A4 Conference proceedings

Techno-economic optimization of a back pressure condenser in a small cogeneration plant with a novel greedy cuckoo search algorithm


Publication Details
Authors: Saari Jussi, Neto Márcio, Cardoso Marcelo, Mankonen Aleksi, Kaikko Juha, Vakkilainen Esa
Publication year: 2020
Language: English
Related Journal or Series Information: Proceedings of the International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems
Title of parent publication: 33rd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2020)
Journal acronym: ECOS
Start page: 1177
End page: 1188
Number of pages: 12
ISBN: 978-1-7138-1406-1
ISSN: 2175-5418
eISSN: 2175-5426
JUFO-Level of this publication: 1
Permanent website address: http://www.proceedings.com/55242.html
Open Access: Not an Open Access publication

Abstract

The
goal of the study was to develop an optimization methodology combining a cost
model, a 2-D heat transfer model, and load variation, executable in a feasible
time in a PC. The cogeneration plant performance at different load points as a
function of the condenser performance is found with process simulation software
to create the objective function to maximize the annual net cash flow. Due to
the computationally heavy heat transfer model, and each objective function
evaluation requiring multiple runs, one per load point, improving optimizer
performance was given particular attention. A novel hybridization of cuckoo
search and a greedy differential evolution strategy was created for this; the
new algorithm is shown to perform better than either of its parent algorithms
or other benchmarks, finding optimal solution in reliably, and within
approximately half the number of function evaluations as required by the parent
algorithms.


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Last updated on 2020-09-11 at 11:37

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