A Numerical Investigation of the Effect of Dust Layer on Particle Migration in an Electrostatic Precipitator

Received: November 5, 2019
Revised: December 21, 2019
Accepted: December 21, 2019
Download Citation: RIS|BibTeX|https://doi.org/10.4209/aaqr.2019.11.0609  

Cite this article:

Gao, W., Wang, Y., Zhang, H., Guo, B., Zheng, C., Guo, J., Gao, X. and Yu, A. (2020). A Numerical Investigation of the Effect of Dust Layer on Particle Migration in an Electrostatic Precipitator. Aerosol Air Qual. Res. 20: 166-179. doi: 10.4209/aaqr.2019.11.0609.

HIGHLIGHTS

• The effect of the dust layer on performance of ESP was investigated.
• The thickness of the dust layer affected the electrical characteristics.
• The impact of the dust resistivity on particle trapping was studied.
• Some recommendations were presented to control dust thickness and resistivity.

Keywords: Dust layer; Electrostatic precipitator; Collection efficiency; Dust resistivity; Performance of decay

INTRODUCTION

An electrostatic precipitator (ESP) is the most commonly used device to remove dust particles from flue gas in many industrial areas, such as coal-fired power plants, steel mills, and construction material factories (Mizuno, 2002; Jaworek et al., 2018; Zheng et al., 2019b). An ESP is also one of the important methods to control PM_2.5 emissions from coal-fired power plants. The working principle of the electrostatic precipitator is to use a high-voltage electric field to ionize the flue gas, and the dust charge in the gas stream is separated from the gas flow by the electric field (Parker, 2012). On the one hand, the ESP structure, operating parameters, temperature, and humidity affect the performance of ESPs. Many researchers have conducted experiments and simulation studies in this regard (Nouri et al., 2012; Yawootti et al., 2015; Zheng et al., 2018c; Krupa et al., 2019; Zheng et al., 2019a). A high electric field strength and ion charge density leads to effective particle charging, and the charged particles provide high migration velocity and collection efficiency (Lin et al., 2012; Gao et al., 2019). Various numerical models of ESP with different electrode configurations have been developed to describe the electric field, gas flow, and particle transport (Bouazza et al., 2018; Dong et al., 2018; Wang et al., 2019). Other important parameters are the properties of dust particles, including particle size, chemical composition, and resistivity, which have been studied widely (Bhanarkar et al., 2008; Jedrusik and Swierczok, 2009; Sui et al., 2016). Some studies show that the particle size distribution of typical fly ash samples from different industries vary (Zheng et al., 2018b), and median diameter could be increased by chemical and electric agglomeration (Chang et al., 2017; Hu et al., 2018). Besides, the main chemical components of the particles are Si, Al, Fe, Ca, Mg, K, and Na. Traditional research results show that resistivity is a key factor in the efficient and stable operation of ESPs (Barranco et al., 2007; Aleksin et al., 2017). The dust particles cannot be effectively trapped by the dust collecting electrode under low resistivity, thereby causing re-entrainment (Ferge et al., 2004; Abdel-Salam et al., 2015). If resistivity is extremely high, then the migration velocity of particles decreases remarkably, and back corona easily occurs under high resistivity. These conditions cause a considerable drop in dust removal efficiency. Numerous investigations have proved that resistivity affects the collection efficiency (Krupa et al., 2008; Wang et al., 2018; Krupa et al., 2019). Therefore, some scholars have also conducted research on resistivity, including resistivity prediction model at different temperatures, SO₃, and humidity condition resistivity change (Barranco et al., 2007; Xu et al., 2014; Zheng et al., 2017). In addition, several studies on dust layer formation and structure were conducted (Minkang and Sijing, 2004; Zhu et al., 2008; Yan et al., 2012). Particle deposition forms could vary under different operating conditions, which are affected by discharge current distribution (Blanchard et al., 2002; Yang et al., 2013). Previous studies have established a meaningful foundation for the study of dust layers. However, most results are qualitative ranges. In the actual operation process, especially in the stable operation of power supply, a quantitative study on the effect of the dust layer has not been published and resistivity on the operating characteristics and performance of the precipitator have not been reported.

In this study, the numerical simulation method is used to study the influence of the thickness, resistivity, voltage, and current characteristics of the dust layer on the operating characteristics of the electrostatic precipitator and particle collection efficiency. The criterion of performance deterioration is obtained, and the dust layer characteristics are explored in relation to the particle collection. Meanwhile, the methods to reduce the influence of the dust layer on the ESP performance are proposed. The findings can be useful in optimizing the ESP performance with reasonable operating conditions.

