Electrostatic precipitators (ESP) have been considered as the main particulate matter (PM) removal facility in the energy industry. This paper presents a real-time optimization method for a one-chamber industrial ESP in an ultra-low emission power plant with an intelligent optimization system (IOS). The IOS seeks to optimize the energy consumption of ESP subject to the outlet concentration requirement in real-time. A coordination control logic is designed to regulate the optimized operation set points with varying operation conditions. The operation optimized by the IOS is compared with the operations under PID (proportion-integral-derivative) and manual control. The results show that the IOS improves the emission compliance rate from 95% of manual control to 100% and the medium concentration is tuned to be 46.6% closer to the emission target. Furthermore, a good balance between emission and energy consumption is achieved, with 35.50% energy conservation for the same emission upper limit of 30 mg/m3. These results prove that the IOS significantly contributes to the efficient operation and economic PM removal by ESP for the energy industry. 相似文献
Environmental Science and Pollution Research - To promote the development of the green and low-carbon wood industry and explore the current status and trend of China’s used-furniture... 相似文献
Journal of Material Cycles and Waste Management - The goal of this study is to determine the potential of Acidithiobacillus ferrooxidans strain Z1 in bioleaching of metal concentrates of waste... 相似文献
The association between allergic respiratory diseases, such as asthma and allergic rhinitis (AR), and green space (GS) remains controversial. Our study aimed to summarize and synthesize the association between individual GS exposure and the incidence of asthma/AR. We systematically summarized the qualitative relationship between GS exposure and asthma and AR. The pooled odds ratio (OR) with 95% confidence intervals (CIs) was used to estimate the effect of the Normalized Difference Vegetation Index (NDVI) on asthma and AR. A total of 21 studies were included for systematic review, and 8 of them underwent meta-analysis. In the meta-analysis of current asthma, the 0?<?radius?≤?100 m group, 100?<?radius?≤?300 m group, and 500?<?radius?≤?1000 m group presented weak negative associations between the NDVI and current asthma. For ever asthma, slight positive associations existed in the 0?<?radius?≤?100 m group and 300?<?radius?≤?500 m group. In addition, the NDVI might slightly reduce the risk of AR in radius of 100 m and 500 m. Our findings suggest that the effects of GS exposure on asthma and AR were not significant. Differences in GS measurements, disease diagnoses and adjusted confounders across studies may have an impact on the results. Subsequent studies should consider potential confounding factors and use more accurate GS exposure measurements to better understand the impact of GS exposure on respiratory disease in the population.