Multi-objective optimization of synthesis gas composition for an oxyfuel gas engine

The Lusatia region in east Europe is challenged by rapid environmental and climatic changes in the last decades. Therefore, energy generation from conventional sources such as coal, natural gas and oil is a major concern regarding greenhouse gas emissions. To address these concerns strategies for CO2 mitigation and renewable energy transition have been released by the local decision makers.
We will develop a Power-to-Gas-to-Power system for CO2-neutral renewable energy storage and reconversion to power and heat. The system is based on water electrolysis, methanation reactor, stationary gas engine and chemical storage. The synthesis gas from the reactor and oxygen from water electrolysis are utilized in the stationary gas engine to produce power and heat. Oxyfuel combustion generates significantly higher combustion temperatures compared to conventional combustion with air, wherefor efficient strategies for temperature reduction are investigated, such as CO2 and H2O dilution, and low-calorific synthesis gases.
This work presents an optimization campaign of the methanation reactor and gas engine system to achieve required heat and power demands for different seasons, while keeping the operation of the reactor and engine safe and stable. The methanation reactor operation will be optimized by changing the pressure, temperature, and H2/CO2 ratio, and conduct equilibrium calculations to determine the synthesis gas composition. The engine operation will be optimized by using the dry synthesis gas as a fuel, and additionally dilute the cylinder with CO2 to control the combustion temperature. The engine simulation will be conducted using the stochastic reactor model with detailed chemistry. The optimization method will be developed in modeFRONTIER 2022R3 using the Non-dominated Sorting Genetic Algorithm II and FAST algorithm.