Artificially evolved soft computing models for photovoltaic power plant output estimation
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Prokop:2012:SMC,
-
author = "Lukas Prokop and Stanislav Misak and Tomas Novosad and
Pavel Kromer and Jan Platos and Vaclav Snasel",
-
booktitle = "IEEE International Conference on Systems, Man, and
Cybernetics (SMC 2012)",
-
title = "Artificially evolved soft computing models for
photovoltaic power plant output estimation",
-
year = "2012",
-
pages = "1011--1016",
-
month = oct # " 14-17",
-
address = "Seoul, Korea",
-
DOI = "doi:10.1109/ICSMC.2012.6377861",
-
size = "6 pages",
-
abstract = "Renewable energy sources are becoming a significant
part of today's 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 use 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).",
-
keywords = "genetic algorithms, genetic programming, distribution
networks, neural nets, photovoltaic power systems,
power engineering computing, power grids, power
transmission reliability, Czech Republic, artificially
evolved soft computing model, electric energy
production prediction, flexible neural tree,
hierarchical neural network, photovoltaic power plant
output estimation, power distribution system, power
grid, power transmission network reliability, power
transmission system, renewable energy sources, wind
power plant, Photovoltaic systems, Sociology,
Statistics, flexible neural trees, fuzzy rules,
photovoltaic power plant, prediction",
-
notes = "Also known as \cite{6377861}",
- }
Genetic Programming entries for
Lukas Prokop
Stanislav Misak
Tomas Novosad
Pavel Kromer
Jan Platos
Vaclav Snasel
Citations