Yanqing Niu

Study on fusion characteristics of biomass ash.

The ash fusion characteristics (AFC) of Capsicum stalks ashes, cotton stalks ashes and wheat stalks ashes that all prepared by ashing at 400 degrees C, 600 degrees C and 815 degrees C are consistent after 860 degrees C, 990 degrees C and 840 degrees C, respectively in the ash fusion temperature test and TG. Initial deformation temperature (IDT) increases with decreased K(2)O and went up with increased MgO, CaO, Fe(2)O(3) and Al(2)O(3). Softening temperature (ST), hemispherical temperature (HT) and fluid temperature (FT) do not affected by the concentrations of each element and the ashing temperature obviously. Therefore, the IDT may be as an evaluation index of biomass AFC rather than the ST used as an evaluation index of coal AFC. XRD shows that no matter what the ashing temperature is, the biomass ashes contain same high-temperature molten material. Therefore, evaluation of the biomass AFC should not be simply on the proportion of elements except IDT, but the high-temperature molten material in biomass ash.

Further study on biomass ash characteristics at elevated ashing temperatures: the evolution of K, Cl, S and the ash fusion characteristics.

Based on the ash-related problems during biomass combustion, the evolution of element S, Cl, K and chemical components and ash fusion characteristics of capsicum stalks, cotton stalks and wheat stalks ashed at 1000, 1200 and 1400 °C are further studied by XRF and XRD. Cl disappears at 815 °C in the form of HCl due to the aluminosilicate of sylvite. Above 1000 °C, inorganic S is released in the form of SO2 by the silicate of K2SO4, which is the main reason that ashing ratio decreases at high temperature. Except of the evaporation of KCl and K2SO4 aerosol which cause the release of K, Cl and S, K may be also reduced by the organic decomposition and the releases of metal K and KOH. The ash fusion characteristics of biomass are mainly dependent on the high-temperature molten material built up by quartz, potassium iron oxide and silicates.

The Effect of Particle Size and Heating Rate on Pyrolysis of Waste Capsicum Stalks Biomass

With pyrolysis as an attractive way to reduce CO2 and degrade residues, the effect of particle size and heating rate on pyrolysis of capsicum stalks has been investigated by thermogravimetry-differential gravimetric analysis and kinetic studies. Results show that pyrolysis reaction rate increases with increasing particle size. It is supposed that the contents of hemicelluloses, cellulose, lignin, and ash of various particle sizes have significant influence on the pyrolysis of biomass. Meanwhile, high heating rate does not mean high reaction rate, there is a complex competition effect between thermal hysteresis effects and the driving force originated from different heating rates.

Short Review on the Origin and Countermeasure of Biomass Slagging in Grate Furnace

Given the increasing demand for energy consumption, biomass has been more and more important as a new type of clean renewable energy source. Biomass direct firing is the most mature and promising utilization method to date, while it allows a timely solution to slagging problems. Alkali metal elements in the biomass fuel and the ash fusion behavior, as the two major origins contributing to slagging during biomass combustion, are analyzed in this paper. The slag presents various layered structures affected by the different compositions of ash particles. Besides, the high-temperature molten material which provides a supporting effect on the skeletal structure in biomass ash was proposed to evaluate the ash fusion characteristics. In addition, numerous solutions to biomass slagging, such as additives, fuel pretreatment and biomass co-firing, were also discussed.

Prediction of Calorific Value of Coal Using Real Power Plant Data

With the depletion of coal in the world, coal quality fluctuates and deviates greatly from the designed coal in many large scale coal-fired power plants. This increases the coal consumption while reduces the boiler combustion efficiency and stability. Thus, it is very important to conduct real-time measurement to the quality of the coal for optimizing the operation. The calorific value analysis is a significant part of the coal quality analysis, and regular proximate analysis method can’t meet real-time control requirements. In this chapter, an artificial neural network (ANN) model using real plant data for prediction of net calorific value of coal in a China power plant is reported. A three-layer BP neural network has been adopted. The input parameters selection was optimized with a compromise between smaller number of parameters and higher level of accuracy through sensitivity analysis. The activation function selection was also discussed in details. The results indicate that when the pureline was selected as the activation function for hidden layer and logsig was selected as the activation function for output layer, the prediction is most accurate. The results have shown good potential for predicting the net calorific value of coal using the real time data. This information will enhance the performance of the combustion control system for power utilities.

An Experimental Study on the Measurement of Moisture Content in Coal with Microwaves

In this article, a platform for measuring moisture content in coal is developed; measurement is carried out on a frequency within 6.6–9.9 GHz. As a result, the fitting curve of microwave attenuation and moisture content of coal are acquired. When the microwave wavelength is at least five times that of the particle size, which indicates λ/d ≥ 5, the measurement result will be more accurate. Further, there is a quadratic curvilinear correlation between the moisture content in coal and microwave attenuation.

A Improved Fuzzy Analytic Hierarchy Process Application in Prevention High Temperature Corrosion

The mechanism of formation of high temperature corrosion in large scale utility boilers is complex and involves numerous interrelated influencing factors. The fuzzy analytic hierarchy process (FAHP) has been employed in this chapter to make quantitative computations of the factors that influence the formation of the corrosion. When constructing the fuzzy judgment matrix, an affecting degree table of influencing factors was worked out first. Then the score of a pair-wise comparison was computed from a proposed expression r ij = x − y + 0.5. This improved method was applied to the analysis of the high temperature corrosion problem of a 215 MW coal-fired utility boiler, combining with in-site test data. The weights of the influencing factors were determined quantitatively and the main influencing factors were found out. Based on the calculated results, various adjustments to the combustion processes were made and, as a result, high temperature corrosion on the water wall tubes has been found largely reduced on the schedule shutdown of the boiler half year later. Moreover, a real-time high temperature corrosion detection technique can be developed based on the method reported in this chapter.