Coal-fired Boilers Research Articles

Experimental study on NOx reduction performance by ammonia solution injection into the fuel-rich zone in a 75 t/h coal-fired industrial boiler

Industrial-scale trials of NOx reduction by ammonia solution injection into the fuel-rich zone were conducted in a 75 t/h corner-tangentially coal-fired boiler, and impacts of SOFA ratio, secondary air distribution modes, and ammonia solution injector configurations on the NOx reduction performance were discussed in detail. Results indicated that the waist air distribution mode and the increase in SOFA ratio could reduce the oxygen concentration in the reduction zone, which was conducive to the NOx reduction performance of injected ammonia solution. Ammonia solution injector configurations also had a remarkable influence on NOx reduction performance. Ammonia solution injected from injectors in the top layer and at four corners yielded lower NOx emissions than that in the bottom layer and on four walls, respectively. Meanwhile, more ammonia solution injectors in service were favorable for the reducing agent mixing with flue gas, thereby enhancing the NOx reduction performance. The lowest NOx emissions of 48 mg/m3 and a corresponding maximum NOx reduction efficiency of 86.09 % were achieved under the optimized conditions, i.e., 30 % SOFA ratio, the waist air distribution mode, and all 16 ammonia solution injectors in service. However, the boiler efficiency test indicated that the retrofit led to a reduction of 0.28 % in the boiler thermal efficiency simultaneously, necessitating further studies to mitigate the adverse effects.

Efficient online prediction and correction of 3D combustion temperature field in coal-fired boilers using GDNN

Predicting furnace temperature distribution is vital for coal-fired boiler safety. Existing methods, including finite element calculations and three-dimensional (3D) reconstruction still face limitations. A 3D combustion temperature field prediction method, GDNN, which utilizes offline-computed computational fluid dynamics (CFD) simulation results for online reconstructions of entire boiler, was proposed. GDNN method leverages the knowledge of the temperature field acquired by the base neural network model and Gaussian processes. Furthermore, a temperature field correction method is introduced, which employs intermediate variables of the GDNN model and measured values from temperature sensors to establish a correction model for the entire predicted temperature field. We compared GDNN's effectiveness with four well-established algorithms: Extreme Learning Machine (ELM), Least Absolute Shrinkage and Selection Operator (LASSO), Deep Neural Network(DNN), and Radial Basis Function (RBF) network, by also substituting these algorithms as the base model in our proposed method. The experimental results demonstrate that the proposed prediction method exhibits the highest performance, and the correction method effectively improves the overall results. The optimal parameters for predicting and correcting 3D furnace temperature field results were determined through experimental comparison, and the proposed method was applied to a 350 MW boiler, achieving an error of 2.41%, proving its real-world effectiveness.

Laboratory Study on Adhesive Ash Deposition Characteristics of Ammonium Bisulfate in Conditions Simulating an Air Preheater for Hard Coal Combustion

The ash blockage of the rotary air preheater is a serious problem of the coal-fired boiler that urgently needs to be solved, which is caused by the adhesive deposition of ammonium bisulfate (ABS) and the fly ash. A comprehensive experimental study was performed to investigate the adhesive ash deposition characteristics based on an experimental platform established. The influences of the gas temperature, the gas velocity, the mass ratio of the ABS to the fly ash (R), and the ash particle size on the ash deposition characteristics were mainly analyzed and discussed under different conditions. The experimental results indicate that the liquid ABS is the root cause of the ash particles adhering to the heat transfer elements of the air preheater. The experimental results indicate that when the gas temperature is in the range of 420–493 K, the ABS ash deposition intensity and the ABS adhesion rate both increase with the increase in the gas temperature. When it is 493 K, the ABS adhesion rates of the corrugated plate and the positioning plate both reach maximum values, which are 31.7% and 27.9%, respectively. With the decrease in gas velocity, the total ash deposition intensity, the ABS ash deposition intensity, the ABS adhesion rate, and the growth rate of the ABS adhesion all increase. The content of ABS in the fly ash is also an important factor. When R rises, the ash deposition intensity and the ABS adhesion rate increase significantly. The particle size of the fly ash has little influence on the total ash deposition intensity, but has a great influence on the ABS ash deposition intensity and the ABS adhesion rate. With the increase in the particle size in the range of 30.8–100 μm, the ABS ash deposition intensity decreases by nearly 50%, and the ABS adhesion rates of plates A and B decrease by about 43.9% and 49.6%, respectively. According to the study results, some effective measures can be taken to solve the ash blocking problem of the rotary air preheater, including using the steam air heater, optimizing the operation parameters of the soot blower, and inhibiting ABS formation.

