Optimize FBC Boiler Operation
There are many different types of optimization programs available that are based upon model predictive control, fuzzy logic, and neural networks. We suggest that you select a technology that meets the control strategy objectives of the plant, as discussed above. The selection should mesh with the existing control system and provide biases to setpoints in the control system. It should also be capable of running on a PC or on the control system controller. The best selection will use standard and/or existing process instrumentation in the plant, such as oxygen analyzers, flow and pressure transmitters, and online emission analyzers.
Figure 5 provides an overview of the basic controls used on a typical FBC boiler. The load is controlled by the steam demand in the form of a non-regenerative feedforward based upon steam flow, steam header pressure, and steam header pressure setpoint. These are incorporated in the boiler demand calculation that includes dynamic compensation, a requirement for AGC. While the boiler integrates the difference between the energy input and energy output of the boiler, the pressure error is primarily only a proportional process. The long FBC boiler time constant does not permit pressure control to operate as an integral control. The change in boiler demand is due primarily to the change in the feedforward. Other changes to boiler demand result from fuel quality changes.
|5. Basic FBC boiler controls. This is a typical control strategy for an FBC boiler with a gas recirculation fan. If a steam turbine is connected to the header, a more complex demand computation involving the steam turbine first-stage pressure and steam flows is employed. The biggest difference between this control system and that used in a conventional solid fuel–burning plant is the bed temperature and fuel feed control loops. In this design, the fuel demand signal goes to the fuel feeder control (11) and the airflow control (3), where excess air is used to trim airflow demand to the secondary air control (6) and the primary control (7). The ratio of secondary to primary air is set by the operator or the optimizer control (5). The induced draft fan controls furnace pressure according to a feedforward from the airflow demand (8). Bed temperature control is maintained by recirculating flue gas into the bed. The flue gas tends to slow combustion and reduce the bed temperature. Source: Metso Automation |
|6. Fuzzy logic the clear winner. The objective of advanced bed temperature control is stable bed temperature. In this FBC boiler test, the average bed temperature recorded during a one-week reference period (upper line) is compared with the performance of the same FBC during another one-week test period, but running with advanced bed temperature control algorithms (lower line). Source: Metso Automation |
The most unique control loop associated with a FBC boiler is the bed temperature. The bed is composed of many tons of hot sand and ash that is fluidized by primary air. The fluidization process is very important to the control of emissions and to minimizing limestone consumption in a coal-fired FBC. Furthermore, bed temperature is a function of fuel quality and changing boiler load because it is a function of the thermal balance of the bed. This is perfect for the application of a fuzzy logic controller, which is outside the scope of this article. Nevertheless, it can be said that these advanced control functions work extremely well in a biomass plant where the fuel constituents and moisture content are unpredictable (Figure 6).—Roger Leimbach (email@example.com) is director of sales and marketing for Metso Automation USA Inc.