LiquidAirPlant

versión 1.0.2 (13.9 KB) por Sam Yang
LiquidAirPlant is a MATLAB code allowing its users to model various liquid air power plant configurations.

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Actualizada 31 Mar 2022

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LiquidAirPlant

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Overview

LiquidAirPlant is a MATLAB code allowing its users to model various liquid air power plant configurations driven by natural gas combustors, parabolic trough solar collectors, and/or ambient air.

Citation

Please cite the following paper if you reference/use the code

S. Yang, Solar-driven liquid air power plant modeling, design space exploration, and multi-objective optimization, Energy, 2022 https://doi.org/10.1016/j.energy.2022.123324

  • Please note that the PTC rim angle in the paper should be 70 degrees, not 50 degrees. Credit to Kevin Lu at OSU for identifying/reporting the discrepancy.

  • Feel free to use/improve the code/model as needed and submit pull requests.

Dependencies

Quickstart

After cloning the repository, run

driver_verification

in MATLAB to simulate ambient air-driven, natural gas-driven, and recuperative natural gas-driven liquid air power plants (LAPPs) as described in

Antonelli, M., Barsali, S., Desideri, U., Giglioli, R., Paganucci, F. and Pasini, G., 2017. Liquid air energy storage: Potential and challenges of hybrid power plants. Applied energy, 194, pp.522-529.

which were referenced as validation cases for the proposed modeling framework.

You can also run

driver

to simulate a solar-driven LAPP as described in my paper.

Model description

The input file is

plant_input.m

I recommend using structures for clarity/simplicity.

You can find all component models under

.\components\

defined as MATLAB functions. You may also add new component models as functions, e.g.,

function [out1, out2,...,out] = fcn_componentname( struct1, struct2,...,struct )

If you want to model and simulate other plant configurations, you can follow the same system assembly convention as

model_X.m

where X is AA, AANG, RAANG, or AAS.

Citar como

Yang, S. “Solar-Driven Liquid Air Power Plant Modeling, Design Space Exploration, and Multi-Objective Optimization.” Energy, Elsevier BV, Feb. 2022, p. 123324, doi:10.1016/j.energy.2022.123324.

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Compatibilidad con la versión de MATLAB
Se creó con R2020a
Compatible con la versión R2020a y siguientes
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