Multi-objective particle swarm optimization of binary geothermal power plants

Joshua Clarke and James T. McLeskey

Applied Energy, 2015, vol. 138, issue C, 302-314

Abstract: In this paper, a method for determining the optimum use of a superheater and/or recuperator in a binary geothermal power plant is developed. Additionally, a multi-objective optimization algorithm is developed to intelligently explore the trade-off between specific work output and specific heat exchanger area and allow visualization of the entire Pareto-optimal set of designs for a wide range of geothermal brine temperatures and dry-bulb temperatures. Selected data is tabulated to show representative optimal designs for each combination of dry-bulb temperature and brine temperature. This work illustrates the development and use of a sophisticated analysis tool utilizing multi-objective particle swarm optimization to allow calculation of the Pareto-optimal set of designs under any combination of dry-bulb temperature and brine temperature while accounting for necessary real-world constraints.

Keywords: Geothermal electric; Binary geothermal; Particle swarm optimization; Multi-objective optimization (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:138:y:2015:i:c:p:302-314

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DOI: 10.1016/j.apenergy.2014.10.072

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