This study demonstrates the need for novel gas engine control systems for com-
bined heat and power plants, also known as cogeneration power plants, connected to natural
gas grids. Hydrogen addition to natural gas grids in a range of up to 5% by volume is already
permitted throughout Europe. This offers the possibility to reduce carbon dioxide emissions
of end consumers connected to public natural gas grids and contributes to climate protec-
tion. However, conventional engine controls are not designed for natural gas/hydrogen mixture
operation. We tested fuels with up to 30% hydrogen by volume using a commercial six-cylinder
spark ignition engine, designed for natural gas or biogas operation in power plants. With engine
settings according to usual cogeneration operation, nitrogen oxide emissions increased expo-
nentially with increasing hydrogen amounts. We demonstrate that the usual approach of using
the lower heating value of the fuel mixture to regulate the engine is unable to accommodate the
hydrogen induced changes. For this reason, we developed a mathematical model to determine
the nitrogen oxide emissions based on boost pressure and power output. The idea behind this
novel approach is to regulate the engine based on emissions, regardless of the fuel gas. In this
work the approach for this virtual sensor is described and its performance demonstrated.
| Titel | Virtual Nitrogen Oxide Sensor for Improved Emission Control in Natural Gas/Hydrogen Cogeneration Power Plants |
|---|---|
| Medien | 5th International Conference Business Meets Technology, Valencia, Spain |
| Verfasser | Johannes Fichtner, Adrian Gegner, Jan Ninow, Prof. Dr.-Ing. Jörg Kapischke |
| Seiten | 59-66 |
| Veröffentlichungsdatum | 13.07.2023 |
| Projekttitel | SoftSenseValve |
| Zitation | Fichtner, Johannes; Gegner, Adrian; Ninow, Jan; Kapischke, Jörg (2023): Virtual Nitrogen Oxide Sensor for Improved Emission Control in Natural Gas/Hydrogen Cogeneration Power Plants. 5th International Conference Business Meets Technology, Valencia, Spain, 59-66. DOI: 10.4995/BMT2023.2023.16705 |