A genetic optimization of a hybrid organic Rankine plant for solar and low-grade energy sources. (November 2015)

• Record Type: Journal Article
• Authors: Scardigno, Domenico; Fanelli, Emanuele; Viggiano, Annarita; Braccio, Giacobbe; Magi, Vinicio
• Is Part Of: Energy. Volume 91(2015)
• Page Start: 807
• Page End: 815
• Publication Date: 2015-11
• Subjects: Organic Rankine cycle -- Multi-objective genetic algorithm -- Low-grade energy -- Solar energy -- Thermo-economic analysis; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2015.08.066
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper provides a multi-objective optimization of a hybrid organic Rankine plant for solar and low-grade energy sources. In this plant, water, with a mass flow rate of 1 kg/s at a temperature of 90 °C, preheats the working fluid. The objective of this work is to search for solutions with the highest first and second law efficiencies of the plant and the lowest LEC (levelized energy cost). The design parameters are i) the working fluid, ii) the evaporating and condensing pressure, iii) the maximum temperature of the collector thermal fluid and iv) a parameter representative of the temperature profiles in the heat exchangers. A NSGAII (non-dominated sorting genetic algorithm) has been used. The Pareto front solutions provide Cyclopropane, R143a and R32 as working fluids. The lowest LEC (0.114 $/kWh) and the highest first law efficiency (9.65%) are achieved by using Cyclopropane, with a power output greater than 100 kW. The highest second law efficiency (44%) is obtained by employing R143a, with a low contribution of the solar source and a power output greater than 10 kW. Finally, R32 solutions have comparable performance with respect to R143a solutions. Highlights: The optimization of a low-grade energy source in an ORC hybrid solar power plant is carried out. Thermodynamic and economic indicators are computed with different design parameters. The study employs the NSGAII (non-dominated sorting genetic algorithm II). Cyclopropane is the working fluid that provides the lowest cost and the highest first law efficiency. R143a is the working fluid that provides the highest second law efficiency.