The problems in generation imbalance for wind power require multi-criteria analysis for the decision makers. In addition to the required multi-criteria analysis, there is also a problem of uncertainty inherent in future changes as a result of interdependence among these criteria. To counter this two problems, this paper describes a systematic approach of Bayesian causal maps and systematic probability generation method. Bayesian causal maps, which is built from causal maps, is used to develop a proposed framework on scenario-based assessment of energy storage technologies for wind power generation. Causal maps provides a rich representation of ideas, through the modeling of complex structures, representing the chain of arguments, as networks.
%0 Book Section
%1 noKey
%A Suharto, Yulianto
%A Daim, TugrulU.
%B Technology Development
%D 2014
%E Daim, Tugrul U.
%E Neshati, Ramin
%E Watt, Russell
%E Eastham, James
%I Springer International Publishing
%K Assessment Bayesian.CausalMap Scenario-Based
%P 91-113
%R 10.1007/978-3-319-05651-7_5
%T Technology Assessment: Energy Storage Technologies for Wind Power Generation
%U http://dx.doi.org/10.1007/978-3-319-05651-7_5
%X The problems in generation imbalance for wind power require multi-criteria analysis for the decision makers. In addition to the required multi-criteria analysis, there is also a problem of uncertainty inherent in future changes as a result of interdependence among these criteria. To counter this two problems, this paper describes a systematic approach of Bayesian causal maps and systematic probability generation method. Bayesian causal maps, which is built from causal maps, is used to develop a proposed framework on scenario-based assessment of energy storage technologies for wind power generation. Causal maps provides a rich representation of ideas, through the modeling of complex structures, representing the chain of arguments, as networks.
%@ 978-3-319-05650-0
@incollection{noKey,
abstract = {The problems in generation imbalance for wind power require multi-criteria analysis for the decision makers. In addition to the required multi-criteria analysis, there is also a problem of uncertainty inherent in future changes as a result of interdependence among these criteria. To counter this two problems, this paper describes a systematic approach of Bayesian causal maps and systematic probability generation method. Bayesian causal maps, which is built from causal maps, is used to develop a proposed framework on scenario-based assessment of energy storage technologies for wind power generation. Causal maps provides a rich representation of ideas, through the modeling of complex structures, representing the chain of arguments, as networks.},
added-at = {2015-01-06T11:59:18.000+0100},
author = {Suharto, Yulianto and Daim, TugrulU.},
biburl = {https://www.bibsonomy.org/bibtex/2f179627789d1dc4b8b3dbec7baaaf47e/ab.mosayyebi},
booktitle = {Technology Development},
doi = {10.1007/978-3-319-05651-7_5},
editor = {Daim, Tugrul U. and Neshati, Ramin and Watt, Russell and Eastham, James},
interhash = {2b74e9f1d154546f8aefefdb6887f68e},
intrahash = {f179627789d1dc4b8b3dbec7baaaf47e},
isbn = {978-3-319-05650-0},
keywords = {Assessment Bayesian.CausalMap Scenario-Based},
language = {English},
pages = {91-113},
publisher = {Springer International Publishing},
series = {Innovation, Technology, and Knowledge Management},
timestamp = {2015-01-06T11:59:18.000+0100},
title = {Technology Assessment: Energy Storage Technologies for Wind Power Generation},
url = {http://dx.doi.org/10.1007/978-3-319-05651-7_5},
year = 2014
}