Prediction of higher heating values of biomass from proximate and ultimate analyses

Two new empirical correlations based on proximate and ultimate analyses of biomass used for prediction of higher heating value (HHV) are presented in this paper. The correlations have been developed via stepwise linear regression method by using data of biomass samples (from the open literature) of varied origin and obtained from different geographical locations. The correlations have been validated via incorporation of additional biomass data. The correlation based on ultimate analysis (HHV = 0.2949C + 0.8250H) has a mean absolute error (MAE) lower than 5% and marginal mean bias error (MBE) at just 0.57% which indicate that it has good HHV predictive capability. The other correlation which is based on proximate analysis (HHV = 0.1905VM + 0.2521FC) is a useful companion correlation with low absolute MBE (0.67%). The HHV prediction accuracies of 12 other correlations introduced by other researchers are also compared in this study.     

On-line determination of the calorific value of solid fuels

In thermal processes with highly inhomogeneous fuels it is desirable to know real time fuel characteristics. In the case of municipal solid waste combustion (MSWC) it was up till now not possible to determine the calorific value of the waste on-line with a high accuracy. In this paper, a new method is presented where the calorific value is determined by means of an observer. A model based upon the mass balance is used together with concentration measurements in the flue gas to calculate on-line the calorific value of the waste. The background of this observer based sensor is discussed in detail, including a sensitivity analysis. Results from tests in different full-scale MSWC plants are presented as well as a comparison with other known off-line methods. It will be shown that the sensor works well and is more accurate than the present off-line methods. Furthermore, some applications of the calorific value sensor will be shortly discussed.     

An algorithm for determining the kinetics of devolatilisation of complex solid fuels from thermogravimetric experiments

An algorithm is introduced for determining the kinetics of devolatilisation of complex fuels, e.g. coal or biomass, when heated in an inert atmosphere. The algorithm uses information from thermogravimetric experiments, at several different, but constant, rates of heating, to identify and characterise the underlying distribution of reactions governing devolatilisation. The algorithm also provides an approximate way of inverting the distributed activation energy model (DAEM), commonly used to model the pyrolysis of coal. Such techniques provide the activation energy, E, and pre-exponential factor, A, for each parallel step participating in the thermal decomposition of a solid fuel. In addition, the amount of material associated with each pair of A and E can be derived.The method is tested on (i) imaginary data from simulated TGA experiments with one or more first-order reactions and (ii) real data from thermogravimetric experiments on the pyrolysis of sewage sludge. In every case the algorithm gave excellent predictions for heating rates other than those at which the pair of E and A were derived. Thus, the algorithm is a useful method of analysing and summarising measurements to provide kinetic data and facilitate predictions.     

A correlation for calculating elemental composition from proximate analysis of biomass materials

Elemental composition of biomass is an important property, which defines the energy content and determines the clean and efficient use of the biomass materials. However, the ultimate analysis requires very expensive equipments and highly trained analysts. The proximate analysis on the other hand only requires standard laboratory equipments and can be run by any competent scientist or engineer. This work introduces a general correlation, based on proximate analysis of biomass materials, to calculate elemental composition, derived using 200 data points and validated further for additional 50 data points. The entire spectrum of solid lignocellulosic materials have been considered in the derivation of the present correlation, which is given as: C = 0.637FC + 0.455VM, H = 0.052FC + 0.062VM, O = 0.304FC + 0.476VM, where FC – 4.7–38.4% fixed carbon, VM – 57.2–90.6% volatile matter, C – 36.2–53.1% carbon, H – 4.36–8.3% hydrogen and O – 31.37–49.5% oxygen in wt% on a dry basis. The average absolute error of these correlations are 3.21%, 4.79%, 3.4% and bias error of 0.21%, −0.15% and 0.49% with respect to measured values C, H and O, respectively. The major advantage of these correlations is their capability to compute elemental components of biomass materials from the simple proximate analysis and thereby provides a useful tool for the modeling of combustion, gasification and pyrolysis processes.     

What correlation is appropriate to evaluate biodiesels and vegetable oils higher heating value (HHV)?

