Model based predictive control for energy efficient biological nitrification process with minimal nitrous oxide production

Behera, Chitta Ranjan; Srinivasan, Babji; Chandran, Kartik; Venkatasubramanian, Venkat

doi:10.1016/j.cej.2015.01.044

Cited by 8 publications

(2 citation statements)

References 41 publications

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“…Several control techniques such as model-predictive (MP), Proportional-Integral-Derivative (PID) and fuzzylogic (FL), can be used to implement the above control principle. While MP control in theory can provide optimal control actions, its application to the N 2 O control problem in full-scale plants is currently not very practical since the present N 2 O models are too uncertain to be used for control (Behera et al, 2015). On the other hand, the PID approach is not suitable to deal with multiple control objectives and the highly nonlinear dynamic behaviour typical of WWT processes.…”

Section: A N U S C R I P Tmentioning

confidence: 99%

A novel fuzzy-logic control strategy minimizing N2O emissions

2017

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A novel control strategy for achieving low NO emissions and low effluent NH concentration is here proposed. The control strategy uses the measurements of ammonium and nitrate concentrations in inlet and outlet of the aerobic zone of a wastewater treatment plant to calculate a ratio indicating the balance among the microbial groups. More specifically, the ratio will indicate if there is a complete nitrification. In case nitrification is not complete, the controller will adjust the aeration level of the plant in order to inhibit the production of NO from AOB and HB denitrification. The controller was implemented using the fuzzy logic approach. It was comprehensively tested for different model structures and different sets of model parameters with regards to its ability of mitigating NO emissions for future applications in real wastewater treatment plants. It is concluded that the control strategy is useful for those plants having AOB denitrification as the main NO producing process. However, in treatment plants having incomplete NHOH oxidation as the main NO producing pathway, a cascade controller configuration adapting the oxygen supply to respect only the effluent ammonium concentration limits was found to be more effective to ensure low NO emissions.

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Section: A N U S C R I P Tmentioning

confidence: 99%

A novel fuzzy-logic control strategy minimizing N2O emissions

2017

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“…The expected output refers to the work of Groen (2010 as the base period); GDP is taken as the index of the desirable output, with the GDP deflator of each city made by the National Bureau of Statistics for deflating treatment (Groen et al, 2013). The non-desired output is calculated by using the calculation method given in the Second Volume (Energy) of the National Greenhouse Gas Inventory Guide of IPCC, based on the nine kinds of energy consumed in various regions and converted into heat and emission coefficients (Behera et al, 2015).…”

Section: Data Source and Variable Selectionmentioning

confidence: 99%

How does education affect urban carbon emission efficiency under the strategy of scientific and technological innovation?

Tang

Dong

Liu

2023

Front. Environ. Sci.

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Low-carbon economy is not only an important topic for the globe but also a serious challenge for China with its economy entering a new level. Based on the DEA-undesirable model and Malmquist index model, urban agglomeration of the Yangtze River Delta and the Guangdong–Hong Kong–Macao Greater Bay Area from 2010 to 2021 were selected as research samples. Based on that, a panel generalized method of moments model was constructed to analyze the effects of the education level, technological development, and their interaction on urban carbon emission efficiency. It found that 1) the carbon emission efficiency of the Yangtze River Delta and the Guangdong–Hong Kong–Macao Greater Bay Area urban agglomerations shows a steady growth trend, but the overall level is low and there are regional differences, among which pure technical efficiency mainly limits the improvement of comprehensive efficiency; 2) the education level and technological development have a high positive correlation on urban carbon emission, and their interaction is conducive to the improvement of carbon emission efficiency. The carbon emission efficiency has a significant advantage under the influence of control variables, such as the economic development level, industrial structure upgrading, opening-up degree, and Internet penetration rate. 3) According to the economic dimension and population dimension, the samples of the Yangtze River Delta and the Guangdong–Hong Kong–Macao Greater Bay Area were divided into large cities and small cities, and regression results showed no substantial changes. It shows that the research conclusion is scientific. According to the aforementioned conclusion, this paper puts forward corresponding countermeasures and suggestions.

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