4.5 Article Proceedings Paper

Fuzzy-control for improved nitrogen removal and energy saving in WWT-plants with pre-denitrification

期刊

WATER SCIENCE AND TECHNOLOGY
卷 47, 期 11, 页码 69-76

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I W A PUBLISHING
DOI: 10.2166/wst.2003.0588

关键词

energy saving; fuzzy-control; nitrogen removal; process optimisation

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In the last few years, numerous studies were carried out, dealing with the application of fuzzy-logic to improve the control of the activated sludge process. In this paper, fuzzy-logic based control strategies for wastewater treatment plants with pre-denitrification are presented that should lead to better effluent quality and, in parallel, to a reduction of energy consumption. Extensive experimental investigations on a large scale pilot plant as well as simulation studies (ASM1 with SIMBA(R)) were carried out in order to design, evaluate and compare different fuzzy-controllers with each other and with comparable conventional control systems. The fuzzy-controllers were designed as high-level controllers that determine the DO-setpoints in the aerated zones and the ratio between aerated and non-aerated zones. Conventional PI-controllers were used to maintain the DO-concentration at the set-point levels. The ammonia and nitrate concentration in the effluent and the ammonia load in the influent were considered as input variables for the different fuzzy-controllers. Compared to the operation with fixed nitrification/denitrification zones and constant DO concentrations, the required air-flow could be reduced up to 24% by using fuzzy-logic based control strategies. In comparison with a more advanced conventional control strategy (relay controller with two thresholds and the NH4-N concentration in the effluent as single control variable) a reduction of air-flow-rate up to 14% could be achieved. At the same time, NH4-N peaks in the effluent that are normally caused by peak flow conditions could be reduced significantly. The large scale experiments show that the fuzzy-controllers can be easily implemented in modern control and supervision systems and that the control characteristics can be followed and modified during operation. It therefore can be expected that the developed fuzzy-control systems will be accepted by the operating personnel in wastewater treatment plants.

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