SIMULATION MODEL

The numerical study was based on a simplified geometric model of a typical wire-plate ESP. The theoretical analysis includes corona discharge, particle charging, particle dynamics model, and gas flow model. As shown in Fig. 1, each sub-process is separately described by relevant governing equations, and these models interact with one another.

Fig. 1. Schematic of multi-process coupling model.

Corona Discharge

Corona discharge is one of the most essential processes in ESPs, and corona discharge results in a space charge being developed in the drift region, with the gas ions imparting their charge to the dust particles. Inside a wire-plate ESP, the governing equations that describe the corona discharge include Poisson’s equation and current continuity equation.

The Poisson’s equation is expressed as

where φ is the electric potential [V], ρ_i is the ion charge density [C m^–3], and ε₀ is the permittivity of free space [C² N^–1 m^–2].

The current continuity equation is expressed as

where

where J is the current density [A m^–2], b_i is the mobility of ions [m² (V·s)^–1], u is the gas phase velocity [m s^–1], and D_i is the ion diffusion coefficient [m² s^–1].

In addition, the corona onset field intensity and voltage on the discharge electrode can be determined by Peek’s law to calculate the ion space charge.

where  is the corona onset field intensity on the wire surface [V m^–1] and r₀ is the radius of the corona wire [m]; δ is the relative density of gas with respect to normal condition of 273.15 K; T_S and T are 273.15 K and local temperature, respectively; P_S and P are 101325 Pa and local pressure, respectively.

Particle Charging

The particle charge is an important factor in determining the migration of the particles because the charged particles are affected by the electric field force in the ESP. The magnitude of the force was dependent on the extent to which the individual particles were charged.

The charging model by Lawless (Lawless, 1996; Zheng et al., 2018a) represents a combination of two charging processes (field and diffusion charging) and provides the overall charging rate in the following dimensionless form:

where v is the dimensionless particle charge, w is the dimensionless electric field intensity, τ is the dimensionless charging time, q_p is the particle charge [C], k is the Boltzmann constant, e is the electronic charge, 1.6 × 10^–19 C, d_p is the particle diameter [m], and ε_r is the relative permittivity of the particle.

Gas Flow

The dusty airflow in the ESP can be considered as an incompressible and state turbulence, and the RNG k-ε model can be used to describe the steady-state turbulent flow. Continuity and momentum equations for the gas flow are shown as follows.

Conservation of mass:

Conservation of momentum:

where ρ_g is the mass density of the gas [kg m^–3], u is the gas velocity [m s^–1], and µ is the dynamic viscosity of the gas [kg m^–1 s^–1].

Particle Dynamics

In the gas-solid two-phase flow, the particles and fluid continuously exchange momentum. When the density of the fluid is much less than that of the particles, the buoyancy force, virtual mass force, and Saffman lift force are of a smaller order of magnitude than the particle inertia itself (Adamiak, 2013; Garrick and Bühlmann, 2018). Brownian force is usually considered for the study of submicron particles, and high temperatures enhance the Brownian motion of the particles (Sardari et al., 2018). High temperatures may also extend the range of particles that can be affected. Therefore, the particles are mainly subjected to aerodynamic drag and electric forces under the effect of the gas flow and electric field because the gravitational, buoyancy, virtual mass, Saffman lift, and Brownian forces have a small order of magnitude. The 2D model is adopted, and the equation of motion can be described as follows:

where m_p is the mass of the particle [kg], u_p is the particle velocity [m s^–1], F_d is the drag force [N], F_c is the Coulomb force [N], and C_D is the drag coefficient. In addition, when the particle size is close to the molecular mean free path, the Cunningham correction factor must be considered for the non-continuum effects in the calculation of the drag forces on submicron particles.

where C_c is the Cunningham correction factor, and λ is the molecule mean free path [m].

Dust Layer

Particles are deflected from the main gas stream to precipitate onto the collection plates, where they form the dust layer. In ESPs, the thickness of the dust layer can be predicted by inlet concentration and efficiency. The equation is as follows:

where ∆m_i is the increased mass of the dust layer in the ESPs [kg],  is the gas flow in ESP [m³ s^–1], ∆t is the time step [s], C_inlet is the particle mass concentration at the ESP inlet [kg m^–3], x represents the different particle size ranges, and η is the efficiency rate [%].

