Research Papers: Gas Turbines: Cycle Innovations

Air-Based Bottoming-Cycles for Water-Free Hybrid Solar Gas-Turbine Power Plants

[+] Author and Article Information
Raphaël Sandoz

e-mail: sandoz@kth.se

James Spelling

e-mail: james.spelling@energy.kth.se

Björn Laumert

e-mail: bjorn.laumert@energy.kth.se

Torsten Fransson

e-mail: torsten.fransson@energy.kth.se
Department of Energy Technology,
KTH Royal Institute of Technology,
Stockholm SE-100 44, Sweden

1Corresponding author.

Contributed by the Cycle Innovations Committee of ASME for publication in the Journal of Engineering for Gas Turbines and Power. Manuscript received June 27, 2013; final manuscript received July 10, 2013; published online September 6, 2013. Editor: David Wisler.

J. Eng. Gas Turbines Power 135(10), 101701 (Sep 06, 2013) (10 pages) Paper No: GTP-13-1192; doi: 10.1115/1.4025003 History: Received June 27, 2013; Revised July 10, 2013

A thermoeconomic model of a novel hybrid solar gas-turbine power plant with an air-based bottoming cycle has been developed, allowing its thermodynamic, economic, and environmental performance to be analyzed. Multi-objective optimization has been performed to identify the trade-offs between two conflicting objectives: minimum capital cost and minimum specific CO2 emissions. In-depth thermoeconomic analysis reveals that the additional bottoming cycle significantly reduces both the levelized cost of electricity and the environmental impact of the power plant (in terms of CO2 emissions and water consumption) when compared to a simple gas-turbine power plant without bottoming cycle. Overall, the novel concept appears to be a promising solution for sustainable power generation, especially in water-scarce areas.

Copyright © 2013 by ASME
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Grahic Jump Location
Fig. 1

Flow sheet of the “air-bottoming” cycle for a hybrid solar gas-turbine power plant

Grahic Jump Location
Fig. 2

Temperature-entropy diagram for an example case of an AB-HSGT

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Fig. 3

TRNSYS flow sheet of the AB-HSGT

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Fig. 4

Pareto optimal front for a typical multi-objective optimization problem

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Fig. 5

Algorithm convergence for the AB-HSGT

Grahic Jump Location
Fig. 6

Specific capital costs versus annual solar share

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Fig. 7

Levelized cost of electricity versus annual solar share

Grahic Jump Location
Fig. 8

Specific CO2 emissions versus LCOE

Grahic Jump Location
Fig. 9

Specific water consumption versus annual solar share

Grahic Jump Location
Fig. 10

Cost of CO2 emissions avoidance versus annual solar share for the AB-HSGT

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Fig. 11

Capital cost breakdown

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Fig. 12

Levelized cost of electricity breakdown

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Fig. 13

Nominal exergy balance and exergy losses for the selected optimal AB-HSGT configuration



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