Organic Rankine cycle (ORC) systems generate power from low-grade heat sources, such as geothermal sources and industrial waste heat. A key feature is that a working fluid is selected to match the temperature of the source. With the vast pool of candidate working fluids comes the challenge of developing a large number of robust thermodynamic media models. We implemented a subcritical ORC model in Modelica that uses working fluid data records and interpolation schemes in lieu of thermodynamic medium evaluation for energy recovery estimation. This is a component model that can be integrated into a larger energy system model. It does not require detailed thermodynamic, heat transfer, or machine analysis. Our ORC model fills a gap where working fluids are ready to choose or easy to add, and at the same time can be integrated into an energy system.
DA - 02/12/2024 DO - 10.3384/ecp207127 N2 -Organic Rankine cycle (ORC) systems generate power from low-grade heat sources, such as geothermal sources and industrial waste heat. A key feature is that a working fluid is selected to match the temperature of the source. With the vast pool of candidate working fluids comes the challenge of developing a large number of robust thermodynamic media models. We implemented a subcritical ORC model in Modelica that uses working fluid data records and interpolation schemes in lieu of thermodynamic medium evaluation for energy recovery estimation. This is a component model that can be integrated into a larger energy system model. It does not require detailed thermodynamic, heat transfer, or machine analysis. Our ORC model fills a gap where working fluids are ready to choose or easy to add, and at the same time can be integrated into an energy system.
PB - Linköping University Electronic Press PY - 2024 SP - 127 EP - 135 T3 - American Modelica Conference 2024 TI - A Modelica Implementation of an Organic Rankine Cycle UR - https://doi.org/10.3384/ecp207127 VL - 207 SN - 1650-3686 ER -