Simulation assisted process simplification and energy recovery from a cryptic biological nutrient removal plant

Minel Bodur, Samet Ergin, Taner Alkay, Seher Kahraman, Ercan Selvi,Goksin Ozyildiz,Sakine Ugurlu Karaagac,Emine Cokgor,Guclu Insel

JOURNAL OF WATER PROCESS ENGINEERING(2024)

引用 0|浏览8
暂无评分
摘要
In this study, simulation-based analysis is conducted for nitrogen removal mechanism in a biological nutrient removal plant designed in an encrypted manner. In the first phase, the simulation study elucidates how nitrogen removal occurs in a complex design using a series of 4 carousel bioreactors with additional nitrate recycle. It is demonstrated that pre-anoxic volume fed with limited internal recirculation only would not be sufficient to meet the discharge Total Nitrogen (TN) limit of 10 mg N/L. However, the addition of simultaneous nitrification-denitrification (SND) processes in aerobic reactors enables compliance with TN discharge limits. In the second phase, the configuration is simplified by means of process simulation, where the complex design is streamlined by eliminating internal recycle while achieving nitrogen removal through the SND process. Plant data confirmed that the simplified configuration can achieve nitrogen removal providing the same discharge quality. The simulations resulted that TN concentration achieved at the plant effluent is comparable, while effluent total phosphorus concentration is decreased by approximately 50 % due to increased activity of Phosphorus Accumulating Organisms (PAOs) under reduced sludge retention time (SRT). In the third phase, the application of the SND process in the field using a simplified and new activated sludge configuration yields similar results to the simulation. According to plant records, 28 % energy savings and an equivalent chemical cost reduction of euro945,000 per year were achieved with the new process configuration.
更多
查看译文
关键词
Dissolved oxygen control,Plant upgrade,Encrypted design,Denitrification potential,Simultaneous nitrification,Denitrification
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要