Boiler Model Research Articles

Modeling of fuel combustion processes in a steam boiler when replacing standard burners

To date, most of Ukraine's thermal power equipment has exhausted its factory resource and is physically and morally obsolete. One of the ways to solve this problem is to modernize it with the introduction of modern fuel-using equipment. The decisive direction in this situation is the focus on domestic technologies, which differ from imported counterparts due to better adaptability to domestic equipment, as well as a more favorable price policy for domestic manufacturers. The presented work was carried out in order to check the feasibility of replacing standard burners with burners built on the basis of jet-niche technology in power boilers, for example, such as the GМ-50 (Е-50-3,9-440GМ) steam boiler. For this, a computer model of a steam boiler and regular burners was developed. The research was carried out using the ANSYS Student software package. The application of the numerical modeling method using the ANSYS Student software complex made it possible to perform a detailed analysis of the fuel combustion process in a steam boiler, evaluate its efficiency and study the impact on environmental indicators. The object of the research was the processes that take place during the combustion of gaseous fuel and their influence on the performance indicators of the GМ-50 power boiler. The subject of the study was a CFD fuel model of the GМ-50 boiler, whose regular burners are capable of working on both liquid and gaseous fuel. Methane was used as fuel. Both regular axial burners and burners built on the basis of jet-niche technology, which are more environmentally friendly, were used as burners. Verification of the CFD model, which took place using a known analytical technique, shows that the discrepancy between the values of analytical calculations and model calculations does not exceed 6.7 %. The average temperature of flue gases in the festoon window was selected as a comparison parameter. The temperature value of 1117 С was obtained analytically. Calculation using the CFD model developed in the ANSYS-CFX environment shows that the temperature value should be 1042 С. It was determined that regular burners are less environmentally friendly than, for example, modern jet-niche ones. So, for the coefficient of excess air  = 1.2, the average value of nitrogen oxides at the fuel outlet is 187 ppm. It makes sense to replace standard burners, for example, with jet-niche ones, which are most suitable for replacing standard ones.

Study on Oxygen-Enriched Combustion Characteristics of Blast Furnace Gas Boiler

ABSTRACT To study the dynamic characteristics of OEC (oxygen-enriched combustion) in a BFG (blast furnace gas) boiler, the BFG boiler of an iron and steel enterprise is taken as the research object, and a thermal test bed for OEC of BFG is set up, and a thermodynamic simulation model of the BFG boiler is constructed based on the heat loss of chemical incomplete combustion obtained from thermal test, using MSP (Multi-Subject Simulation Platform). The effects of OC (oxygen concentration) and the position of oxygen entering the furnace chamber on the key parameters of the OEC process of the BFG boiler under different working conditions were analyzed. The results showed that the excess air coefficient of 1.2 and exhaust temperature of 120°C was kept constant during the thermal test. With a fuel volume of 2.4 Nm3/h, for example, after the OC was increased from 21% to 40%, the combustion flame temperature in the furnace was increased by about 34°C, the heat loss due to unburned gas was reduced by 0.21%, and the boiler efficiency was increased by 1.38%. In the dynamic model, at the instant when the OC is changed, the disturbance of the whole system is relatively large, and the FAT (furnace average temperature) outlet, the pressure of the steam ladle, and the MST (main steam temperature) will have a step change, and then gradually level off again. With the increase of OC, the combustion reaction is more and more intense, the steam side of the heat transfer process is strengthened, the boiler efficiency is improved, and the FAT chamber outlet, the steam ladle pressure and the MST after OEC in different ways of oxygen entry into the furnace chamber will be longer and longer to reach a stable value. The results of the study can provide a reference for the OEC operation of BFG boilers.

Energy flow tracking of integrated energy system with electric thermal storage boiler

Abstract With the complexity and diversification of the integrated energy system, accurate optimization of resource allocation and scheduling has become the focus of research. This paper studies the energy flow tracking technology of the heat-electric integrated energy system with an electric thermal storage boiler. The modeling of the electric thermal storage boiler and the application of the energy flow tracking technology not only improves the flexibility and stability of the system but also realizes the comprehensive monitoring and analysis of the electric energy and heat energy flow in the system. Finally, the energy flow tracking technology is used to reveal the flow path and distribution of energy in the system through the example of the integrated energy system. It also shows the flexible energy and space-time transfer characteristics of the electric thermal storage boiler in the electrothermal integrated energy system.