The heating value is one of the most important properties of animal fats, vegetable oils and biodiesels for their use as fuels in stead of petroleum.There are lots of formulae or correlations encountered in the literature to evaluate biomass fuels’ higher heating value (HHV). Lots of them are not specially established for vegetable oils, animal fats and their derivatives. In this paper, some correlations previously published and based on ultimate analysis or fatty acid composition are applied to some bio oils samples collected from the literature. The aim of this article is to investigate what of them can be used to estimate animal fats, biodiesels, vegetable oils and their derivatives HHV with a high accuracy. With an absolute average error inferior to 4%, the results show that the formulae of : Channiwala and Parikh, Boie and Vondracek, Boie, Vondracek, Fassinou et al. Milne, IGT, Demirbas and Dulong can be used at this purpose with a high accuracy by comparison to the bomb calorimetric method.     

煤工业分析方法的改进

通过试验和数理统计分析,对应用MAC-G全自动工业分析仪与国标法测定煤的工业分析进行对比．结果表明,两种方法无显著差异,而且差值的置信区间也很小。MAC—G分析仪在180min内可分析19个样品的分析基水分、灰分和挥发分,不仅提升了测试效率,也减少了人为因素的影响,大大提高了分析结果的可靠性。     

Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks

Coal, a prime source of energy needs in-depth study of its various parameters, such as proximate analysis, ultimate analysis, and its biological constituents (macerals). These properties manage the rank and calorific value of various coal varieties. Determination of the macerals in coal requires sophisticated microscopic instrumentation and expertise, unlike the other two properties mentioned above. In the present paper, an attempt has been made to predict the concentration of macerals of Indian coals using artificial neural network (ANN) by incorporating the proximate and ultimate analysis of coal. To investigate the appropriateness of this approach, the predictions by ANN are also compared with conventional multi-variate regression analysis (MVRA). For the prediction of macerals concentration, data sets have been taken from different coalfields of India for training and testing of the network. Network is trained by 149 datasets with 700 epochs, and tested and validated by 18 datasets. It was found that coefficient of determination between measured and predicted macerals by ANN was quite higher as well as mean absolute percentage error was very marginal as compared to MVRA prediction.     

Ash fusibility and compositional data of solid recovered fuels

Several approaches are established to analyse the fouling and slagging propensities of coal ashes, but the same cannot be said of solid recovered fuel (SRF) ashes. This work has been conducted by using some fouling and slagging indicators, which are commonly applicable to coal ashes, on SRF ashes to ascertain their applicability.In this work, laboratory prepared ashes derived from municipal solid waste (MSW), sewage sludge, demolition wood, shredded rubber tyres, and plastic/paper fluff are analysed for their fusibility leading to fouling and slagging using three approaches; the ash fusibility temperatures (AFT), ternary phase diagrams, and fouling/slagging indices. The results from each approach are examined to determine the inclination of the ashes toward fouling and slagging. A subsequent inter-comparison of the methods was conducted to validate the methods which are in agreement and are applicable to SRF ashes. The study showed that ternary equilibrium phase diagram SiO₂-CaO-Al₂O₃, various fouling and slagging indices, and AFT can be used to complement each other to predict ash fusion properties, fouling and slagging propensities of SRF ashes.     

油页岩工业分析与元素分析各项指标间的相互关系

通过对松辽盆地北部油页岩进行铝甑分析,得出w(油)基本上都大于6%,具有较好的工业利用价值。油页岩的工业分析和元素分析实验结果表明,工业分析中灰分、挥发分、固定碳、发热量与元素分析中的w(碳)、w(氢)、w(氮)指标间存在一定的关系。这对油页岩开发利用和实验数据的验证具有重要的意义。     

The effect of air preheating on the combustion of solid fuels on a grate

Combustion of solid fuels on a grate is widely used. Mostly, the combustion behaviour is explained by the classical theory of Rogers. However, that theory cannot explain the combustion process when primary air preheating is applied. Solid fuel grate combustion is studied by experiments in a pot furnace. Experiments with and without primary air heating are described. These are compared with conclusions learnt from real plant experiments. It was found that the pot furnace experiments have a limited value in explaining the combustion behaviour of solid fuels on a grate. In order to be able to explain the results from practice an quantitative extension of Rogers' theory for the case with air preheating is presented.     

