Energy consumption analysis in wastewater treatment plants using simulation and SCADA system: Case study in northern Taiwan

2020 ◽  
Vol 276 ◽  
pp. 124248
Author(s):  
Wu-Yang Sean ◽  
Ya-Yun Chu ◽  
Lili Lorensia Mallu ◽  
Jian-Gu Chen ◽  
Han-Yang Liu
Keyword(s):  
Wastewater Treatment ◽  
Energy Consumption ◽  
Wastewater Treatment Plants ◽  
Scada System ◽  
Energy Consumption Analysis ◽  
Northern Taiwan

scholarly journals A Data-Driven Soft Sensor to Forecast Energy Consumption in Wastewater Treatment Plants: A Case Study

2020 ◽  
pp. 1-1
Author(s):  
Fouzi Harrou ◽  
Tuoyuan Cheng ◽  
Ying Sun ◽  
Tor Ove Leiknes ◽  
Noreddine Ghaffour
Keyword(s):  
Wastewater Treatment ◽  
Energy Consumption ◽  
Wastewater Treatment Plants ◽  
Soft Sensor ◽  
Data Driven

scholarly journals Energetic-Environmental-Economic Feasibility and Impact Assessment of Grid-Connected Photovoltaic System in Wastewater Treatment Plant: Case Study

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 100
Author(s):  
Horia Andrei ◽  
Cristian Andrei Badea ◽  
Paul Andrei ◽  
Filippo Spertino
Keyword(s):  
Power Generation ◽  
Wastewater Treatment ◽  
Energy Consumption ◽  
Wastewater Treatment Plant ◽  
Wastewater Treatment Plants ◽  
Treatment Plant ◽  
Economic Feasibility ◽  
Photovoltaic System ◽  
The Impact

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.

Wastewater treatment process impact on energy savings and greenhouse gas emissions

2014 ◽  
Vol 71 (2) ◽  
pp. 303-308 ◽  
Author(s):  
D. Mamais ◽  
C. Noutsopoulos ◽  
A. Dimopoulou ◽  
A. Stasinakis ◽  
T. D. Lekkas
Keyword(s):  
Wastewater Treatment ◽  
Energy Consumption ◽  
Greenhouse Gas ◽  
Energy Savings ◽  
Wastewater Treatment Plants ◽  
Specific Energy Consumption ◽  
Ghg Emissions ◽  
Wastewater Treatment Process ◽  
Conventional Activated Sludge

The objective of this research was to assess the energy consumption of wastewater treatment plants (WWTPs), to apply a mathematical model to evaluate their carbon footprint, and to propose energy saving strategies that can be implemented to reduce both energy consumption and greenhouse gas (GHG) emissions in Greece. The survey was focused on 10 WWTPs in Greece with a treatment capacity ranging from 10,000 to 4,000,000 population equivalents (PE). Based on the results, annual specific energy consumption ranged from 15 to 86 kWh/PE. The highest energy consumer in all the WWTPs was aeration, accounting for 40–75% of total energy requirements. The annual GHG emissions varied significantly according to the treatment schemes employed and ranged between 61 and 161 kgCO2e/PE. The highest values of CO2 emissions were obtained in extended aeration systems and the lowest in conventional activated sludge systems. Key strategies that the wastewater industry could adopt to mitigate GHG emissions are identified and discussed. A case study is presented to demonstrate potential strategies for energy savings and GHG emission reduction. Given the results, it is postulated that the reduction of dissolved oxygen (DO) set points and sludge retention time can provide significant energy savings and decrease GHG emissions.

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

Electronics ◽  
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.

Controlling the Settling of Activated Sludge in Pulp and Paper Wastewater Treatment Plants

1999 ◽  
Vol 40 (11-12) ◽  
pp. 223-229 ◽  
Author(s):  
Frédéric Clauss ◽  
Christel Balavoine ◽  
Delphine Hélaine ◽  
Gaëtan Martin
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Pulp And Paper ◽  
Organic Load ◽  
Forest Industry ◽  
Filamentous Bulking ◽  
Mineral Particles ◽  
Mineral Powder

Forest industry wastewaters are difficult to clean: hydraulic and organic load variations, filamentous bulking or pin-point flocs negatively impact depollution processes. The addition of a fine, mineral, talc-based powder, Aquatal, into the aeration tanks of wastewater treatment plants connected to pulp and paper factories has been successfully tested since end of '97. The first case-study presents full results obtained over a period of 18 months in a 20,000 p.e. plant connected to a paper factory. The mineral powder was regularly added to control sludge volume index, thereby ensuring low suspended solids concentration in the outfluent. Plant operators could easily adapt biomass concentration to match organic load variation, thereby maintaining pollution micro-organisms ratio constant. In a second case study, a trouble-shooting strategy was implemented to counteract filamentous bulking. A one-off, large dosage enabled the plant operator to deal effectively with poor settleability sludge and rapidly control sludge blanket expansion. In both cases, the main common characteristics observed were an increase in floc aggregation and the production of heavier and well-structured flocs. The sludge settling velocity increased and an efficient solid/liquid separation was obtained. After a few days, the mineral particles of Aquatal were progressively integrated into the sludge floc structure. When the mineral powder was added to the activated sludge in the aeration basin, chemical interactions frequently encountered with other wastewater treatment additives did not pose a problem. Moreover, with this mineral additive, the biological excess sludge displayed good thickening properties and dewatering was improved. Despite the addition of the insoluble mineral particles, the amount of wet sludge expelled did not increase. Aquatal offers a rapid solution to floc settleability problems which so frequently arise when physical or biological disorders appear in forest industry wastewater treatment plants.

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

Water ◽  
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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