A multi-fluid PSO-based algorithm for the search of the best performance of sub-critical Organic Rankine Cycles

• Published in: Energy (Oxford) Vol. 129; pp. 42 - 58
• Main Authors: Cavazzini, G., Bari, S., Pavesi, G., Ardizzon, G.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.06.2017; Elsevier BV
• Subjects: Algorithms; Critical temperature; Cycle ratio; Data processing; Heat; Inspection; Optimization; Optimization algorithms; Organic Rankine Cycles; PSO; swarms; System efficiency; Temperature; Temperature effects; Thermodynamics; Vapors; Waste heat; Working fluid; System efficiency; Organic Rankine Cycles; Critical temperature; Waste heat; Working fluid; PSO
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2017.04.090

The present paper focuses on the thermodynamic optimization of a sub-critical ORC for heat source temperatures in the range between 80 and 150 °C. The most significant novelty of the optimization procedure is that the optimization algorithm was modified for this particular application in order to allow the swarm particles to dynamically choose the working fluid among a list of 37 candidates during their heuristic movement, by continuously and dynamically modifying the search domain of each particle iteration-by-iteration due to the different vapour saturation lines of the chosen working fluid. The significant amount of data obtained by the optimization procedure highlighted the dependency of the system efficiency on two main parameters: the Jakob number related to the optimized cycle (Jaopt) and the ratio between the critical temperature of the working fluid and the inlet heat source temperature. At closer inspection, a third new parameter Ω was identified, resulting from the combination of the previous two, whose minimization is correlated to the maximization of system efficiency. A procedure for the preliminary estimation of the optimal cycle allowing to estimate with good accuracy the Jakob number Jaopt and the corresponding value of Ω was also developed. •An PSO algorithm allowing for the dynamic choice of the working fluid is presented.•Thermodynamic optimizations for several heat source temperatures were carried out.•An effective parameter for choosing the best performing working fluids is presented.