Experimental and simulation study on coal-fired power generation coupling with fluidized bed biomass gasification

Positive-pressure fluidized bed technology utilizes the pressure generated by biomass gasification to facilitate further combustion within the furnace. This technique addresses the safety risks associated with external pressure in fluidizing medium and high-temperature situations and reduces equipment investment and operating expenses. However, research on the effects of the positive-pressure process in fluidized beds on gasification coupled with coal-fired power generation systems is scarce. To fill this research gap, extensive experimentation and Aspen Plus simulation were conducted to investigate the impact of equivalence ratio (ER), gasification pressure, and gasification temperature on the gasification performance. A 660 MW coal-fired boiler model was established to reveal the coupling effect on flue gas temperature and thermal efficiency by gasification from a positive-pressure fluidized bed on the boiler, and its accuracy was proved by comparing the actual boiler design parameters. The power generation cost of the positive-pressure gasification coupled coal-fired power generation system is calculated with the established model. The results indicate that an increase in gasification pressure from 4000Pa to 8000Pa resulted in no significant change in the operating indicators of the boiler, with the tail gas temperature near 132 °C and a boiler thermal efficiency of 92.68 %. Gas yield, carbon conversion rate, and gasification efficiency were positively correlated with gasification temperature and ER. However, the heat value of combustible gas increased with the gasification temperature and decreased with an increase in ER. With the rise of the biomass gas blending ratio, the power generation cost of the unit gradually decreases. Respectively, the positive -pressure would lower the power generation costs of a 660 MW coal-fired boiler by 5.76 × 105$/year. This study demonstrates that positive-pressure fluidized bed gasification may retain high gas yields and efficiency, significantly lowering equipment investment and operating expenses, as a very efficient energy-saving and carbon-reduction technique.

CONTROL OF BIOMASS BOILER WATER TEMPERATUR USING SLIDING MODE CONTROL SYSTEM

Medium scale biomass temperature control is aspecific field of control issues where one of the most important features is cost effectiveness. It means that anykind of control system improvement should be done withthe lowest possible additional costs. Generally, the basiccontrol of such kind of boiler regulates temperature ofoutlet heating water. This control can be also performed bya conventional or advanced control. Although the main problem of this study is the constructionof the model of biomass boiler for control purposes, our taskdeals with technology of boilers and principles of its innerprocesses as well. Creation of the model comes out not onlyfrom these important findings, but also from experimentaldata collected during measurements in real operation. Heatand mass balance calculations were made according to thesedata and they serve to precise dynamic properties ofexperimental unit for biomass combustion.Based on the derived mathematical model of the biomassboiler, here is possibility to enhance the control byadditional algorithms that are responsible for extendedoptimization functions. In this paper, an advanced processcontrol such as sliding mode control system (SMC) is usedto control the temperature of the boiler water. The resultsshow that SMC has strong immunity for the disturbanceand the varying of process parameters.

CFD MODELING OF THE GM-50 (E-50-3.9-440GM) BOILER FURNACE

The main purpose of the work is to analyze the feasibility of replacing standard burners with burners that operate using jet niche technology burners in power boilers, such as the GM-50 steam boiler (E-50-3.9-440GM). To achieve this goal, a computer model of the steam boiler and burners was built. The study was conducted using the ANSYS Student software suite. The application of numerical modeling methods using the ANSYS Student software suite allowed for a detailed analysis of the fuel combustion process in the steam boiler, evaluate its efficiency, and examine its impact on environmental indicators. The object of the study is the processes occurring during the combustion of gaseous fuel and their impact on the performance indicators of the GM-50 power boiler. The subject of the study is the CFD model of the fuel boiler GM-50, whose standard burners are capable of operating on both liquid and gaseous fuel. Methane was used as the fuel, and both standard axial burners and jet niche technology burners were used, which are more environmentally friendly. Verification of the CFD model, which was performed using a known analytical method, indicates that the discrepancy between the analytical calculations and the model calculations does not exceed 6.7 %. The average temperature of the flue gases in the “festoon window” was chosen as the comparison parameter. Analytically, the temperature value was obtained to be 1117 °C. The calculation using the CFD model, developed in ANSYS-CFX, indicates that the temperature value should be 1042 °C. It was determined that standard burners are less environmentally friendly than, for example, modern jet niche technology burners. For an air excess coefficient α = 1.2, the average value of nitrogen oxides at the outlet from the burner is 187 ppm. There is sense in replacing standard burners, for example, with jet niche technology burners, which are the most suitable for replacing standard ones. Bibl. 24, Fig. 6.

