scholarly journals Structure and indicators of electric energy consumption in dairy wastewater treatment plant

Author(s):  
Radosław Żyłka ◽  
Beata Karolinczak ◽  
Wojciech Dąbrowski
Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3769 ◽  
Author(s):  
Radosław Żyłka ◽  
Wojciech Dąbrowski ◽  
Paweł Malinowski ◽  
Beata Karolinczak

The intensification of biological wastewater treatment requires the high usage of electric energy, mainly for aeration processes. Publications on energy consumption have been mostly related to municipal wastewater treatment plants (WWTPs). The aim of the research was to elaborate on models for the estimation of energy consumption during dairy WWTP operation. These models can be used for the optimization of electric energy consumption. The research was conducted in a dairy WWTP, operating with dissolved air flotation (DAF) and an activated sludge system. Energy consumption was measured with the help of three-phase network parameter transducers and a supervisory control and data acquisition (SCADA) system. The obtained models provided accurate predictions of DAF, biological treatment, and the overall WWTP energy consumption using chemical oxygen demand (COD), sewage flow, and air temperature. Using the energy consumption of the biological treatment as an independent variable, as well as air temperature, it is possible to estimate the variability of the total electric energy consumption. During the summer period, an increase in the organic load (expressed as COD) discharged into the biological treatment causes higher electric energy consumption in the whole dairy WWTP. Hence, it is recommended to increase the efficiency of the removal of organic pollutants in the DAF process. An application for the estimation of energy consumption was created.


2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
ZhenHua Li ◽  
ZhiHong Zou ◽  
LiPing Wang

Wastewater treatment plant (WWTP) is the energy-intensive industries. Energy is consumed at every stage of wastewater treatment. It is the main contributor to the costs of WWTP. Analysis and forecasting of energy consumption are critical to energy-saving. Many factors influence energy consumption. The relationship between energy consumption and wastewater is complex and challenging to identify. This article employed the fuzzy clustering method to categorize the sample data of WWTP and analyzed the relationship between energy consumption and the influence factors in different categories. The study found that energy efficiency in various categories was changed and the same influence factors in different types had different influence intensity. The Radial Basis Function (RBF) neural network was used to forecast energy consumption. The data from the complete set and categories was adopted to train and test the model. The results show that the RBF model using the date from the subset has better performance than the multivariable linear regression (MLR) model. The results of this study provided an essential theoretical basis for energy-saving in WWTP.


2012 ◽  
Vol 66 (6) ◽  
pp. 1277-1281 ◽  
Author(s):  
P. Jenicek ◽  
J. Bartacek ◽  
J. Kutil ◽  
J. Zabranska ◽  
M. Dohanyos

Anaerobic digestion is the only energy-positive technology widely used in wastewater treatment. Full-scale data prove that the anaerobic digestion of sewage sludge can produce biogas that covers a substantial amount of the energy consumption of a wastewater treatment plant (WWTP). In this paper, we discuss possibilities for improving the digestion efficiency and biogas production from sewage sludge. Typical specific energy consumptions of municipal WWTPs per population equivalent are compared with the potential specific production of biogas to find the required/optimal digestion efficiency. Examples of technological measures to achieve such efficiency are presented. Our findings show that even a municipal WWTP with secondary biological treatment located in a moderate climate can come close to energy self-sufficiency. However, they also show that such self-sufficiency is dependent on: (i) the strict optimization of the total energy consumption of the plant, and (ii) an increase in the specific biogas production from sewage sludge to values around 600 L per kg of supplied volatile solids.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 100
Author(s):  
Horia Andrei ◽  
Cristian Andrei Badea ◽  
Paul Andrei ◽  
Filippo Spertino

Wastewater treatment plants and power generation constitute inseparable parts of present society. So the growth of wastewater treatment plants is accompanied by an increase in the energy consumption, and a sustainable development implies the use of renewable energy sources on a large scale in the power generation. A case study of the synergy between wastewater treatment plants and photovoltaic systems, aiming to improve the energetic, environmental and economic impacts, is presented. Based on data acquisition, the energy consumption analysis of wastewater treatment plant reveals that the highest demand is during April, and the lowest is during November. The placement of photovoltaic modules is designed to maximize the use of free space on the technological area of wastewater treatment plant in order to obtain a power output as high as possible. The peak consumption of wastewater treatment plant occurs in April, however the peak production of the photovoltaic is in July, so electrochemical batteries can partly compensate for this mismatch. The impact of the photovoltaic system connectivity on power grid is assessed by means of the matching-index method and the storage battery significantly improves this parameter. Carbon credit and energy payback time are used to assess the environmental impact. The results prove that the photovoltaic system mitigates 12,118 tons of carbon and, respectively, the embedded energy is compensated by production in 8 ½ years. The economic impact of the photovoltaic system is analyzed by the levelized cost of energy, and the results show that the price of energy from the photovoltaic source is below the current market price of energy.


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