The average thickness of the dust layer can be calculated as follows:

where h is the average thickness of the dust layer [m], ρ_layer is the density of the dust layer [kg m^–3], l is the length of the collection electrode [m], and H_ESP is the height of the collection electrode [m].

The voltage of the dust layer can be calculated as follows:

where U_layer is the voltage of the dust layer [V], ρ is the resistivity of the dust layer [Ω·cm], and division by 100 is due to unit conversion.

The resistivity of the dust layer considering chemical composition and temperature can be directly measured by experiment or calculated as follows (Zheng et al., 2018b):

where N_K+Na+Li is the percentage of K, Na, and Li atoms; N_Fe is the percentage of Fe atoms [%]; N_Ca+Mg is the percentage of Ca and Mg atoms [%]; N_Al+Si is the percentage of Al and Si atoms [%]; and T denotes the temperature of the dust layer [K].

COMPUTATIONAL DETAILS

This numerical study was based on a single-channel wire-plate type ESP, which has been simplified as a 2D geometry model of two flat collecting plates and four circular corona wires, as shown in Fig. 2(a). The geometry was similar to the ESP we investigated in a previous work (Gao et al., 2019). The geometry of this computation model was defined as a 0.96 m long × 0.4 m wide rectangle with four electrodes placed in the channel, of which the diameter was 3.5 mm. The distance between the first wire and duct inlet was 120 mm. The dimensions were 0.2 m for the wire-to-plate distance and 0.24 for the wire-to-wire distance.

Fig. 2. (a) Geometry of modeled wire-plate ESP and (b) schematic of formation of dust layer.

The schematic of the dust layer formation is shown in Fig. 2(b). The negatively charged high-resistivity dust particles are continuously deposited on the dust-collecting plate by the electric field force. However, due to the high resistivity of the dust, the release of the charged electric charge is extremely slow, and the negative surface charge of the dust layer increases with the increasing deposition thickness and time, thereby affecting the dust collection efficiency. Thus, the present study was designed to determine the effect of the dust layer on the particle removal ability and improve the ESP performance with a dust layer.

The basic parameters of the applied voltage, gas, and particle are listed in Table 1. The gas temperature was always 423.15 K in this study. The particles were injected into the computational domain at the inlet of the ESP channel and had a mass density of 2100 kg m^–3. The particles had a uniform diameter that was simulated from 0.1 to 10 µm, and the inlet velocity was 1 m s^–1. Two important factors for dust, of which the dust layer thickness varied from 0 to 5 mm, and the dust layer thickness, changed from 10⁴ to 10¹² Ω·cm.

In the meshing process of the models, we used ANSYS meshing software to produce the mesh, which contained 180,847 nodes and 19,735 elements in this simulation domain. This computational domain was discretized into quadrilateral meshing, as shown in the structure in Fig. 3. The figure illustrates the accuracy of the grid according to the different locations; for example, the grid is dense near the discharge electrodes because the high-current density regions are generated around the four discharge wires.

Fig. 3. Mesh picture of 2D single-channel wire-plate ESP and refined mesh structure around discharge electrode wire.

In addition, some results of this study are calculated and simulated based on these formulas. Particle collection efficiency η was calculated with the following equation:

where C_inlet is the particle mass concentration at the ESP inlet [kg m^–3] and C_outlet is the corresponding particle mass concentration at the ESP outlet [kg m^–3]. x represents the different particle size ranges.

Deutsch efficiency equation can be used to calculate particle average migration velocity, and particle collection efficiency η can be converted to the following equation:

Particle average migration velocity w_p can be calculated as follows:

where A is the area of the collection plate in ESP [m²], and Q is the gas flow in ESP [m³ s^–1]. 

RESULTS AND DISCUSSION

In industrial applications, dust particles are collected in an ESP, and a dust layer is formed on the dust collecting plate. The study mainly simulates how the dust layer affects the particle collection in the wire-plate ESP. Furthermore, in our previous studies, this type of ESP was simulated under different conditions, such as electrode configurations, applied voltage, and particle size; the simulated results have been compared with experimental data and showed good agreement (Guo et al., 2014a, b; Yang et al., 2018; Zheng et al., 2018a; Wang et al., 2019).