A flexible and deep peak shaving scheme for combined heat and power plant under full operating conditions

Improving the flexible and deep peak shaving capacity of combined heat and power (CHP) plant under full operating conditions to facilitate renewable energy consumption is the main choice of novel power system. Accordingly, a dry/wet state automatic conversion control scheme fuses the precise mechanism structure, reinforcement learning and multi-objective model predictive control (MPC) algorithms is designed to promote the deep peak shaving ability of CHP plant in this paper. Firstly, the detailed mechanism models of once-through boiler at dry and wet state are presented by analyzing the dynamic characteristics of steam-water flow. Secondly, the large-scale unknown parameters in mechanism models are identified via the Takagi-Sugeno fuzzy modeling, reinforcement learning algorithms and actual dry/wet state conversion data. Thanks to the proposed hybrid modeling strategy, the high-precision boiler-steam unit models at dry and wet state are rapid obtained. Then, to meet different peak shaving demands, the multi-objective MPC algorithm is respectively constructed under dry and wet state with the comprehensive consideration of operational constraints, load tracking error, algorithm stability, power generation cost, CO2 and NOx emission costs. Aiming at maximizing the peak shaving efficiency and flexible operation ability of plant, a dry/wet automatic control scheme combined the designed multi-objective MPC algorithms and identified dry/wet state models is proposed. Finally, the load variation rate of 5 % and 2 % RCM/min is respectively achieved in the dry/wet state conversion tests on a 350 MW CHP plant based on the proposed control scheme. Thus, the rapid and thorough dry/wet state conversion performance of once-through boiler has successfully improved the operational flexibility of CHP plant under full operating conditions.

Numerical Analysis of the Co-firing Combustion of Coal and Palm Shell Kernel In Stoker Boiler

The United Nations Framework Convention on Climate Change (UNFCCC) states that Indonesia is committed to contributing to global climate change solutions. The government will also continue to encourage the development of a number of renewable energy (EBT)-based power generation projects. This is based on the use of renewable energy which is still low, namely around (1.9%) 8215.5 MW. Meanwhile, the potential for EBT to become energy can be around 443,208 MW. One source of EBT in Indonesia that can be utilized is Biomass. Co-firing of biomass is a relatively cheaper option and does not require investment in new power plants. However, Co-firing combustion has several aspects that need to be studied, such as temperature combustion and the generation of gas emissions. Therefore, this study aims to determine the temperature and the emissions resulting from co-firing of palm kernel shell biomass. This research was conducted using the Computational Fluid Dynamics method on stoker boiler model. The test parameters of the research was the maximum and average temperatures in the furnace, and the average and maximum fractions of CO2, SO2 in the stoker boiler furnace. From the research conducted, it was found that the resulting combustion temperature decreased as the co-firing fraction of the biomass increased. However, CO2 gas emissions increased and SO2 decreased with increasing fraction of co-firing biomass which showed a decrease in harmful gas emissions and complete combustion that occurred in the furnace.

Modeling and control of boiler in thermal power plant using model reference adaptive control

The boiler is a multi-variable system, which is very difficult to control due to its nonlinear behavior, uncertainties, interactions between variables, and unmeasured and frequent disturbances. Instead of conventional control techniques, modern control techniques are being implemented in most boilers by industries. Mathematical modeling is a useful tool to analyze a complex system’s performance and design a controller for the same. The mathematical model is derived from the open-loop data obtained from the process station. The mathematical equation is then derived using the decoupling technique in terms of transfer function. An adaptive controller is designed and implemented for the model and the simulation study for the same is carried out using MATLAB. The proposed method discussed in the paper can adjust the controller parameters in response to changes in plant and disturbance in real-time by referring to the reference model that specifies the properties of the desired control system.

Numerical and physical modeling of the aerodynamic process in a direct-flow coil-type boiler using a laboratory stand

The article examines the modes of gas passage through the chimney of a direct-acting steam generator set using a laboratory stand made of a cylindrical coil. The criterion for determining the gas flow regime is a dimensionless quantity called the Reynolds number. The air flow velocities and temperatures were determined experimentally. Based on these results, the Reynolds number was calculated and the flow regimes at each measurement point were determined, and the dependence of the Reynolds number on temperature and velocity was obtained, and the experiment was analyzed. With the help of the ANSYS program, a model of air movement on the stand was built. When deciphering the geometric model, the ANSYS SpaceClaim program was used. The model made it possible to estimate the distribution of the air flow velocity in the boiler model based on experimental values. Further, after constructing a geometric model using the ANSYS Icem CFD program, a dispersion model was cre-ated that showed the temperature distribution of flue gases in the external gas flow of the basic model of a direct-flow steam boiler. The processing of experimental data showed a further prospect of intensification of the heat exchange process in a direct-flow steam boiler of the coil type.

