Integrated whole-boiler process models are useful in the design of biomass and coal-fired boilers, and they can also be used to analyse different scenarios such as low load operation and alternate fuel firing. Whereas CFD models are typically applied to analyse the detail heat transfer phenomena in furnaces, analysis of the integrated whole-boiler performance requires one-dimensional thermofluid network models. These incorporate zero-dimensional furnace models combined with the solution of the fundamental mass, energy, and momentum balance equations for the different heat exchangers and fluid streams. This approach is not new, and there is a large amount of information available in textbooks and technical papers. However, the information is fragmented and incomplete and therefore difficult to follow and apply. The aim of this review paper is therefore to: (i) provide a review of recent literature to show how the different approaches to boiler modelling have been applied; (ii) to provide a review and clear description of the thermofluid network modelling methodology, including the simplifying assumptions and its implications; and (iii) to demonstrate the methodology by applying it to two case study boilers with different geometries, firing systems and fuels at various loads, and comparing the results to site measurements, which highlight important aspects of the methodology. The model results compare well with values obtained from site measurements and detail CFD models for full load and part load operation. The results show the importance of utilising the high particle load model for the effective emissivity and absorptivity of the flue gas and particle suspension rather than the standard model, especially in the case of a high ash fuel. It also shows that the projected method provides better results than the direct method for the furnace water wall heat transfer.

To enable the inclusion of intermittent renewable energy sources on existing power grids requires base-load coal-fired power plants to operate flexibly, including fast load changes and continuous low-load operation. Low-load operation of a 620 MWe subcritical boiler is analyzed with the aid of a cosimulation methodology that incorporates a detailed 3D computational fluid dynamics (CFD) model together with a one-dimensional process model. A discretized one-dimensional model of the water/steam circuit was developed for the furnace, the radiant superheaters, and the convective/back pass heat exchangers. This is coupled with a detailed CFD model incorporating the furnace and radiant superheaters using an Eulerian–Eulerian reference frame. The coupled model is used to investigate the combustion stability, water/steam side effects, and the radiant heat-exchanger operational limits for six different burner firing arrangements at a low boiler load of 32% of maximum continuous rating. The results show that certain firing arrangements can lead to a high risk of fire-side corrosion and overheating of heat-exchanger components. Based on the analyses of combustion stability, boiler efficiency, and the safe operation of heat-exchanger components, a mixed firing arrangement with a higher secondary air mass flowrate for nonfiring burners was selected as the best operational strategy at this low load for the boiler under investigation.

An integrated data-driven surrogate model and one-dimensional (1-D) process model of a 620 [ MWe] utility scale boiler is presented. A robust and computationally inexpensive computational fluid dynamic (CFD) model of the utility boiler was utilized to generate the solution dataset for surrogate model training and testing. Both a standard multi-layer perceptron (MLP) and mixture density network (MDN) machine learning architectures are compared for use as a surrogate model to predict the furnace heat loads and the flue gas inlet conditions to the convective pass. A hyperparameter search was performed to find the best MLP and MDN architecture. The MDN was selected for surrogate model integration since it showed comparable accuracy and provides the ability to predict the associated uncertainties. Validation of the integrated model against plant data was performed for a wide range of loads, and critical results were predicted within 5–8% of the measured results. The validated model was subsequently used to investigate the effects of using a poor-quality fuel for the 100% maximum continuous rating load case. The uncertainties predicted by the surrogate model were propagated through the integrated model using the Monte Carlo technique, adding valuable insight into the operational limits of the power plant and the uncertainties associated with it.

The use of a thermal non-equilibrium Eulerian-Eulerian model for the simulation of a 620 MWe power boiler is proposed for capturing the combustion and radiative heat transfer found in the pulverized fuel systems. The models eliminates the use of a Lagrangian reference frame in tracking solid fuel particles thereby reducing the computational expense and time. The model solves the scalar transport for the particle mass, energy and radiation interactions between the pseudo-particle and continuous phases. The goal is to apply the modelling approach to generate a simulation database for different load cases and firing conditions which in turn will be used to study flexible operation. The model is validated against both numerical and applicable site data measurements. It is shown that the model is able to adequately resolve the furnace and superheater wall heat fluxes. Additionally the resolution of the flow field, combustion dynamics and wall fluxes are demonstrated for both an 80% and 60% operational loads. Moreover, it is shown that the Eulerian-Eulerian model results in approximately a 30% computational resource reduction when compared to traditional modelling approaches.