Online Coal Identification Based on One-Dimensional Convolution and Its Industrial Applications

In order to improve the utilization rate of coal generation and reduce carbon emissions from coal-fired boilers, the operation parameters of power plant boilers should be matched with the actual burning coal. Due to the complex and high-risk blending process of multiple coal types, the actual application of coal types inconsistent with expectations may lead to low combustion efficiency of boilers, cause disturbances to the normal operation of thermal power units, increased energy waste and carbon emissions, and even lead to serious explosion accidents. Therefore, the online identification of coal types for thermal power units is of great significance. To obtain the precise type of coal online, in the present work, a data-driven coal identification method is proposed based on convolutional networks that do not necessitate additional hardware detection equipment and are easy to implement. Experimental results indicate that the proposed method exhibits superior performance in comparison to traditional methods, thus ultimately improving the performance of thermal power plant.

THERMOPHYSICAL AND ENVIRONMENTAL ASSESSMENT OF NATURAL GAS UTILIZATION IN THE RECONSTRUCTION OF A PULVERIZED COAL-FIRED BOILER

Link for citation: Maltsev K.I., Gil A.V., Abramov N.V., Puzyrev S.A. Thermophysical and environmental assessment of natural gas utilization in the reconstruction of a pulverized coal-fired boiler. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 30-38 In Rus. The relevance of the investigation is caused by the need to assess the completeness of fuel combustion, harmful emissions, and temperature stress of the screen surfaces of a pulverized coal-fired boiler during its reconstruction for natural gas combustion. Currently, the conversion of solid fuel combustion installations to natural gas is highly relevant due to significantly lower emissions of carbon compounds. The main aim of this research is to study the physicochemical processes in the combustion chamber at various loads with flammable natural gas combustion and evaluate the effectiveness of combustion organization during the reconstruction of a pulverized coal-fired boiler. Objects: combustion chamber of a boiler unit with a steam capacity of 210 t/h, burners, parameters of the combustion chamber environment Methods: comparison of results obtained from analytical thermal calculations and numerical modeling. The numerical simulation of gas flare combustion was performed using the ANSYS Fluent software package. Reynolds Averaged Navier–Stokes approaches based on averaging the Navier–Stokes equations over the Reynolds number with additional equations for the turbulent kinetic energy k and the rate of turbulent kinetic energy dissipation ε were applied to describe the turbulent flow. Results. A numerical study of the physicochemical processes in the combustion chamber of a boiler unit was conducted after its reconstruction for natural gas combustion. Dependencies of temperature level changes, hydrodynamics, and concentrations of combustion products components in the volume of the combustion chamber at various loads were obtained. It was found that high-temperature combustion products are redistributed towards the front and rear walls, resulting in the formation of zones in the wall layer with a significant temperature gradient. The nozzles of the tertiary air contribute to the reduction of nitrogen oxide emissions in the combustion chamber by suppressing their formation due to oxygen deficiency in the combustion zone, as well as by lowering the temperature of the flame in the oxidizing zone.

A new on-line combustion optimization approach for ultra-supercritical coal-fired boiler to improve boiler efficiency, reduce NOx emission and enhance operating safety