Proximate analysis based multiple regression models for higher heating value estimation of low rank coals

In this paper, multiple nonlinear regression models for estimation of higher heating value of coals are developed using proximate analysis data obtained generally from the low rank coal samples as-received basis. In this modeling study, three main model structures depended on the number of proximate analysis parameters, which are named the independent variables, such as moisture, ash, volatile matter and fixed carbon, are firstly categorized. Secondly, sub-model structures with different arrangements of the independent variables are considered. Each sub-model structure is analyzed with a number of model equations in order to find the best fitting model using multiple nonlinear regression method. Based on the results of nonlinear regression analysis, the best model for each sub-structure is determined. Among them, the models giving highest correlation for three main structures are selected. Although the selected all three models predicts HHV rather accurately, the model involving four independent variables provides the most accurate estimation of HHV. Additionally, when the chosen model with four independent variables and a literature model are tested with extra proximate analysis data, it is seen that that the developed model in this study can give more accurate prediction of HHV of coals. It can be concluded that the developed model is effective tool for HHV estimation of low rank coals.     

NO reduction capacity of four major solid fuels in reburning conditions - Experiments and modeling

The combustion of solid fuels in the rotary kiln and in the calciner of a cement plant generates fuel and thermal NO. This NO can be reduced inside the reducing zone of the calciner. This occurs in two different ways: homogeneous reduction by hydrocarbons and heterogeneous reduction by char. The purpose of this paper is to identify the relative contribution of volatile matters or char on the NO reduction process, which largely depends on the nature of the solid fuel used for reburning.Experiments were undertaken in an Entrained Flow Reactor (EFR), at three temperatures: 800, 900 and 1000 °C. Four major fuels used in the cement production process were studied: a lignite, a coal, an anthracite and a petcoke. Specific experiments were undertaken to determine (i) their devolatilisation kinetics and the gas species released. A wide range of species influencing the NO chemistry was carefully analyzed. Then, (ii) the char oxidation and (iii) the char NO reduction kinetics were characterized. Finally, (iv), the “global” NO reduction capability of each fuel was quantified through experiments during which all phenomena could occur together. This corresponds to the situation of an industrial reactor in reducing conditions. Anthracite and petcoke reduce only very small quantities of NO whereas lignite and coal reduce, respectively, 90% and 80% of the initially present 880 ppm of NO (at 1000 °C after 2 s).The four types of experiments described above were then modeled using a single particle thermo-chemical model that includes heterogeneous reactions and detailed chemistry in the gas phase. This model reveals that both NO reduction on char and NO reduction by volatiles mechanisms contribute significantly to the global NO reduction. After short residence times (several tenth of a second), gas phase reactions reduce NO efficiently; after long residence times (several seconds) the char reduces larger quantities of NO.     

Characterization of a lab-scale platinum filament pyrolyzer for studying the fast devolatilization of solid fuels

Platinum filament pyrolyzers achieve very high temperature and heating rate and can provide useful parameters for practical applications in combustion, pyrolysis and gasification processes. The critical use of an experimental instrument is necessary to provide reliable data. In this work, a commercial pyrolyzer (CDS Pyroprobe 2000) is characterized to obtain a correspondence between the nominal and the effective operating conditions. This is the basis for the modeling estimation of the effective thermal history of the sample during each experimental run. The experimental results obtained performing the devolatilization of coals, biomass and waste fuels using the pyrolyzer are compared with those obtained in a conventional thermogravimetric balance, to evaluate the effects of extremely different operating conditions. The amount of volatile released programming the most severe thermal conditions using the pyrolyzer (thus in conditions more similar to large-scale plants) differs significantly from that of thermogravimetric runs. Global kinetics are obtained fitting the experimental results and using the thermal history of the sample from the model results. They depend strongly on the conditions used for the devolatilization. Global kinetics obtained in the thermogravimetric balance runs (low heating rate) overestimate the rate of devolatilization in the pyrolyzer (high heating rate).     

