All coals contain mineral matter in their ash. Slag deposits form when molten or sticky particles of flyash are quenched upon contact with furnace walls or other radiant surfaces. The deposits reduce heat transfer to the walls and increase the amount of heat in the boiler's convective pass. The resulting rise in furnace exit gas temperature (FEGT) increases the temperatures of main and reheat steam, desuperheating spray flows, and NOx emissions. For best boiler performance it is important to maintain an optimal balance between furnace and convective pass heat transfer.
Sootblowing with high-pressure steam or air is the method of choice for keeping boiler heat-transfer sections free of slag. Wall blowers and water cannons are used to remove slag from the furnace's water walls, while retractable blowers are used to clean the boiler's convective pass, including the air preheater. Furnace sootblowing restores heat transfer in that area, reducing FEGT, steam temperatures, desuperheating sprays, and NOx emissions. Convective pass cleaning increases steam temperatures and desuperheating sprays and reduces boiler exit gas temperature.
The challenge in sootblowing optimization is to determine which sections of the boiler to clean and how often. Economic tradeoffs among NOx output, the opacity of stack emissions, steam temperatures, efficiency, boiler tube life, sootblower steam consumption, and O&M costs must be considered.
Getting sootblowing frequency and location just right can yield substantial economic benefits. For a typical 600-MW unit, optimal sootblowing can lower heat rate by 20 Btu/kWh and NOx emissions by 0.020 lb/mmBtu. Assuming a fuel cost of $1.50/mmBtu, NOx credits priced at $2,000/ton, and a five-month ozone season, those two reductions alone can lower a boiler's annual operating costs by approximately $500,000. Accounting for avoided power generation losses increases financial benefits by a factor of ten or more.
Knowledge is power
Lehigh University's Energy Research Center (ERC) has developed a unique, knowledge-based expert system (KBES) for sootblowing optimization based on the premise that knowledge is stronger than data. The KBES is implemented as a computer code called IntelliClean. At the heart of the program is a robust database that characterizes the effects of sootblowing using parameters such as the cleanliness of heat-transfer surfaces, steam temperatures, attemperation spray flow, emissions level, and stack opacity.
Powered by KBES, IntelliClean uses live process data (process events) to make real-time, on-line decisions about optimal sootblower activation. The optimal sootblowing activation strategy is event-driven and selects sootblower groups to be activated when and where needed to satisfy the sootblowing optimization goal and imposed operating and environmental constraints.
The characterization data are obtained by activating sootblowers or groups of sootblowers one at a time and recording and analyzing the effects. This data, and boiler operating data, then are integrated in a knowledge base that is used by KBES and IntelliClean to develop an optimal sootblower activation strategy. Significantly, the strategy is site-specific because the data in the knowledge base are empirical, representing the results of using sootblowers installed at particular locations on a particular boiler with a unique internal configuration.
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