Multiple-input multiple-output Radial Basis Function Neural Network modeling and model predictive control of a biomass boiler

This study presents a model predictive control of a 4 × 3 Multiple-Input Multiple-Output (MIMO) biomass control system that uses radial basis function (RBF) as an activation function to enhance the control performance. The biomass boiler model is developed from the system identification box in MATLAB by collecting measured input and output data from the 31.5 MW Wonji sugar mill and analyzing the data using black box modeling approach. The major goal of this study is to improve the MIMO control performance of a biomass boiler by utilizing Radial Basis Function Neural Network (RBFNN) to increase model accuracy which ultimately enhances the overall control system. Biomass boilers have four inputs and three outputs. The inputs are airflow 1, airflow 2, water flow and stocker speed (the speed of the motor which feeds bagasse or sugarcane pulp) and outputs are temperature, pressure and drum level. The RBFNN model was programmed using MATLAB R2021a software with system identification toolbox. Shorter settling times of 0.286 s, 1.873 s, and 0.637 s, as well as tolerable overshoots of 0.505%, 1.5%, and 15.698% for temperature, pressure, and level respectively, were achieved with the suggested model predictive controller using RBFNN model. However, when utilizing the identical controller and state space model, the settling times are 2.318 s, 5.461 s, and 6.147 s, with overshoots of 4.737%, 8.152%, and 38.194% for the three variables respectively. The suggested method was compared to the model predictive control (MPC) biomass boiler state space model, which can be considered as a model without RBFNN. The simulation results indicate that the RBFNN-based MPC performed better than the state space model-based MPC. This is because, the state space model is always constant, in contrast to the neural network's active monitoring of boiler dynamics.

Machine Learning Aided Numerical and Experimental Investigation of Hydrodynamic Performance in the Circulating Fluidized Bed Boiler

Abstract This study attempts to illustrate the benefits of integrating the concepts of machine learning algorithms with the field of thermo-fluidic applications. The current work is aimed at identifying effective or significant hydrodynamic input parameters, which are capable of deriving full benefit of fluidization that could yield a better circulating fluidized bed (CFB) furnace design using the Apriori algorithm. For this, historical datasets from the literature are collected and pretreated based on the design under observation. Association analysis performed by this Apriori algorithm measures the comparative strength of parameters under consideration. Also, this algorithm is capable of identifying the right combinations of parameters that can produce maximum fluidization performance. The end results suggested by this Apriori algorithm are validated using the computational fluid dynamics package. For this, the transient behavior of a scaled-down (1:20) reactor model of a real-time industrial CFB boiler is simulated using ansys fluent 18.0. In specific, the effects of fluidizing velocities, inventory heights of the bed, and particle sizes recommended by the Apriori algorithm are investigated. Here, the effects are assessed in terms of volume fraction distribution and axial velocity profile distribution profiles. From the results of simulations, it was clearly found that 2 m/s inlet velocity produced good circulating fluidized bed patterns on a bed inventory height of 0.5 m for a mean particle size of 200 µm. The results obtained from the simulations are once again validated visually against snapshots obtained during real-time laboratory fluidization experimental runs. Among all the cases of comparisons, the best agreement is demonstrated by Apriori algorithm compared to the numerical and the experimentally obtained results. Also, it is found that the manual time taken to identify the right combinations of parameters is drastically reduced by this method compared to conventional optimization algorithm and trial error methods.

Mathematical modeling of a 30 MW biomass-fired grate boiler: A reliable baseline model taking fuel-bed structure into account

Grate boilers are widely applied in biomass combustion for heat and energy generation. However, grate-firing systems often suffer from low efficiency and high emission. Computational fluid dynamic (CFD) becomes increasingly popular as a flexible method to obtain the detailed combustion behaviors in the furnace, and to optimize the performance of existing grate boilers. This paper presents efforts toward a reliable baseline CFD model for an industrial biomass-fired grate boiler, where the structure of the fuel-bed was sufficiently considered. The combustion performances in the furnace were investigated experimentally and numerically by coupling the fuel bed and freeboard, to clarify the impact of bed structure on the simulation accuracy. Results show that when the bed structure has been taken into account, the predictions are in better agreement with the various measurements, as the deviations between them are all within 10 %. Moreover, the flame center drops, the total heat transferred to the water-cooled walls increases, and the residence time of flue gas is greatly prolonged from 2.76 s to 3.90 s, resulting in a distinct difference of the temperature and species patterns in the freeboard. The simulations will provide valuable theoretical guidance for the accurate modeling of grate-fired boiler.