Co-firing of coal and cattle feedlot biomass (FB) fuels. Part I. Feedlot biomass (cattle manure) fuel quality and characteristics

The use of cattle manure (referred to as feedlot biomass, FB) as a fuel source has the potential to solve both waste disposal problems and reduce fossil fuel based CO₂ emissions. Previous attempts to utilize animal waste as a sole fuel source have met with only limited success due to the higher ash, higher moisture, and inconsistent properties of FB. Thus, a co-firing technology is proposed where FB is ground, mixed with coal, and then fired in existing pulverized coal fired boiler burner facilities. A research program was undertaken in order to determine: (1) FB fuel characteristics, (2) combustion characteristics when fired along with coal in a small scale 30 kW_t (100,000 BTU/h) boiler burner facility, and (3) combustion and fouling characteristics when fired along with coal in a large pilot scale 150 kW_t (500,000 BTU/h DOE-NETL boiler burner facility). These results are reported in three parts. Part I will present a methodology of fuel collection, fuel characteristics of the FB, its relation to ration fed, and change in fuel characteristics due to composting. It was found that FB has approximately half the heating value of coal, twice the volatile matter of coal, four times the N content of coal on heat basis, and due to soil contamination during collection, the ash content is almost 9-10 times that of low ash (5%) coal. The addition of <5% crop residues had little apparent effect on heating value. The main value of composting for combustion fuel would be to improve physical properties and to provide homogeneity. The energy potential of FB diminished with composting time and storage; however, the DAF HHV is almost constant for ration, FB-raw, partially composted and finished composted. The fuel N per GJ is considerably high compared to coal, which may result in increased NO_x emissions. The N and S contents per GJ increase with composting of FB while the volatile ash oxide% decreases with composting. Based on heating values and alkaline oxides, partial composting seems preferable to a full composting cycle. Even though the percentage of alkaline oxides is reduced in the ash, the increased total ash percentage results in an increase of total alkaline oxides per unit mass of fuel. The adiabatic flame temperature for most of the biomass fuels can be empirically correlated with ash and moisture percentage.     

A thermochemical concept-based equation to estimate waste combustion enthalpy from elemental composition

Waste combustion is an interesting alternative for waste management and energy recovery. Knowledge of the waste higher heating value (HHV) is important for judging it’s worth as fuel. This work introduces a new equation, based on thermochemical concepts, to calculate HHV from elemental composition. This equation is expressed in terms of mass percentages on a dry basis of carbon (%C), hydrogen (%H), oxygen (%O), nitrogen (%N), and sulfur (%S); the HHV is computed in MJ/kg. The equation is as follows: HHV=(1−(%H₂O/100))(−0.3708(%C)−1.1124(%H)+0.1391(%O)−0.3178(%N)−0.1391(%S)). The thermochemical concept on which this expression is based involves a wide applicability. This equation neglects the inorganic carbon, hence it is not very adequate when there is a significant concentration of it. The predictions from this approach were contrasted against those proceeding from equations currently used in combustion technology, and also against bomb calorimeter data. The new equation is clearly competitive with respect to other formulations, and it can be very helpful for presenting a waste HHV value based on different derivation suppositions.     

On the high‐gasification rate of Brazilian manganese ore in chemical‐looping combustion (CLC) for solid fuels

The high rate of char gasification observed when using a Brazilian manganese ore as compared to ilmenite is investigated in a batch fluidized‐bed reactor. Experiments were carried out at 970°C using petroleum coke, coal and wood char as fuel with a 50% H₂O in N₂ as fluidizing gas. A manufactured manganese oxygen carrier was also used, however, which presented a slower char conversion rate than the manganese ore. It is concluded that decrease in H₂ inhibition and oxygen release are unlikely to be the main responsible mechanisms for the ore's unexpected gasification rate. The ore was also mixed in different ratios with ilmenite and it was observed that the presence of even small amounts of ore in the bed resulted in increased gasification rate. Thus, the high‐gasification rate for the manganese ore could be due to a contribution from the impurities in the ore by catalyzing the gasification reaction. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4346–4354, 2013     

