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  • Renewable energy sources are becoming a significant part of todays energy mix. The unstable production of many renewable energy sources including photovoltaic and wind power plants puts increased demands on power transmission systems and on the power grid as a whole. Soft computing methods can contribute to the prediction of electric energy production of renewable resources and therefore to the reliability of the power transmission networks. This work compares two soft computing methods that utilize genetic programming to evolve predictors of a selected renewable energy resource that meets the real world criterion of high output variance and relatively large installed power (in context of the power distribution system of the Czech Republic). 2012 IEEE.
  • Renewable energy sources are becoming a significant part of todays energy mix. The unstable production of many renewable energy sources including photovoltaic and wind power plants puts increased demands on power transmission systems and on the power grid as a whole. Soft computing methods can contribute to the prediction of electric energy production of renewable resources and therefore to the reliability of the power transmission networks. This work compares two soft computing methods that utilize genetic programming to evolve predictors of a selected renewable energy resource that meets the real world criterion of high output variance and relatively large installed power (in context of the power distribution system of the Czech Republic). 2012 IEEE. (en)
Title
  • Artificially evolved soft computing models for photovoltaic power plant output estimation
  • Artificially evolved soft computing models for photovoltaic power plant output estimation (en)
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  • Artificially evolved soft computing models for photovoltaic power plant output estimation
  • Artificially evolved soft computing models for photovoltaic power plant output estimation (en)
skos:notation
  • RIV/61989100:27240/12:86085009!RIV13-MSM-27240___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(EE.2.3.20.0073), P(FR-TI1/420), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
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  • 123721
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/12:86085009
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • prediction; photovoltaic power plant; genetic programming; fuzzy rules; flexible neural trees (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [3EB592C4D9BB]
http://linked.open...v/mistoKonaniAkce
  • Soul
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 2012
http://linked.open...in/vavai/riv/obor
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http://linked.open...iv/tvurceVysledku
  • Krömer, Pavel
  • Mišák, Stanislav
  • Platoš, Jan
  • Prokop, Lukáš
  • Snášel, Václav
  • Novosád, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1062-922X
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ICSMC.2012.6377861
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4673-1714-6
http://localhost/t...ganizacniJednotka
  • 27240
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