DIGICARBA
Outline
Researchers of Water and Wastewater Engineering within the Water and Environmental Engineering Group at Aalto University are developing a digital twin of the wastewater treatment process at Viikinmäki plant in the project called DIGICARBA. A digital twin of the plant is a digital replica of the physical wastewater treatment process with continuous data transmission to produce predictive simulations for operators' decision-making. The research novelty of the new project is to produce a digital twin with a focus on greenhouse gas emissions mitigation. Meanwhile, the practical gain would be to use the developed digital twin for the Viikinmäki plant on a daily basis to support proactive operation and process control. The goals of the project should be accomplished in the timeframe from 2023 to 2025.
The main motivation for optimization process initiation was upcoming updates of the EU Urban Wastewater Treatment Directive that will include requirements on energy neutrality by 2040 for medium and large wastewater treatment plants. Besides the legislative updates, greenhouse gas emission monitoring and control would be implied to achieve sustainable operation of wastewater treatment plants. Soon, many wastewater treatment plants will require optimizing existing processes while avoiding excessive capital costs, which would affect customers.
Description
Hence, creating a digital twin based on a mechanistic model is the option for providing continuous predictive simulations. Operators will use key performance indicators extracted from model simulations for alternative scenario analysis to choose the best scenario of process change that will ensure lower greenhouse gas emissions while not compromising effluent quality. The carbon balance will be improved as GHG emissions will be reduced.
Data sources
The designed digital twin will be based on various sources of data: technical information, historical online and laboratory data, and up-to-date process instrumentation data. Moreover, wastewater analysis will be done for process model adjustments. The data will be pre-processed, organized, and used for process model development, adjustment, calibration, and validation. The process mechanistic model and machine learning tools will be used to create predictive simulations.
Process model
SUMO software from Dynamita SARL will be used to design the digital twin process model. SUMO software has already been used for several modelling study cases worldwide and is suitable for digital twin development. Viikinmäki treatment plant model will include process steps focusing on greenhouse gas emissions, carbon footprint, and energy consumption.
Focus on greenhouse gas emissions
GHG emission modelling still requires comprehensive research as it involves several operational variables and differences in conditions and treatment plant design used in research. However, Viikinmäki treatment plant has a significant design advantage for this study case – it is constructed in underground bedrock with exhaust air pipe equipped with gas compound measurements; therefore, GHG emissions monitoring will be more comprehensive. One of the main contributing GHGs to the carbon footprint of wastewater treatment plants is nitrous oxide (N2O). Viikinmäki plant is equipped with liquid and gaseous phase nitrous oxide measurement sensors providing necessary data for model development. One of the aimed goals will be to provide accurate simulations of GHG emissions.
Collaboration
Before the project initiation, collaborations between Aalto University researchers and INRAE institute director of research Sylvie Gillot were developed to work on greenhouse gas emission mitigation projects, including the DIGICARBA project. Collaboration with Dynamita SARL was also established to work on full-scale model development. DIGICARBA project work will be done cooperating with other researchers in the Water and Wastewater Engineering Group.
Foundation and industry involvement
DIGICARBA project is funded by Business Finland (“Decarbonized Cities” program) from 2023 to 2025 and carried out in collaboration with Helsinki Region Environmental Services Authority HSY, FCG Finnish Consulting Group Oy, Valmet Oyj, Brighthouse Intelligence Oy, Mittausguru Oy, Turun seudun puhdistamo Oy and Hämeenlinnan Seudun Vesi Oy.
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Digital twin for optimizing the carbon balance in wastewater treatment
Researchers at Aalto are creating a digital model for automatic continuous predictive process simulations supporting wastewater treatment plant operation in a new project called DIGICARBA. The proposed digital tool will have a wastewater treatment process model connected to continuous data transmission from the Helsinki wastewater treatment plant.