operating Cost Reduction Using a BESS
