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Thermo-Fluids Research Centre (TFRC)
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Thermo-Fluids

NextORC: Fundamental studies on Organic Rankine Cycle expanders

NextORC is an EPSRC funded project (Grant number: EP/P009131/1) that is running from May 2017 until April 2020. The focus of the project is to improve fundamental understanding on the performance of screw and turbo expanders within organic Rankine cycle (ORC) systems. The project is a collaboration between the Turbomachinery and Compressor Centre research groups at City, and is being completed in partnership with Heliex Power.

Background and motivation

Commercial steam power plants pressurise and heat water to produce steam which is then expanded to produce electricity. However, using an organic fluid permits low temperature heat sources, typically between 80 and 350°C, to be converted into mechanical power more economically than steam. Organic Rankine cycles (ORC) have a great potential to contribute to the UK's mix of low-carbon technologies with promising applications such as combined heat and power, concentrated-solar power and waste-heat recovery from reciprocating engines and other industrial processes with waste heat streams. However, despite successful commercialisation of ORCs for industrial-scale applications, more development is required at the commercial and domestic scales before its potential can be realised. More specifically, at these small-scales, the challenge lies in the design of systems that are efficient but are also low cost. One approach to achieving this is to develop systems that operate efficiently over a range of different conditions. This will enable the high-volume, low-cost production of ORC systems, enabling significant improvements in the economy-of-scale. Furthermore, at this scale, different expander technologies, such as turbo and screw expanders, and system architectures can be considered. However, it is not clear which expander technology or system architecture is the optimal choice to achieve the desired improvements in the economy-of-scale. To answer this question, it is important to improve the understanding of how different ORC expanders perform across a wide range of operating conditions, and to investigate how these systems respond to changes in the working fluid.

Project objectives

The over-arching aim of this project is to improve the understanding of ORC expander design and off-design performance through developing, and validating, suitable tools to accurately predict design point and off-design performance of ORC systems. This will be achieved by targeting research towards five objectives:

  1. Improve the fundamental understanding of design point scaling and off-design performance of supersonic turbines operating with non-ideal gases, and develop improved performance models
  2. Improve the fundamental understanding of the performance of screw expanders during two-phase expansion and to develop improved screw expander performance models
  3. To upgrade an existing experimental test facility to enable the characterisation of loss mechanisms present within ORC expanders and provide validation of performance models and CFD codes
  4. To understand how single and cascaded systems, comprising of both turbine and screw expanders, operate under different heat source conditions and with different working fluids
  5. To identify system configurations that can operate over a range of operating conditions and provide the best compromise between design and off-design performance, and system cost

Key deliverables and outcomes

The primary outcomes of this research will be improved fundamental understanding of the performance of ORC expanders for turbine and screw expanders. This information will allow the identification of optimal systems configurations that offer improvements in. More specifically, this project will deliver:

  1. Validated performance models for ORC turbines
  2. Validated performance models for two-phase screw expanders operating with both mixed and separated inlet flows
  3. State-of-the-art ORC testing facilities for validation of component performance models
  4. Recommendations on the most appropriate system configurations that can be implemented within a range of potential applications, thus improving the economy-of-scale