NOx formation model for utility boilers using robust two-step steady-state detection and multimodal residual convolutional auto-encoder

BackgroundTo achieve carbon neutrality, thermal power plants will take on greater peak-shaving responsibilities, resulting in utility boilers running at more frequently-changing states. This variation inevitably contributes to dirtier measurement data, and the data will follow new distributions that represent asynchronous operational characteristics. MethodTo predict the NOx formation concentration in this new context, a novel modelling framework is proposed. First, a two-step steady-state detection algorithm, including a basic and a precise identification procedure, is proposed to select steady-state samples from operational data. This algorithm also combines with a bayesian optimization–variational mode decomposition (BO–VMD) approach to enhance its robustness by eliminating high-frequency noise, and with an empirical cumulative distribution based outlier detection (ECOD) to remove outliers. Therefore, a high-quality steady-state dataset is acquired. Based on these data, a multimodal residual convolutional auto-encoder is developed to extract the latent variables that vary with the operation modes. These variables are then used to construct the multimodal NOx prediction model. Significant findingsThe findings on a 660 MW utility boiler reveal that, the proposed modelling framework has a lower misdiagnosis rate in steady-state identification compared to the one-step detection technique, and achieves higher fitting and generalization accuracy than the global modelling method.

A simplified mechanism of hydrogen addition to methane combustion for the pollutant emission characteristics of a gas-fired boiler

The reaction mechanism of hydrogen-enriched methane (HEM) combustion is significant in the combustion process. In this study, four widely used reaction mechanisms for methane combustion are simplified to investigate the pollutant emission characteristics of a gas-fired boiler used for HEM combustion. The laminar burn velocity (LBV) and ignition delay time (IDT) of the four detailed and four simplified mechanisms are compared, and the simplified San Diego mechanism is identified as the optimal mechanism using relative error and population standard deviation analysis. The temperatures and key components of the simplified San Diego mechanism are also compared with those of the detailed San Diego mechanism under various XH2. Based on the simplified San Diego mechanism, a chemical reactor network model for gas-fired boilers is further established to investigate the pollutant emissions of HEM combustion, in which the hydrogen doping ratio XH2 ranged from 0 to 80% and the inlet air and fuel temperature Tin ranged from 300 K to 600 K. Results showed that at Tin = 300 K with XH2 ranging from 0 to 80%, the mole fraction of NO increase by 1.94 times because of the increase in peak flame temperature; moreover, the mole fractions of N2O, CO, and CO2 decrease by approximately 25%, 50%, and 52%, respectively. With XH2 ranging from 0 to 40% and Tin ≥ 500 K, the mole fraction of NO decreases because the reduction reaction of NO + H = N + OH is promoted, whereas when XH2 is further increased to 80%, the increased H promotes the increase in NO again. CO emissions decreased as XH2 increased from 0 to 80%, whereas they increased by approximately 1.3 times as Tin increased from 300 K to 600 K because of the CO2 decomposition. N2O emissions decreased by more than 25% as XH2 increased from 0 to 80%. Additionally, CO2 emissions decrease by 52% with an increase in XH2 and by only 5% with an increase in Tin, indicating that XH2 has a larger impact on CO2 emissions. The proposed optimal HEM combustion mechanism is conducive to improving the efficiency of numerical calculations.

Mathematical model of a steam boiler as a control plant

Mathematical model of a steam boiler as a control plant

Dynamic performance analysis and control strategy optimization for supercritical coal-fired boiler: A dynamic simulation

The flexibility of the coal-fired boiler depends on the control system, which is designed according to its dynamic characteristics. In this paper, a detailed dynamic model of a supercritical coal-fired boiler is developed in Dymola, and the necessary control models are built. The model is validated against the design values under various conditions with a maximum error of 2.19%. The model is further validated by comparing dynamic simulation results with operating data. Then, the dynamic behavior of the boiler is analyzed under the single- and two-parameter disturbances. When the feedwater temperature, feedwater flow, and coal quantity are all disturbed by −5%, the maximum deviations of the live steam temperature are −21 °C, +32 °C, and −34 °C, respectively. Compared to the simultaneous change of feedwater and fuel, the maximum value of the live steam temperature is reduced by 21.56 °C when the coal quantity is changed 100 s before the feedwater flow. Besides, a first-order inertia compensation element is developed ahead of the feedwater flow command, which effectively improves the performance of the water-fuel ratio control. As the load-variation rate increases, the deviation in the transient process of the thermodynamic parameters increases, and the time required for stabilization lengthens.