To take into account the economy, environment protection and operating safety of the boiler in the combustion optimization process, a new on-line combustion optimization approach for boiler is proposed. The historical combustion data collected from DCS of the coal-fired power plant is preprocessed at first. Then improved biogeography optimization-based long short-term memory neural network (IBBO-LSTM) and similarity measurement method are designed to construct the adaptive dynamic combustion model for boiler with boiler efficiency, NOx emission and the temperature of water wall as outputs respectively. After that improved non-dominated sorting genetic algorithm-Ⅱ (INSGA-Ⅱ) is designed to generate a series of boiler combustion optimization solutions under different running load offline, and improved multi-level fuzzy comprehensive evaluation (IDHGF) is designed to retain the combustion optimization solutions with higher running safety. Meanwhile, the retained optimization solutions are integrated into an optimization cases base. Thereafter, case-based reasoning based on safety enhancement mechanism (CBRSEM) is designed to achieve the online combustion optimization for boiler. Finally, to confirm the effectiveness of the combination of IBBO-LSTM, INSGA-Ⅱ, IDHGF and CBRSEM, different online optimization methods (IBBO-LSTM-INSGA-Ⅱ, IBBO-LSTM-INSGA-Ⅱ-IDHGF, IBBO-LSTM-NSGA-Ⅱ-DHGF-CBR, IBBO-LSTM-NSGA-Ⅱ-IDHGF-CBR, IBBO-LSTM-NSGA-Ⅱ-DHGF-CBRSEM, IBBO-LSTM-NSGA-Ⅱ-IDHGF-CBRSEM, IBBO-LSTM-INSGA-Ⅱ-DHGF-CBR, IBBO-LSTM-INSGA-Ⅱ-IDHGF-CBR) are adopted to optimize a given combustion case. The proposed on-line combustion optimization approach for boiler received satisfied combustion optimization results that the growing for boiler efficiency was 0.653%, and the reduced concentration for NOx emission reached 22.891 mg/m3, and the operating safety raised from 5.592 to 6.913. In conclusion, IBBO-LSTM-INSGA-Ⅱ-IDHGF-CBRSEM can online offer the combustion optimization strategy to the boiler operators to improve boiler efficiency, reduce NOx emission and enhance the running safety of boiler, so that it is suitable for online application.

Experimental Study on NOX Formation Characteristics in Flue Gas Recirculation Combustion Process of S-CO2 Coal-Fired Boiler

ABSTRACT Flue gas recirculation technology and air-staged combustion technology are both effective methods for reducing the production of NOX in coal-fired boilers. However, the synergistic effect of air-staged combustion technology and flue gas recirculation technology on NOX generation characteristics in S-CO2 boilers needs further study. The formation characteristics of NOX in the main combustion zone of coal combustion were studied experimentally when flue gas recirculation and air-staged combustion were combined. The results indicate that as the recirculation flue gas is injected at deeper levels, there is a gradual decrease in the concentration of NOX along the path, And the concentration of O2 also decreases gradually. The concentration of NOX decreases as the excess air coefficient decreases. The concentration of O2 increases as the excess air coefficient increases. Additionally, the NOX concentration at the furnace outlet increases with the increase of the excess air coefficient. Along the axial direction of the one-dimensional flame combustion furnace, the NOX production along the way and the NOX concentration at the outlet decrease with the increase of the flue gas recirculation position. Flue gas recirculation in air-staged combustion is an effective method for reducing NOX emissions. The positioning of flue gas recirculation significantly impacts NOX emissions. The NOx concentration is lowest when the flue gas recirculation rate is 27% and the mixing position of the recirculated flue gas is 300 mm with an excess air coefficient of 0.8.

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.

A method of designing an SNCR installation for small pulverized coal-fired boilers on the example of OP-50 boiler

Small pulverized coal-fired heating boilers are popular in heating and industrial applications. Recent changes in emissions limits forced interest in clean-up technologies dedicated for such a boilers, which previously were not included in regulations. The paper presents a method of designing an Selective Non Catalytic Reduction (SNCR) installation for small pulverized coal-fired boilers on the example of OP-50 boiler. Among main challenges during technology development and adjustment injection lances type, position, and operating parameters including reagent type and concentration can be enumerated. The designing process covered mainly following parts: object tests, temperature distribution determination (including balance calculations and computational fluid dynamics (CFD) modelling) leading to lances position determination, injection nozzles designing, installation tuning and calibration. Final measurements confirmed the ability of designed system to reduce NOx concentration in the flue gases below limit given in regulations.

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.