In the following subsections, the electrical characteristics were compared under different applied voltages, dust layer thickness, and dust resistivity. The effect on the particle trajectory and charge were also considered. Eventually, the results of particle collection efficiency, relative efficiency, and migration velocity were obtained under different thickness and resistivity rates.

Effect of Dust Layer on Corona Discharge

The voltage-current characteristics under the different dust layer thicknesses were plotted with 10¹² Ω·cm dust resistivity in Fig. 4. From the three resulting curves, we found that the strongest V-I characteristic was produced without the dust layer, especially in regions with high applied voltage. The increased thickness of the dust layer would also produce a lower current density because the high resistivity dust accumulated over time, which resulted in sharp reduction of the current density along the collecting plate. In general, a good V-I characteristic led to improved ability in particle collection. Overall, with the increase of the applied voltage, the current density continuously increased at different thickness rates of the dust layer.

Fig. 4. Typical V_a–I_a characteristic-current density as function of applied voltage without dust layer and with two different thicknesses of the dust layer.

This simulation was conducted under the conditions of dust resistivity (10¹² Ω·cm) with different dust layer thicknesses at an applied voltage of 60 kV to further investigate the electrical characteristics in the wire-plate ESP. The distribution of the electric potential is shown in Fig. 5(a). The electric potential was much lower near the collecting plate than in other regions. However, when the thickness of the dust layer increased, the surface potential around the plate began to rise significantly due to the influence of the dust layer on the voltage drop. The ion charge density distributions under the different layer thicknesses of 0, 1, 3, and 5 mm were compared in Fig. 5(b). The ion charge density decreased sharply away from the discharge electrode. The ion charge density region also weakened gradually between the two adjacent wires due to corona suppression. The results showed that the ion charge density decreased dramatically around the corona wire with the increasing thickness of the dust layer as a result of the reduction of effective potential difference, and inhibition occurs. Thus, according to the results in Fig. 5, the thicker dust layer has an adverse effect on the electrical characteristics.

Fig. 5. Electric potential (V × 10³, a) and ion charge density (C m^–3 × 10^–6, b) distribution without dust layer and with 1, 3, and 5 mm dust layer.

To investigate the distribution of the electric field strength under different dust layer thickness (mm) with dust resistivity (10¹² Ω·cm), the simulation was finished with applied voltage of 60 kV for this model, as shown in Fig. 6(a). The distance between the imaginary red line and the center of the channel were 0.19 m in both conditions. The electric field strength near the dust-collecting plate decreased significantly with increasing dust layer thickness due to changed electric potential. However, according to the results, the electric field strength did not maintain a uniformly decreasing trend every time the thickness was increased by 1 mm. For example, the trend of the decrease in the electric field strength with the increasing dust layer thickness from 0 mm to 1 mm is stronger than the downward trend of 4 mm to 5 mm. This finding could mean that the electric field strength near the collecting plate would no longer have a clear downward trend when the dust layer is extremely thick. 

The distribution of electric field strength under various dust resistivity rates with 5 mm dust layer thickness was plotted in Fig. 6(b). The results show that the electric field strength was affected by different dust resistivity, which is the same as the thickness condition. The electric field strength also declines with rising dust resistivity, especially in high-resistivity conditions. In addition, the trends of decreased electric field strength could be divided into two regions. In the first stage (R_d < 10¹⁰ Ω·cm), the Es did not change apparently, and it dropped slightly only when dust resistivity reached 10¹⁰ Ω·cm. In the second stage (R_d > 10¹⁰ Ω·cm), the electric field strength near the plate decreased sharply until R_d increased to 10¹² Ω·cm.

Fig. 6. Distribution of electric field strength under (a) different dust layer thickness mm with dust resistivity 10¹² Ω·cm and (b) different dust resistivity Ω·cm with 5 mm dust layer thickness at applied voltage of 60 kV.

Overall, these results suggest an association between electrical characteristics, dust layer thickness, and dust resistivity. The electrical performance was affected by thickness and resistivity of the dust layer, but it was not linearly decreased as shown above. Interestingly, with the increasing thickness of the dust layer and dust resistivity, the place with field strength became the lowest and the lowest place became the highest. The peak value of the electric field strength decreased by 41.2%. In addition, the electric field strength distribution changed with the accumulation of the dust layer, and all the data used in the simulation are actual parameters within the acceptable range. Therefore, this work should be useful for the optimization of the dust layer under reasonable operational conditions, such as a good period of rapping process.

