Abstract

The object of the study are substances that are used as a working fluid in systems operating on the basis of an organic Rankine cycle. The purpose of research is to find substances with the best thermodynamic, thermal and environmental properties. Research conducted on the basis of the analysis of thermodynamic and thermal properties of substances from the base “REFPROP” and with the help of numerical simulation of combined-cycle plant utilization triple cycle, where the lower cycle is an organic Rankine cycle. Base “REFPROP” describes and allows to calculate the thermodynamic and thermophysical parameters of most of the main substances used in production processes. On the basis of scientific publications on the use of working fluids in an organic Rankine cycle analysis were selected ozone-friendly low-boiling substances: ammonia, butane, pentane and Freon: R134a, R152a, R236fa and R245fa. For these substances have been identified and tabulated molecular weight, temperature of the triple point, boiling point, at atmospheric pressure, the parameters of the critical point, the value of the derivative of the temperature on the entropy of the saturated vapor line and the potential ozone depletion and global warming. It was also identified and tabulated thermodynamic and thermophysical parameters of the steam and liquid substances in a state of saturation at a temperature of 15 °C. This temperature is adopted as the minimum temperature of heat removal in the Rankine cycle when working on the water. Studies have shown that the best thermodynamic, thermal and environmental properties of the considered substances are pentane, butane and R245fa. For a more thorough analysis based on a gas turbine plant NK-36ST it has developed a mathematical model of combined cycle gas turbine (CCGT) triple cycle, where the lower cycle is an organic Rankine cycle, and is used as the air cooler condenser. Air condenser allows stating material at a temperature below 0 °C. Calculation of the parameters of all substances in the model are based on a base “REFPROP”. Numerical investigations on this model showed that the highest net efficiency will be at work on pentane. Butane and R245fa have the same net efficiency, for 0.8% lower than pentane. Ammonia has a net efficiency of 2.5% is lower than pentane. CCP net efficiency strongly depends on the condensation temperature of the substance, as for pentane at lower temperature of condensation at 10 °C it is increased by 1%.

Highlights

  • Organic Rankine Cycle (ORC) – is a cycle, the working substance of which are low-boiling substances (LBS)

  • For a more thorough analysis based on a gas turbine plant NK36ST it has developed a mathematical model of combined cycle gas turbine (CCGT) triple cycle, where the lower cycle is an organic Rankine cycle, and is used as the air cooler condenser

  • CCP net efficiency strongly depends on the condensation temperature of the substance, as for pentane at lower temperature of condensation at 10 °C it is increased by 1%

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Summary

Introduction

Organic Rankine Cycle (ORC) – is a cycle, the working substance of which are low-boiling substances (LBS). Use as a working substance of the LBS allows to solve a number of problems existing water as the working medium: lower the temperature of the heat removal through the use of air condensers in the winter and increase the efficiency of this cycle; due to a high density to reduce the size, weight and cost of the units; by condensing steam at high pressures to reduce or eliminate air suction to the condenser and to improve heat transfer there in. The ORC is used to generate electricity from of low potential waste heat, but as shown in [10, 11] it can be used in a combined cycle gas turbine (CCP) and schemes of powerful units thermal and nuclear power. Safety and environmental performance of the ORC are highly dependent on the type of the LBS. Environmental cleanliness LBS is determined ozone depletion potential (ODP) and global warming potential (GWP)

Select the substances and analysis based on database REFPROP
Findings
Analysis using CCP model
Full Text
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