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Electricity based heat supply of the chemical industry
Design the future energy system of the chemical industry. Rethink and optimize the energy system and develop the required technologies. Think holistically and consider thermodynamic, economics, and ecology.
Keywords: energy system optimization; process design; heat pumps; waste heat recovery; renewable energy; power-to-heat; steam
Traditionally, production facilities in chemical parks are supplied with energy by steam at various pressure levels. The steam is usually generated by burning fossil fuels in central plants. The worldwide effort to reduce CO2 emissions will change the situation. The transition to renewable energy sources, such as wind power, photovoltaics, or hydropower, leads to a stronger focus on electricity also for heat generation. This forces the significance of high efficient power-to-heat processes also for high temperature heat.
There are many degrees of freedom in realizing the energy transition in the chemical industry. Various technologies for converting electricity into heat exist, such as conventional electricity-driven steam boilers, vapor-compression heat pumps, and Brayton heat pumps. These technologies have different properties (efficiencies, media, dynamic behavior, etc.) and different requirements (investment costs, integration into the overall system, etc.). An aspect that complicates the assessment is that these technologies partly have a low Technological-Readiness-Level (TRL) and are not yet commercially available. Thus, these technologies' characteristics (efficiency, costs, etc.) have to be estimated by thermoeconomic process models.
Traditionally, production facilities in chemical parks are supplied with energy by steam at various pressure levels. The steam is usually generated by burning fossil fuels in central plants. The worldwide effort to reduce CO2 emissions will change the situation. The transition to renewable energy sources, such as wind power, photovoltaics, or hydropower, leads to a stronger focus on electricity also for heat generation. This forces the significance of high efficient power-to-heat processes also for high temperature heat. There are many degrees of freedom in realizing the energy transition in the chemical industry. Various technologies for converting electricity into heat exist, such as conventional electricity-driven steam boilers, vapor-compression heat pumps, and Brayton heat pumps. These technologies have different properties (efficiencies, media, dynamic behavior, etc.) and different requirements (investment costs, integration into the overall system, etc.). An aspect that complicates the assessment is that these technologies partly have a low Technological-Readiness-Level (TRL) and are not yet commercially available. Thus, these technologies' characteristics (efficiency, costs, etc.) have to be estimated by thermoeconomic process models.
In this work, we will consider data from a typical chemical park, including both the supply and demand sides. We will completely delete the fossil-based energy supply system and start from scratch with electrically-driven technologies. The overarching research question is how an electrivcally-driven energy supply system should be structured to guarantee the energy supply while beeing economically and ecologically competitive.
You will use or learn the following skills:
- Thermoeconomically process modeling by non-linear programming (NLP)
- Linearization using piecewise linear regression
- Energy system optimization using mixed-integer linear programming (MILP)
In this work, we will consider data from a typical chemical park, including both the supply and demand sides. We will completely delete the fossil-based energy supply system and start from scratch with electrically-driven technologies. The overarching research question is how an electrivcally-driven energy supply system should be structured to guarantee the energy supply while beeing economically and ecologically competitive. You will use or learn the following skills:
- Thermoeconomically process modeling by non-linear programming (NLP)
- Linearization using piecewise linear regression
- Energy system optimization using mixed-integer linear programming (MILP)
If you are interested in this master's thesis, please get in touch with Dr. Dennis Roskosch (droskosch@ethz.ch)
If you are interested in this master's thesis, please get in touch with Dr. Dennis Roskosch (droskosch@ethz.ch)