Effect of Dust Layer on Particle Removal

The single-particle charging and trajectory under different thickness of the dust layer and different dust resistivity at 10  particle size are shown in Figs. 7(a) and 7(b). The applied voltage kept a constant value of 60 kV throughout the entire investigation unless specified. Furthermore, the contour background in the figure represents the ion charge density distribution under different conditions of the dust layer. The single particle was released from y = 0.001 m to track the trajectory and calculate the particle space charge.

As shown in Figs. 7(a) and 7(b), the four contour background with the ionic charge density around the corona wire was seriously reduced with a thick layer and high dust resistance. Furthermore, the results show that the particle charging trend is not like the particle trajectory; apparently, the particle was quickly charged upon reaching the vicinity of the first discharge corona wire (x = 0.12 m). Subsequently, the charging speed of the particle becomes slow after passing the first corona wire. Most importantly, these results indicate that the particle capture ability was severely affected by increased dust layer thickness and high dust resistivity. After comparing the results shown in Figs. 7(a) and 7(b), we find that the simulated results are the same as the electrical characteristics discussed earlier, but the effects of the increased thickness and dust resistance on the trajectory and charge of the single particle were not the same. The current study found that when the resistivity of the dust is constant, the effect of thickness on the particle collection performance becomes small as the thickness increases. Moreover, when the thickness of the dust layer does not change and when the resistivity exceeds a certain characteristic value, a severely negative impact occurs on the particle removal ability. For example, the resistivity shows a completely different degree of influence on the particle trajectory and charging compared with the dust resistance, increasing from 10¹⁰ to 10¹¹ Ω·cm, 10⁸ to 10¹⁰ Ω·cm, and 10¹¹ to 10¹² Ω·cm. Further discussion of the effects of dust resistivity on the ESP capabilities under various conditions is provided in the subsequent section.

Fig. 7. Particle migration and charging under (a) different thicknesses of dust layer and (b) different dust resistivity at 10 µm particle size.

Fig. 8 shows the particle collection efficiency for various particle sizes with different dust layer conditions. The overall trends of collection efficiency without dust layer and with different dust layer conditions are shown as the U curves with particle size from 0.05 µm to 10 µm. The investigation of collection efficiency has shown that the overall efficiency is highest when no dust layer exists for all particle sizes involved in this study. Furthermore, the collection efficiencies decreased differently under various dust layer conditions. Compared with the no dust layer, the collection efficiency decreased from 89% to 62.4% with the 5 mm and 10¹² Ω·cm dust layer. For the same dust resistivity with the layer thickness increased from 3 mm to 5 mm, the dust collection efficiency was only slightly reduced. However, for the same dust layer thickness with increased resistivity from 10¹¹ to 10¹² Ω·cm, the efficiency was sharply reduced, which could mean that after the resistivity reached a certain value, any further increase may have a strong impact on the dust collection efficiency, which would be much greater than the effect of thickness. Furthermore, the compared particle trajectories with color scaled to the particle charge for the no-dust layer and 5 mm dust layer at 10 µm particle size are shown in Fig. 8. As expected, the particle trajectories are severely affected by the presence of the dust layer. Furthermore, the left side of Fig. 8 shows that the curve variations of efficiency changes with different particle sizes are not significant. However, the trajectory of the particles exhibited different movement behavior on the right side of Fig. 8 because the electric field, ion concentration, and particle charge decreased at different spatial positions with the increase of dust resistivity and thickness.

Fig. 8. Particle collection efficiencies (%, left) for different sized particles and particle trajectories with color scaled to particle charge (right, e) at 10 µm particle size without dust layer and with 5 mm dust layer.

Correlation between Properties of Dust and Collection Efficiency

Fig. 9 shows the typically calculated particle collection efficiencies and relative efficiencies at different particle sizes under 0, 1, 2, 3, 4, and 5 mm thickness of the dust layer. The collection efficiencies should be taken as illustrative. With increasing thickness of the dust layer, the collection efficiencies decreased under all particle sizes. In addition, similar to the aforementioned U-shaped curve, the lowest particle collection efficiency was generated at the particle diameter from 0.1 µm to 1 µm under every thickness condition, not in the smallest particle. On the other hand, the relative efficiency (red line) in the figure indicates that the effect of increased thickness on efficiency is not a linear decline. Moreover, the thickness of the dust layer has a greater adverse effect on the collection of particles smaller than 5 µm and larger than 0.1 µm.