CO2 system integrated with ejector and mechanical subcooling: A comprehensive assessment

To achieve the goal of clean annual space heating and cooling for residential buildings, the concept of annual space heating and cooling transcritical CO2 system combined with ejector and mechanical subcooling is proposed. The problem of large throttling loss and performance degradation when CO2 system is applied for residential space heating and cooling can be solved. A theoretical model of the new proposed system is developed, and then optimized by the method of genetic algorithm. Moreover, taking an ordinary residential building located in 70 cities belonging to different climate zones as the application scenario, the seasonal, annual, environmental, and economic performance of eight heating and cooling solutions are compared and discussed. The results indicate that the COP and exergy efficiency of the new proposed system is significantly improved in contrast to conventional mechanical subcooling system, which increases by 11.48% and 21.64% in heating mode, and 8.99% and 8.69% in cooling mode, respectively. The annual performance coefficient of the new proposed system is 7.21%∼8.21% higher than conventional mechanical subcooling system. Additionally, the life cycle carbon emissions of the new proposed system can be significantly reduced by 12.23%∼89.58% compared with the combined solution of coal-fired boiler and R32. With the advancement of CO2 technology, it is possible to improve the economic performance of CO2 systems and the price of the new proposed system is lower than all solutions when the price of compressor is reduced by 60%. This study can provide a theoretical reference for the development and optimization of CO2 combined heating and cooling system, and provide a feasible solution for residential annual space heating and cooling.

Creating an Advanced Sensor Network to calculate real-time, mass-weighted flue gas composition and air heater leakage of a coal-fired utility boiler under dynamic operating conditions

Utilization of renewable energy sources to minimize the environmental impact of energy production has changed the way utility boilers operate, requiring frequent load cycling between full load and partial loads as low as 30%. Dynamic operation of coal-fired utility boilers significantly reduces boiler efficiency when compared to steady state at full load. Data-driven plant optimization has shown success with coal-fired utility boilers under dynamic operating conditions. The purpose of this work was to create an Advanced Sensor Network (ASN) to provide more extensive real-time data to inform dynamic plant optimization of Net Unit Heat Rate (NUHR). The ASN consists of gas sampling grids in the convective pass of the boiler and downstream of the air heater. These sampling grids allow for quantification of spatial variation of flue gas within the boiler and calculation of mass-weighted composition of flue gas through the combination of composition, velocity, and temperature measurements. The comparison of O2 between the inlet and outlet of the air heater is used to calculate air leakage in real time. Flue gas composition and air heater leakage are both important factors in boiler efficiency and NUHR.The results of this work support the value of mass-weighted averages for determining flue gas composition accurately. The measurements from the ASN show increased composition stratification during dynamic operation, with an average standard deviation 38% higher than observed during steady-state operation. Air heater leakage was also observed to increase from 2.8% to 5.1% following a load change. Prior to the installation of the ASN, these data would not have been available for dynamic control. These real-time data will be leveraged to calculate and optimize for NUHR during dynamic operation in future work.

Influence of over-fired air location on gas-particle flow characteristics within a coal-fired industrial boiler under radial air staging

To achieve low-NOx emission in the coal-fired industrial boiler, the radial air staging method is proposed. The location of the over-fired air (OFA) is an essential parameter as it affects the combustion stability, NOx generation, burnout, and slagging trend. These are related to the gas-particle flow such as the recirculation region, gas mixture, and gas-particle mixture. Therefore, in this paper, taking a coal-fired industrial boiler with radial air staging method as an object, in a cold-modeling furnace, the gas-particle flow characteristics under various OFA locations (LD of 1.29, 1.43, 1.72, and 2.00) are studied. When OFA is radially arranged, the OFA jet diffuses towards the furnace center. As the LD increases, the size of the central recirculation region increases, thereby improving combustion stability. When the LD is 2.00, the mixing of the OFA jet and PCC jet obviously is delayed. Moreover, an increase in LD leads to more returned particles in the furnace center, promoting the reduction reaction of NOx. In addition, as the LD increases from 1.29 to 1.72, the gas-particle mixing uniformity is enhanced, which is beneficial to the uniform temperature distribution. Comprehensively, the LD of 1.43–1.72 is recommended when radial air staging is adopted in coal-fired industrial boilers.

An LSTM-PSO-Based Predictive Strategy and Its Application in the Main Steam Temperature Control in Power Plants

We proposed an LSTM-PSO predictive controller strategy to overcome the large delay and strong disturbance during main steam temperature control. First, the long short-term memory (LSTM) network model was developed to forecast the future trend of mainstream temperature, and the deviation between the model output and the expected value after feedback correction was minimized by the particle swarm optimization (PSO) algorithm. Then, the LSTM-PSO predictive controller was taken as the primary controller to maintain the steam temperature of the coal-fired boiler. A comparative simulation with conventional PID cascade control and dynamic matrix controller strategies was given, and the test calculations indicate that the adjustment time was shortened and the overshoot was reduced. Finally, the LSTM – PSO predictive control strategy was deployed into the actual boiler operation process of a 300 MW coal-fired power plant, within 0.5 °C steady-state error and 2 °C dynamic error.

