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Model-based energy optimisation of a small-scale decentralised membrane bioreactor for urban reuse

机译:基于模型的小型分散膜生物反应器用于城市回用的能源优化

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摘要

The energy consumption of a small-scale membrane bioreactor, treating high strength domestic wastewater for community level wastewater recycling, has been optimised using a dynamic model of the plant. ASM2d was chosen as biological process model to account for the presence of phosphate accumulating organisms. A tracer test was carried out to determine the hydraulic behaviour of the plant. To realistically simulate the aeration demand, a dedicated aeration model was used incorporating the dependency of the oxygen transfer on the mixed liquor concentration and allowing differentiation between coarse and fine bubble aeration, both typically present in MBRs. A steady state and dynamic calibration was performed, and the calibrated model was able to predict effluent nutrient concentrations and MLSS concentrations accurately. A scenario analysis (SCA) was carried out using the calibrated model to simulate the effect of varying SRT, recirculation ratio and DO set point on effluent quality, MLSS concentrations and aeration demand. Linking the model output with empirically derived correlations for energy consumption allowed an accurate prediction of the energy consumption. The SCA results showed that decreasing membrane aeration and SRT were most beneficial towards total energy consumption, while increasing the recirculation flow led to improved TN removal but at the same time also deterioration in TP removal. A validation of the model was performed by effectively applying better operational parameters to the plant. This resulted in a reduction in energy consumption by 23% without compromising effluent quality, as was accurately predicted by the model. This modelling approach thus allows the operating envelope to be reliably identified for meeting criteria based on energy demand and specific water quality determinants.
机译:小型膜生物反应器(用于处理高强度生活废水以进行社区级废水回收)的能耗已使用工厂的动态模型进行了优化。选择ASM2d作为生物过程模型来说明磷酸盐蓄积生物的存在。进行了示踪剂测试,以确定工厂的水力性能。为了真实地模拟曝气需求,使用了专用的曝气模型,该模型结合了氧气转移对混合液浓度的依赖性,并可以区分通常存在于MBR中的粗气泡和细气泡曝气。进行了稳态和动态校准,并且校准的模型能够准确预测废水中的营养物浓度和MLSS浓度。使用校准后的模型进行了情景分析(SCA),以模拟变化的SRT,再循环比和DO设定点对废水质量,MLSS浓度和曝气需求的影响。将模型输出与经验导出的能耗相关联,可以对能耗进行准确的预测。 SCA结果表明,减少膜的曝气量和SRT对总能耗最有利,而增加再循环流量则可提高TN的去除率,但同时也会降低TP的去除率。通过将更好的运行参数有效地应用于工厂,对模型进行了验证。正如模型所精确预测的那样,这导致能耗降低了23%,而不会影响污水质量。因此,该建模方法允许可靠地确定运行范围,以基于能量需求和特定水质决定因素来满足标准。

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