Correction to: Unit Energy Consumption as Benchmark to Select Energy Positive Retrofitting Strategies for Finnish Wastewater Treatment Plants (WWTPs): a Case Study of Mikkeli WWTP

The energy costs usually represent the second largest part of the running costs of a wastewater treatment plant (WWTP). It is therefore crucial to increase the energy efficiency of these infrastructures and to implement energy management systems, where quantitative performance metrics, such as performance indicators (PIs), play a key role. This paper presents energy PIs which cover the unit energy consumption, production, net use from external sources and costs, and the results used to validate them and derive their reference values. The results of a field study with 17 Portuguese WWTPs (5-year period) were consistent with the results obtained through an international literature survey on the two key parcels of the energy balance – consumption and production. The unit energy consumption showed an overall inverse relation with the volume treated, and the reference values reflect this relation for trickling filters and for activated sludge systems (conventional, with coagulation/filtration (C/F) and with nitrification and C/F). The reference values of electrical energy production were derived from the methane generation potential (converted to electrical energy) and literature data, whereas those of energy net use were obtained by the difference between the energy consumption and production.

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

IEEE Sensors Journal ◽

10.1109/jsen.2020.3030584 ◽

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

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

Energies ◽

10.3390/en14010100 ◽

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.

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Wastewater treatment process impact on energy savings and greenhouse gas emissions

Water Science & Technology ◽

10.2166/wst.2014.521 ◽

2014 ◽

Vol 71 (2) ◽

pp. 303-308 ◽

Cited By ~ 48

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.

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

Journal of Cleaner Production ◽

10.1016/j.jclepro.2020.124248 ◽

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

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Estimating the Chemical Oxygen Demand of Petrochemical Wastewater Treatment Plants Using Linear and Nonlinear Statistical Models – A case study

Chemosphere ◽

10.1016/j.chemosphere.2020.129465 ◽

2021 ◽

pp. 129465

Author(s):

Milad Abouzari ◽

Parham Pahlavani ◽

Fatemeh Izaditame ◽

Behnaz Bigdeli

Keyword(s):

Wastewater Treatment ◽

Chemical Oxygen Demand ◽

Statistical Models ◽

Wastewater Treatment Plants ◽

Oxygen Demand ◽

Petrochemical Wastewater ◽

Linear And Nonlinear

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Analysis of the Total Unit Energy Consumption of a Car with a Hybrid Drive System in Real Operating Conditions

Energies ◽

10.3390/en14133966 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3966

Author(s):

Jarosław Mamala ◽

Michał Śmieja ◽

Krzysztof Prażnowski

Keyword(s):

Energy Consumption ◽

Internal Combustion Engine ◽

Electric Drive ◽

Combustion Engine ◽

Internal Combustion ◽

Operating Conditions ◽

Hybrid Drive ◽

Total Unit ◽

Unit Energy ◽

Unit Energy Consumption

The market demand for vehicles with reduced energy consumption, as well as increasingly stringent standards limiting CO2 emissions, are the focus of a large number of research works undertaken in the analysis of the energy consumption of cars in real operating conditions. Taking into account the growing share of hybrid drive units on the automotive market, the aim of the article is to analyse the total unit energy consumption of a car operating in real road conditions, equipped with an advanced hybrid drive system of the PHEV (plug-in hybrid electric vehicles) type. In this paper, special attention has been paid to the total unit energy consumption of a car resulting from the cooperation of the two independent power units, internal combustion and electric. The results obtained for the individual drive units were presented in the form of a new unit index of the car, which allows us to compare the consumption of energy obtained from fuel with the use of electricity supported from the car’s batteries, during journeys in real road conditions. The presented research results indicate a several-fold increase in the total unit energy consumption of a car powered by an internal combustion engine compared to an electric car. The values of the total unit energy consumption of the car in real road conditions for the internal combustion drive are within the range 1.25–2.95 (J/(kg · m)) in relation to the electric drive 0.27–1.1 (J/(kg · m)) in terms of instantaneous values. In terms of average values, the appropriate values for only the combustion engine are 1.54 (J/(kg · m)) and for the electric drive only are 0.45 (J/(kg · m)) which results in the internal combustion engine values being 3.4 times higher than the electric values. It is the combustion of fuel that causes the greatest increase in energy supplied from the drive unit to the car’s propulsion system in the TTW (tank to wheels) system. At the same time this component is responsible for energy losses and CO2 emissions to the environment. The results were analysed to identify the differences between the actual life cycle energy consumption of the hybrid powertrain and the WLTP (Worldwide Harmonized Light-Duty Test Procedure) homologation cycle.

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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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