Fig. 9. Typical collection efficiencies and relative efficiencies for particles with diameter 0.1, 1, 5, and 10 µm under different layer thickness (dust resistivity 10¹² Ω·cm, applied voltage 60 kV, and inlet velocity 1 m s^–1).

The particle collection and relative efficiencies with the increasing dust resistivity, which were simulated under different particle sizes and different applied voltages, are presented in Figs. 10(a) and 10(b). Overall, the particle collection efficiency decreases with the increase in dust resistivity for both cases. The reason is that the particles with high resistivity do not easily lose polarity once charged, thereby causing difficulty in removal, which decreases efficiency. Apparently, in all cases, the resistivity has less effect on the collection efficiency before the resistivity increases to 10¹⁰ Ω·cm. However, once the resistivity exceeds 10¹⁰ Ω·cm, the efficiency starts to drop rapidly for different relative efficiencies with various particle sizes, as shown in Fig. 10(a). The results in Fig. 10(a) show that the relative efficiency of small particles decreased faster than those of large particles in this case, which means that for two particles with the same resistivity (R_d > 10¹⁰ Ω·cm), dust resistivity will have a greater effect on the smaller particles. For example, the relative efficiency of 10 µm decreased by 30% with the increasing dust resistivity from 10¹⁰ to 10¹² Ω·cm. Meanwhile, the relative efficiency of 1 µm is 0.582 with the same resistivity.

Fig. 10. Particle collection and relative efficiencies with increasing dust resistivity were simulated at different particle sizes.

The comparison of average electric field strength with the increasing dust resistivity under different situations, such as applied voltage and layer thickness, is presented in Fig. 11. An important consideration is that different discharge electrode structures and their intensities are classified into three types: type 1 (0.733 mA m^–2), type 2 (0.812 mA m^–2), and type 3 (0.505 mA m^–2) under applied voltage 60 kV. In general, the overall trend of the average electric field was similar to the previously obtained results of dust collection efficiency, which decreases as the particle resistivity increases. Moreover, comparing different levels of applied and discharger types, we found that when the dust resistivity reaches a certain value, the case with the stronger discharge has a higher rate of decline of the average electric field strength. For instance, the decline rate is 32.6% at 80 kV and 28.6% at 60 kV with the same type and thickness of the dust layer with dust resistivity equal to 10¹² Ω·cm. The reason is that for the case of high discharge intensity, the average field intensity is relativity high, but with the addition of high resistivity particles in the ESP, the back corona causes of breakdown voltage decreases, and the spatial field strength drops sharply. Furthermore, similar results were obtained under different levels of discharge types, which are 29.4, 28.6, and 23.9% corresponding to high, medium, and low-intensity discharge. Besides, as expected, the collection of high resistivity particles is adversely affected when the dust layer thickness increases from 3 to 5 mm in this simulation. The particle collection efficiency is also presented in Fig. 11. However, the decline rate of collection efficiency was different compared with the average electric field strength. The results show that the decrease rate under 80 kV condition is not the highest with the increasing dust resistivity from 10⁴ Ω·cm to 10¹² Ω·cm, which means that the strength of the electric field is not the only factor that affects the collection efficiency of particles, although both of them show the same declining trend. Therefore, other factors, such as ionic charge density and polar form, still affect the performance of ESP as the resistivity increases.

Fig. 11. Average electric field strength and particle collection efficiency with increasing dust resistivity under different types of electrode discharge intensity and operation conditions at particle size of 5 µm.

The dust resistivity of particles plays an important role in the degradation of the particle collection efficiency. To further investigate the effect of the resistivity on particle trapping, we analyze the performance degradation of particle migration velocity with the increasing dust resistivity under different simulation conditions, as shown in Fig. 12. The results indicate that the migration velocity decreases when the particle resistivity is sufficiently large. Furthermore, the red dashed lines are fitted to represent and link different decline rates, such as 99%, 90%, 80%, 70%, and 60% for each case. The different regions separated by dotted lines are filled with several colors to represent the ranges of the decline rate for particle migration velocity. Similar to the results of previous studies, when particles with higher resistivity enter the ESP, their migration speed decreases sharply. However, when the different red dotted drop lines are fitted in Fig. 12, the rate of decline in each case with the increasing resistance does not drop together after the dust resistivity reaches a certain value. This figure shows two findings. First, the case in which the strongest discharge is affected is first compared with three other cases. For example, as indicated by the red dotted lines in Fig. 12, the migration velocity of the highest discharger case (80 kV) decreases by 1% first as the dust resistivity increases. This trend is also shown by the 90%, 80%, 70%, and 60% dotted lines. Second, the different color regions indicate that when the resistivity is less than a certain value, the migration velocity does not decrease substantially. However, the particle migration velocity decreases when the resistivity exceeds this specific value and drastically decreases as the resistivity increases further. In the 80 kV case, the reduction of the migration velocity decreased by 57.7% when the dust resistivity increased from 10⁴ Ω·cm to 10¹² Ω·cm.