Revealing Inter-regional Environmental Inequities Hidden in China's Energy Transition.

Energy transition is an important way to control air pollution, but it may conflict with the economic goal of alleviating regional inequality due to its inherently different cost burdens. As one of the effective measures of energy transition, this paper takes small coal-fired boiler (SCB) upgrading as an example to explore the regional mismatch between upgrading costs and health benefits. Here, we construct a boiler-level inventory of SCB upgrades for the North China Plain (NCP) during 2013-2017 and propose an integrated modeling framework to quantify the spatial contribution of economic costs and health benefits associated with SCB upgrading. We find that although the total health benefits could offset the total costs for the entire region, the developed municipalities (Beijing and Tianjin) are likely to gain more health benefits from less-developed neighboring provinces at lower costs. These developed municipalities contribute only 14% to the total health benefits but gain 21% of the benefits within their territories, 56% of which come from neighboring provinces. Their benefits are approximately 5.6 times their costs, which is much higher than the 1.5 benefit-cost ratio in neighboring provinces. Our findings may be useful in shaping more equitable and sound environmental policies in China or other regions of the world with serious coal-related air pollution.

DClink: A data-driven based clinkering prediction framework with automatic feature selection capability in 500 MW coal-fired boilers

dClink: A data-driven based clinkering prediction framework with automatic feature selection capability in 500 MW coal-fired boilers

Emission Characteristics, Speciation, and Potential Environmental Risks of Heavy Metals from Coal-Fired Boilers: A Review

Coal-fired boilers, including coal-fired power plants (CFPPs) and coal-fired industrial boilers (CFIBs), are an important area for achieving sustainability globally as they are one of the globally important sources of anthropogenic emissions of heavy metals (HMs) due to huge amount of coal consumption. To date, the investigation of atmospheric emission characteristics, speciation, and potential environmental risks of HMs from coal-fired boilers has received widespread attention and achieved significant progress. To characterise the emissions of HMs from coal-fired boilers, research is currently being carried out in the areas of (1) studying the release of HMs from coal combustion processes, (2) developing emission factors and emission inventories, and (3) revealing the cross-media partitioning of HMs between different output streams. Research on the chemical forms of HMs in waste from coal-fired boiler is currently focused on chemical valence and speciation components. The sequential chemical extraction method is currently the most widely used method for investigating the chemical fractionations of HMs in wastes from coal-fired boilers. Studies indicate that different HM elements display differentiated characteristics of speciation in waste from coal-fired boilers. Early studies on potential environmental risk and ecological risk caused by HMs are usually based on actual monitoring values of HMs in the target environmental media. The risk assessment code method and the leaching toxicity method are the most widely used method to study the potential environmental risk of HMs in waste from coal-fired boilers. With the implementation of global carbon emission reduction strategies, the scale of coal-fired boilers and air pollution control technologies are bound to change in the future. Therefore, as an important component of global efforts to achieve sustainable development, more research is needed in the future to improve the accuracy of emission inventories, reveal the mechanisms of HM chemical transformation, and establish methods for potential environmental risk assessment at regional scales.

Rapid Classification and Quantification of Coal by Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Coal is expected to be an important energy resource for some developing countries in the coming decades; thus, the rapid classification and qualification of coal quality has an important impact on the improvement in industrial production and the reduction in pollution emissions. The traditional methods for the proximate analysis of coal are time consuming and labor intensive, whose results will lag in the combustion condition of coal-fired boilers. However, laser-induced breakdown spectroscopy (LIBS) assisted with machine learning can meet the requirements of rapid detection and multi-element analysis of coal quality. In this work, 100 coal samples from 11 origins were divided into training, test, and prediction sets, and some clustering models, classification models, and regression models were established for the performance analysis in different application scenarios. Among them, clustering models can cluster coal samples into several clusterings only by coal spectra; classification models can classify coal with labels into different categories; and the regression model can give quantitative prediction results for proximate analysis indicators. Cross-validation was used to evaluate the model performance, which helped to select the optimal parameters for each model. The results showed that K-means clustering could effectively divide coal samples into four clusters that were similar within the class but different between classes; naive Bayesian classification can distinguish coal samples into different origins according to the probability distribution function, and its prediction accuracy could reach 0.967; and partial least squares regression can reduce the influence of multivariate collinearity on prediction, whose root mean square error of prediction for ash, volatile matter, and fixed carbon are 1.012%, 0.878%, and 1.409%, respectively. In this work, the built model provided a reference for the selection of machine learning methods for LIBS when applied to classification and qualification.

