Heliostat Field Layout Optimization with Evolutionary Algorithms

13 pages•Published: September 29, 2016

Pascal Richter, David Laukamp, Levin Gerdes, Martin Frank and Erika Ábrahám

Abstract

The exploitation of solar power for energy supply is of increasing importance. While technical development mainly takes place in the engineering disciplines, computer science offers adequate techniques for optimization. This work addresses the problem of finding an optimal heliostat field arrangement for a solar tower power plant.
We propose a solution to this global, non-convex optimization problem by using an evolutionary algorithm. We show that the convergence rate of a conventional evolutionary algorithm is too slow, such that modifications of the recombination and mutation need to be tailored to the problem. This is achieved with a new genotype representation of the individuals.
Experimental results show the applicability of our approach.

Keyphrases: evolutionary algorithms, heliostat field layout optimization, solar tower power plants

In: Christoph Benzmüller, Geoff Sutcliffe and Raul Rojas (editors). GCAI 2016. 2nd Global Conference on Artificial Intelligence, vol 41, pages 240-252.

Links:	https://easychair.org/publications/paper/Q9n4
	https://doi.org/10.29007/7p6t

BibTeX entry

@inproceedings{GCAI2016:Heliostat_Field_Layout_Optimization,
  author    = {Pascal Richter and David Laukamp and Levin Gerdes and Martin Frank and Erika Ábrahám},
  title     = {Heliostat Field Layout Optimization with Evolutionary Algorithms},
  booktitle = {GCAI 2016. 2nd Global Conference on Artificial Intelligence},
  editor    = {Christoph Benzmüller and Geoff Sutcliffe and Raul Rojas},
  series    = {EPiC Series in Computing},
  volume    = {41},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/Q9n4},
  doi       = {10.29007/7p6t},
  pages     = {240-252},
  year      = {2016}}

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