Analysis of cyclic combustion of solid fuels

The cyclic nature of coal particles combustion results from the movement of loose material in the flow contour of the circulating fluidized bed (CFB): the combustion chamber, the cyclone, the downcomer.The experimental results proved that the cyclic change of the oxygen concentration around coal particles, led to the vital change of both mechanism and combustion kinetics. The mathematical model of the process of coal combustion has been scientifically described whose original concept is based on the allowance for cyclic changes of concentrations of oxygen around the char particle. It enables the prognosis for change of the surface and the centre temperatures and a mass loss of the char particles during the cyclic combustion. It allows to appoint mass-rate of combustion of a char particle in the above conditions.     

Prediction of higher heating values for saturated fatty acids from their physical properties

Higher heating values (HHVs) of fatty acids (C₄–C₁₈) were measured and correlated using linear least square regression analysis. Equations were developed for the estimation of the HHVs of saturated fatty acids from their molecular weight (Mw), density (DN) and carbon number (CN). These equations are HHV = 0.0518 Mw + 29.76, HHV = −93.4 DN + 122.67 and HHV = 0.7271 CN + 31.419 with R² values of 0.9895, 0.9798, and 0.9895, respectively. The correlations may be used for HHV estimation of mixtures of fatty acids developed from vegetable oils.     

Characterisation of large solid recovered fuel particles for direct co-firing in large PF power plants

Solid Recovered Fuels (SRF) are solid fuels prepared from high calorific fractions of non-hazardous waste materials intended to be co-fired in coal power plants and industrial furnaces (CEN/TC 343, Solid Recovered Fuels, 2003). They are composed of variety of materials of which some, although recyclable in theory, may have become in forms that made their recycling an unsound option. The SRF with an equivalent median diameter D₅₀ of 6.8 mm are to be directly co-fired in an existing pulverised coal power plant. In comparison to pulverised coal, the particle size distribution of the SRF is of several magnitudes higher, resulting in a different burnout behaviour. Size reduction of the SRF to a fraction similar to coal is not economically feasible. As such, the idea is to co-fire SRF without any further size reduction, and of course this proceeding bears the risk of incomplete combustion.Accordingly, the prediction of the burner levels at which the SRF should be injected and whether or not a complete combustion will be achieved under full and part load conditions are the primary objectives of this paper. In this work, laboratory experiments have been conducted to forecast the success of co-firing the SRF in a commercial pulverised coal power plant. It involves the analyses of the fuel and its intermediate chars, generated at conditions comparable to boiler conditions, to determine some characteristic parameters, namely the burnout time, the aerodynamic lift velocity (ALV), and the apparent densities. The information gathered from the lab experiments are correlated to boiler conditions to determine the possible distances they are likely to travel under various regimes, full load and part load, before they are completely consumed. Different scenarios are examined, and based on the results, the optimal boiler injection points are predicted.     

Supported silver adsorbents for selective removal of sulfur species from hydrocarbon fuels

Dispersed silver oxides on supports such as TiO₂, γ-Al₂O₃ and SiO₂ were observed to be effective desulfurizing agents for refined fuels at ambient conditions. TiO₂ was determined to be the most stable support for silver oxide. Ag (4 wt%)/TiO₂ demonstrated a saturation sulfur capacity of 6.3 mgS/g for JP5 fuel containing 1172 ppmw sulfur. This high affinity for sulfur translated to one sulfur heterocycle associated with every two surface Ag atoms in the sorbent even in the presence of a 160-fold excess of other aromatics found in the fuel. A unique attribute of these sorbents was that they were thermally regenerable at 450 °C using air as a stripping medium over multiple cycles. Desulfurization characteristics also varied with fuel composition. Variation in desulfurization performance between JP5, JP8 and a light fraction JP5 were established and associated with the differences in sulfur composition of these fuels. The effects of surface area, porosity and crystal structure of the sorbent on sulfur capacity are also presented.