A data analysis approach to evaluate the impact of the capacity utilization on the energy consumption of wastewater treatment plants

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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Modelling to Lower Energy Consumption in a Large WWTP in China While Optimising Nitrogen Removal

Energies ◽

10.3390/en14185826 ◽

2021 ◽

Vol 14 (18) ◽

pp. 5826

Author(s):

Mónica Vergara-Araya ◽

Verena Hilgenfeldt ◽

Di Peng ◽

Heidrun Steinmetz ◽

Jürgen Wiese

Keyword(s):

Wastewater Treatment ◽

Energy Consumption ◽

Lower Energy ◽

Wastewater Treatment Plants ◽

Discharge Water ◽

Rapid Changes ◽

Strong Relation ◽

Nitrogen Elimination ◽

The Impact ◽

Automation Strategies

In the last decade, China has sharply tightened the monitoring values for wastewater treatment plants (WWTPs). In some regions with sensitive discharge water bodies, the values (24 h composite sample) must be 1.5 mg/L for NH4-N and 10 mg/L for total nitrogen since 2021. Even with the previously less strict monitoring values, around 50% of the wastewater treatment plants in China were permanently unable to comply with the nitrogen monitoring values. Due to the rapid changes on-site to meet the threshold values and the strong relation to energy-intensive aeration strategies to sufficiently remove nitrogen, WWTPs do not always work energy-efficiently. A Chinese WWTP (450,000 Population equivalents or PE) with upstream denitrification, a tertiary treatment stage for phosphorus removal and disinfection, and aerobic sludge stabilisation was modelled in order to test various concepts for operation optimisation to lower energy consumption while meeting and undercutting effluent requirements. Following a comprehensive analysis of operating data, the WWTP was modelled and calibrated. Based on the calibrated model, various approaches for optimising nitrogen elimination were tested, including operational and automation strategies for aeration control. After several tests, a combination of strategies (i.e., partial by-pass of primary clarifiers, NH4-N based control, increase in the denitrification capacity, intermittent denitrification) reduced the air demand by up to 24% and at the same time significantly improved compliance with the monitoring values (up to 80% less norm non-compliances). By incorporating the impact of the strategies on related processes, like the bypass of primary settling tanks, energy consumption could be reduced by almost 25%. Many of the elaborated strategies can be transferred to WWTPs with similar boundary conditions and strict effluent values worldwide.

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Review of Methods for Assessing the Impact of WWTPs on the Natural Environment

Clean Technologies ◽

10.3390/cleantechnol3010007 ◽

2021 ◽

Vol 3 (1) ◽

pp. 98-122

Author(s):

Joanna Bąk ◽

Krzysztof Barbusiński ◽

Maciej Thomas

Keyword(s):

Environmental Management ◽

Wastewater Treatment ◽

Energy Consumption ◽

Environmental Impact ◽

Natural Environment ◽

Wastewater Treatment Plants ◽

Correct Diagnosis ◽

Current State ◽

The Impact ◽

Constant Improvement

Environmental management in facilities such as wastewater treatment plants (WWTPs) allows for the implementation of the Deming cycle, and thus the constant improvement of the mitigation of the environmental impact. The correct diagnosis of the current state of functioning of the WWTPs, the identification of aspects that may have a measurable impact on the environment, and their assessment are of key importance. The article discusses the possible causes of the impact of WWTPs on the natural environment. Among other problems, such issues as energy consumption, noise and the formation of bioaerosols and odor nuisances were taken into account. Different ways of assessing the impact of wastewater treatment plants on the environment were collated, taking into account the need to assess not only the technological process itself but also the buildings during their use. The results of methods for assessing the environmental impact of wastewater treatment plants in selected countries were also compared.

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Energy audit in small wastewater treatment plants: methodology, energy consumption indicators, and lessons learned

Water Science & Technology ◽

10.2166/wst.2015.306 ◽

2015 ◽

Vol 72 (6) ◽

pp. 1007-1015 ◽

Cited By ~ 37

Author(s):

P. Foladori ◽

M. Vaccari ◽

F. Vitali

Keyword(s):

Wastewater Treatment ◽

Energy Consumption ◽

Wastewater Treatment Plants ◽

Capacity Utilization ◽

Oxygen Demand ◽

Lessons Learned ◽

Electrical Heating ◽

Energy Audit ◽

Energy Audits ◽

Common Situation

Energy audits in wastewater treatment plants (WWTPs) reveal large differences in the energy consumption in the various stages, depending also on the indicators used in the audits. This work is aimed at formulating a suitable methodology to perform audits in WWTPs and identifying the most suitable key energy consumption indicators for comparison among different plants and benchmarking. Hydraulic-based stages, stages based on chemical oxygen demand, sludge-based stages and building stages were distinguished in WWTPs and analysed with different energy indicators. Detailed energy audits were carried out on five small WWTPs treating less than 10,000 population equivalent and using continuous data for 2 years. The plants have in common a low designed capacity utilization (52% on average) and equipment oversizing which leads to waste of energy in the absence of controls and inverters (a common situation in small plants). The study confirms that there are several opportunities for reducing energy consumption in small WWTPs: in addition to the pumping of influent wastewater and aeration, small plants demonstrate low energy efficiency in recirculation of settled sludge and in aerobic stabilization. Denitrification above 75% is ensured through intermittent aeration and without recirculation of mixed liquor. Automation in place of manual controls is mandatory in illumination and electrical heating.