Novel configuration of dual-temperature condensation and dual-temperature evaporation high-temperature heat pump system: Carbon footprint, energy consumption, and financial assessment

To achieve the goal of carbon neutrality for the application of industrial heating by recovery waste heat, the concept of dual-temperature condensation and dual-temperature evaporation is proposed for the high-temperature heat pump (HTHP) by introducing the techniques of ejector and two-stage compression. The energy, exergy, emission, and economic models are developed and optimized for the two new proposed systems. Then, the energy consumption, CO2 emissions and cost (LCC) during the whole life cycle are compared with five existing heat pumps and four traditional boilers. The highest coefficient of performance (COP) of heat pump (HP) can be got when intermediate water temperature on the heat sink side is optimum. The new proposed systems have better performances than the other five HTHPs. During the rated working condition, discharge temperature decreases by the use of dual-temperature condensation and dual-temperature evaporation HP with an ejector (Ej-DCDE). The optimal COP of Ej-DCDE-2 is 4.25, which is 11.55% and 1.43% higher than dual-temperature condensation and single-temperature evaporation HP and Ej-DCDE-1, respectively. The exergy destruction of Ej-DCDE-2 is reduced by 27.88% compared with basic heat pump (Base). Moreover, Ej-DCDE-2 has the lowest primary energy consumption of 14.62 ktoe, 22.19% and 25.09% lower than Base and oil-fired boiler during the total working period, respectively. In general, HTHPs have lower carbon dioxide, gaseous and particular pollutant emissions compared with boilers, especially Ej-DCDE-2. Finally, Ej-DCDE-2 has the minimum LCC, which is 14.67% and 11.75% less than Base and coal-fired boiler. Ej-DCDE-2 shows the most potential advantages of all the heating solutions and is recommended to replace traditional boilers for industrial heating.

Numerical research on ammonia-coal co-firing in a 1050 MW coal-fired utility boiler under ultra-low load: Effects of ammonia ratio and air staging condition

Co-firing ammonia (NH3) with coal for thermal power generation is a promising strategy for achieving global carbon neutrality. However, the drawbacks of NH3 combustion (e.g., narrow flammability limits, low theoretical flame temperature, high NOX emissions, etc.) can negatively impact the performance of coal-fired boilers, particularly for large-scale ones operating under ultra-low loads. As such, this study was conducted to investigate the ultra-low-load combustion characteristics of a 1050 MW coal-fired boiler when employing NH3-coal co-firing technology. Three-dimensional numerical simulations of ten combustion scenarios were performed to examine the effects of the NH3 co-firing ratio (ranging from 0% to 80%, by calorie) and air staging condition (Separated Over Fire Air (SOFA) ratio ranging from 4% to 24%) on temperature, gas species distributions, and emissions. Results show that as the NH3 co-firing ratio increases to 80%, the in-furnace average gas temperature decreases by 100 ∼ 200 K. The oxidation of NH3 takes precedence over the reduction of NO with NH3, leading to a surge in NO emissions· NH3 slip can be prevented at ultra-low loads due to the rapid consumption of NH3 near coal burners. Meanwhile, CO2 emissions reduce to 20% of that observed in pure coal firing. The increased H2O content in flue gas promotes coal burnout through the water–gas reaction, while the high H2O emissions may potentially cause low-temperature corrosion. At a SOFA ratio of 16%, a relatively large high-temperature region is achieved in the furnace, indicating more stable combustion under ultra-low loads. Excessively small or large SOFA ratios can reduce combustion intensity in the primary combustion zone while contributing to lower NO emissions.