Experimental study of gas-particle flow in the coal-fired industrial boiler applied radial air staging at variable over-fired air distributions

Radial air staging is an innovative method for reducing NOx emissions from coal-fired boilers compared to conventional axial air staging. However, an important issue in using this method is to set the over-fired air (OFA) distribution rationally to achieve good boiler performance. This paper aims to optimize the OFA distribution by evaluating important gas-particle (GP) parameters that influence the pulverized coal (PC) combustion performance. The GP flow experiment is conducted in a laboratory furnace model of a coal-fired boiler with different OFA distributions. The experimental results show that as RIO (Two-level OFA distribution ratio) changes from 0:1 to 1:0, the mixture of the OFA jet and airflow in the main combustion zone is advanced, which is conducive to PC burnout. Meanwhile, the size of the central recirculation zone decreases, resulting in poor PC ignition. It is worth noting that at RIO of 1:0, the central recirculation zone disappears at section y/d = 2.5, indicating that there is no high-temperature flue gas downstream to heat the fresh PC particles, which is extremely unfavorable for the stable combustion of the PC. In addition, at RIO of 0:1, compared to other cases, there are more particles in the central recirculation zone, which promotes the reduction reaction of N element released from PC particles, thus reducing NOx emission. According to the comprehensive evaluation, it is recommended that the RIO of the two-level OFA be set to 1:1 when using radial air staging in a coal-fired boiler. The results provide new insights into the application of the air staging method for efficient and clean PC utilization.

Dynamic model of a waste heat boiler

The paper discusses the experience of developing and identifying a model of a waste heat boiler as a distributed parameters plant. The waste heat boiler is considered as a heat exchanger with cross flows of interacting media. The first order hyperbolic equation acts as a mathematical model of water flow heating with a variable rate. Using the spectral method of distributed systems, a representation of the problem is obtained in the form of an expansion into a series in an orthonormalized basis, which makes it possible to represent the solution in the form of a vector-matrix model of the state space. The state-space representation is used to implement the model in a dynamic systems simulation package. The heater temperature calculation is based on the energy balance equation. The temperature of the media separator wall is determined by the heat fluxes between the exhaust gas, the wall, and the heated water. The wall temperature is assumed to be constant along the entire length of the heat exchanger. The paper presents a block diagram of the model, which takes into account the mutual influence of the wall temperatures and the heated water flow. The heat flux from the exhaust gas is calculated directly from the known parameters of the exhaust gas at the inlet and outlet of the waste heat boiler. Based on the design parameters of the heat exchanger, the dynamic characteristics of the heat transfer process are determined. The data obtained during the operation of the waste heat boiler are used to identify the heat transfer coefficient between the walls of the heat exchanger and the water flow. The result of the heat transfer coefficient identification agrees with the reference data. The article presents graphs of the original data, simulation results. It is shown that the maximum mismatch between the model and real data does not exceed two degrees, and the mean absolute error is less than 0.2 degrees.

Simplified finite volume-based dynamic modeling, experimental validation, and data-driven simulation of a fire-tube hot-water boiler

This paper proposes and implements a novel approach to simulate the dynamic behavior of hot-water fire-tube boilers, in which physical phenomena-based and data-driven modeling methodologies have both been employed. The first model, which includes a reduced one-dimensional finite volume method to simulate the flue-gas side’s behavior, can be employed for accurate sizing of the unit considering end-users’ dynamic consumption profile. In the data-driven model instead, machine learning algorithms are used to estimate hot water’s supply temperature, which makes it a suitable tool for real-time prediction and model predictive control. Utilizing the latter model in combination with an advanced management system allows reducing the plant’s energy consumption and enhancing its controllability. Employing the measurements performed in an Italian industrial firm, the developed model is validated and is demonstrated to have a limited thermal efficiency estimation bias of 1.2%. Furthermore, the data-driven model achieves a mean absolute relative difference error lower than 6%, demonstrating its acceptable accuracy for various prediction horizons.