Design Modelling for Commercial/Pilot-Scale Circulating Fluidized Bed Combustion (CFBC) Boiler

Two biggest problems in present Indian pulverized coal combustion (PCC) power plants are that large capacity of PCC plants has reached retirement due to age limit and huge coal import from outside countries. Increasing the utilization of circulating fluidized bed combustion (CFBC)Circulating fluidized bed combustion (CFBC) technology in India is the best solution for renovating old PCC boilersBoiler to extend their life to 20–25 years and reducing coal import by increasing the utilization of local low-grade coals in effective manner. Even though CFBCCirculating fluidized bed combustion (CFBC) technology is economically sound, technically feasible and environmentally friendly than PCC technology, CFBCCirculating fluidized bed combustion (CFBC) technology utilization in India is still in the nascent stage. To increase the utilization of CFBCCirculating fluidized bed combustion (CFBC) technology in India, more designDesign models are needed to come out on Indian low-grade fuels such as Indian lignite and high ash coal for predicting thermal and environmental performance, analysing designDesign and optimizing processes in operation at wider range of operating parameters. In this paper, a CFBCCirculating fluidized bed combustion (CFBC) boilerBoiler designDesign modelling which is developed by programming code of visual basics for applications (VBA) software is explained. To check the accuracy, the design methodology is applied to validate the practical data of different CFBCCirculating fluidized bed combustion (CFBC) units on various aspects such as thermal performance model (boilerBoiler efficiencyEfficiency, flow rates), hydrodynamic model (solids volume fraction), heat transferHeat transfer model (water wall heat transferHeat transfer coefficient) and sulphur capture model (SO2 emissionsEmissions). The designDesign procedure which is applied for validation process gives satisfactory results on different aspects, and the qualitative agreement is found between predicted values and actual measurements.