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Forecasting Energy Consumption of Wastewater Treatment Plants with a Transfer Learning Approach for Sustainable Cities

Electronics ◽

10.3390/electronics10101149 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1149

Author(s):

Pedro Oliveira ◽

Bruno Fernandes ◽

Cesar Analide ◽

Paulo Novais

Keyword(s):

Wastewater Treatment ◽

Energy Consumption ◽

Transfer Learning ◽

Short Term Memory ◽

Wastewater Treatment Plants ◽

Learning Approach ◽

Sustainable Cities ◽

Short Term ◽

Long Short Term Memory ◽

Gated Recurrent Units

A major challenge of today’s society is to make large urban centres more sustainable. Improving the energy efficiency of the various infrastructures that make up cities is one aspect being considered when improving their sustainability, with Wastewater Treatment Plants (WWTPs) being one of them. Consequently, this study aims to conceive, tune, and evaluate a set of candidate deep learning models with the goal being to forecast the energy consumption of a WWTP, following a recursive multi-step approach. Three distinct types of models were experimented, in particular, Long Short-Term Memory networks (LSTMs), Gated Recurrent Units (GRUs), and uni-dimensional Convolutional Neural Networks (CNNs). Uni- and multi-variate settings were evaluated, as well as different methods for handling outliers. Promising forecasting results were obtained by CNN-based models, being this difference statistically significant when compared to LSTMs and GRUs, with the best model presenting an approximate overall error of 630 kWh when on a multi-variate setting. Finally, to overcome the problem of data scarcity in WWTPs, transfer learning processes were implemented, with promising results being achieved when using a pre-trained uni-variate CNN model, with the overall error reducing to 325 kWh.

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Methodology for Energy Optimization in Wastewater Treatment Plants. Phase II: Reduction of Air Requirements and Redesign of the Biological Aeration Installation

Water ◽

10.3390/w12041143 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1143

Author(s):

Ana Belén Lozano Avilés ◽

Francisco Del Cerro Velázquez ◽

Mercedes Llorens Pascual Del Riquelme

Keyword(s):

Wastewater Treatment ◽

Energy Consumption ◽

Phase Ii ◽

Wastewater Treatment Plants ◽

Energy Optimization ◽

Treatment Plant ◽

Pressure Losses ◽

San Pedro ◽

Air Supply ◽

Optimization Methodology

Phase I of the proposed energy optimization methodology showed how the selection of best management criteria for the biological aeration process, and the guarantee of its control at the wastewater treatment plant (WWTP) in San Pedro del Pinatar (Murcia, Spain) produced reductions of around 20% in energy consumption by considerably reducing the oxygen needs of the microorganisms in the biological system. This manuscript focused on phase II of this methodology, which describes the tools that can be used to detect and correct deviations in the optimal operating points of the aeration equipment and the intrinsic deficiencies in the installation, in order to achieve optimization of the oxygen needs by the microorganisms and improve the efficiency of their transfer from the gas phase to the liquid phase. The objectives pursued were: (i) to minimize the need for aeration, (ii) to reduce the pressure losses in the installation, (iii) to optimize the air supply pressures to avoid excessive energy consumption for the same airflow, and (iv) to optimize the control strategy for the actual working conditions. The use of flow modeling and simulation techniques, the measurement and calculation of air transfer efficiency through the use of off-gas hoods, and the redesign of the aeration facility at the San Pedro del Pinatar WWTP were crucial, and allowed for reductions in energy consumption in Phase II of more than 20%.

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Ecohydrological modelling of water discharge and nitrate loads in a mesoscale lowland catchment, Germany

Advances in Geosciences ◽

10.5194/adgeo-21-49-2009 ◽

2009 ◽

Vol 21 ◽

pp. 49-55 ◽

Cited By ~ 7

Author(s):

Q. D. Lam ◽

B. Schmalz ◽

N. Fohrer

Keyword(s):

Wastewater Treatment ◽

Municipal Wastewater ◽

Agricultural Land ◽

Assessment Tool ◽

Wastewater Treatment Plants ◽

Water Discharge ◽

Swat Model ◽

Validation Period ◽

Calibration Period ◽

The Impact

Abstract. The aims of this study are to identify the capacities of applying an ecohydrological model for simulating flow and to assess the impact of point and non-point source pollution on nitrate loads in a complex lowland catchment, which has special hydrological characteristics in comparison with those of other catchments. The study area Kielstau catchment has a size of approximately 50 km2 and is located in the North German lowlands. The water quality is not only influenced by the predominating agricultural land use in the catchment as cropland and pasture, but also by six municipal wastewater treatment plants. Ecohydrological models like the SWAT model (Soil and Water Assessment Tool) are useful tools for simulating nutrient loads in river catchments. Diffuse entries from the agriculture resulting from fertilizers as well as punctual entries from the wastewater treatment plants are implemented in the model set-up. The results of this study show good agreement between simulated and measured daily discharges with a Nash-Sutcliffe efficiency and a correlation coefficient of 0.76 and 0.88 for the calibration period (November 1998 to October 2004); 0.75 and 0.92 for the validation period (November 2004 to December 2007). The model efficiency for daily nitrate loads is 0.64 and 0.5 for the calibration period (June 2005 to May 2007) and the validation period (June 2007 to December 2007), respectively. The study revealed that SWAT performed satisfactorily in simulating daily flow and nitrate loads at the lowland catchment in Northern Germany.

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