Fig. 12. Performance degradation of particle migration velocity with increasing dust resistivity under different simulation conditions.

In summary, the results in this section indicate that the dust resistivity not only has a serious impact on particle collection when it reaches a certain value but also show that the effect of dust resistivity on the collection performance is not the same under different discharge intensity conditions. Moreover, the purpose of analyzing these results is to propose a criterion for the decline of the migration velocity under different working conditions and the comparison when the migration velocity decreases by 1% or 10% with various conditions, such as thickness of dust layer, dust resistivity, and applied voltage. Therefore, these results will be fully discussed, and some quantitative suggestions for industrial reference will be given in the following section.

Method to Reduce the Influence of Dust Layer on ESP Performance

In the previous section, the thickness of the dust layer and dust resistivity has been shown to significantly affect the overall electric characteristics and particle collection performance. Therefore, some recommendations were given to reduce the effects of the dust layer by regulating the particle properties and designing dust removal systems.

Based on the research results, even if we do not consider the back corona, reentrainment of dust, and other issues, the dust layer still plays a key role in the ESP. For example, the thickness of the dust layer, dust resistivity, and the same operating parameters affect the performance of the ESP. Thus, how to reduce the impact of relevant aspects becomes an important problem. Furthermore, these interesting phenomena indicated that, in practical applications, if people do not consider particle resistivity and dust layers, then the collection efficiency may be overvalued. These phenomena can also provide ideas to prevent efficiency reduction by thick dust layer or high resistance of particles. Some methods to reduce the influence of the dust layer on particle removal are listed as follows:

• The ESP operating temperature can be adjusted to change the particle resistivity to a suitable range.
• The period of rapping process can be optimized to ensure that the dust layer does not exceed a certain thickness.
• According to different fly ash characteristics, discharge configurations can be changed to reduce the voltage drop of excessive dust layers.

The results were obtained under single-channel wire-plate-type ESP, and the dust resistivity was only a considered factor of particles in this case. Therefore, the exact result for a specific case depends on the particle characteristics and ESP parameters.

CONCLUSION

In this study, the effect of the dust layer on particle migration in a low-temperature ESP was investigated in detail. Detailed conclusions are as follows:

First, the thickness of the dust layer affected the voltage-current characteristics such that a thick dust layer resulted in a sharp reduction of the current density along with the collecting plate. The results show that the different thickness affected the electric potential and ion charge density distribution. Besides, the distribution of electric field strength was severely affected by the dust resistivity and thickness of the dust layer. The reduction in the highest field intensity became lowest with the increasing thickness and resistivity, and the peak value of the electric field strength decreased by more than 40%.

Second, the increasing thickness and dust resistivity rapidly reduced the particle charge. It also affected the performance of particle migration trajectories. Meanwhile, the investigation of collection efficiency showed that the overall efficiency was highest when no dust layer existed for all particle sizes considered in this study. The collection efficiency decreased from 89% to 62.4% with 5 mm and 10¹² Ω·cm dust layer for the 10 µm particles compared with the case without a dust layer.

Finally, the result shows that the collection efficiency reduction is different with the rising thickness of the dust layer under different particle sizes. Also, compared with relative efficiency, the effect of resistivity on the small particle is more significant than that of larger particles. However, a diagram of performance degradation was proposed, which proved that particle migration does not begin to decrease after the resistivity exceeds a particular value in some cases. The reason is that the different discharge conditions also affect the downward trend. Furthermore, some recommendations were presented to control dust thickness and resistivity in a reasonable range by optimizing various working conditions to improve collection efficiency.

ACKNOWLEDGEMENTS

This work is supported by the Australia Research Council (ARC) Research Hub for Computational Particle Technology, Monash University (Australia), State Key Lab of Clean Energy Utilization and State Environmental Protection Engineering Center for Coal-Fired Air Pollution Control (China), National Key Research and Development Program of China (No. 2016YFC0203701).