Spatial R-vine copula for streamflow scenario simulation

Guilherme Pereira; Álvaro Veiga; Tobias Erhardt; Claudia Czado

doi:10.1109/PSCC.2016.7540939

Spatial R-vine copula for streamflow scenario simulation

Guilherme Pereira
, Álvaro Veiga
, Tobias Erhardt
, Claudia Czado

Associate Professorship of Applied Mathematical Statistics

Pontifícia Universidade Católica do Rio de Janeiro
Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

As there are spatial and temporal dependencies of streamflow at hydroelectric power plants (HPPs), we develop a high dimensional statistical model for streamflow scenario simulation which considers both. We use a pair-copula-based model reparametrized in terms of spatial variables derived from the river network, the distance between HPPs and precipitation measurements. This approach reduces the complexity of the model by reducing the number of parameters, preserves however the flexibility introduced by the pair-copulas. Based on simulations, we demonstrate that our model can capture spatial and temporal dependence between HPPs and thus, generate multivariate scenarios that reproduce historical features as shown in an empirical exercise with 39 HPPs.

Original language	English
Title of host publication	19th Power Systems Computation Conference, PSCC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9788894105124
DOIs	https://doi.org/10.1109/PSCC.2016.7540939
State	Published - 10 Aug 2016
Event	19th Power Systems Computation Conference, PSCC 2016 - Genova, Italy Duration: 20 Jun 2016 → 24 Jun 2016

Publication series

Name	19th Power Systems Computation Conference, PSCC 2016

Conference

Conference	19th Power Systems Computation Conference, PSCC 2016
Country/Territory	Italy
City	Genova
Period	20/06/16 → 24/06/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

High dimensional dependence models
spatial R-vine copulas
streamflow scenario simulation
vine copulas

Access to Document

10.1109/PSCC.2016.7540939

Cite this

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title = "Spatial R-vine copula for streamflow scenario simulation",

abstract = "As there are spatial and temporal dependencies of streamflow at hydroelectric power plants (HPPs), we develop a high dimensional statistical model for streamflow scenario simulation which considers both. We use a pair-copula-based model reparametrized in terms of spatial variables derived from the river network, the distance between HPPs and precipitation measurements. This approach reduces the complexity of the model by reducing the number of parameters, preserves however the flexibility introduced by the pair-copulas. Based on simulations, we demonstrate that our model can capture spatial and temporal dependence between HPPs and thus, generate multivariate scenarios that reproduce historical features as shown in an empirical exercise with 39 HPPs.",

keywords = "High dimensional dependence models, spatial R-vine copulas, streamflow scenario simulation, vine copulas",

author = "Guilherme Pereira and {\'A}lvaro Veiga and Tobias Erhardt and Claudia Czado",

note = "Publisher Copyright: {\textcopyright} 2016 Power Systems Computation Conference.; 19th Power Systems Computation Conference, PSCC 2016 ; Conference date: 20-06-2016 Through 24-06-2016",

year = "2016",

month = aug,

day = "10",

doi = "10.1109/PSCC.2016.7540939",

language = "English",

series = "19th Power Systems Computation Conference, PSCC 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "19th Power Systems Computation Conference, PSCC 2016",

}

Pereira, G, Veiga, Á, Erhardt, T & Czado, C 2016, Spatial R-vine copula for streamflow scenario simulation. in 19th Power Systems Computation Conference, PSCC 2016., 7540939, 19th Power Systems Computation Conference, PSCC 2016, Institute of Electrical and Electronics Engineers Inc., 19th Power Systems Computation Conference, PSCC 2016, Genova, Italy, 20/06/16. https://doi.org/10.1109/PSCC.2016.7540939

Spatial R-vine copula for streamflow scenario simulation. / Pereira, Guilherme; Veiga, Álvaro; Erhardt, Tobias et al.
19th Power Systems Computation Conference, PSCC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7540939 (19th Power Systems Computation Conference, PSCC 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Spatial R-vine copula for streamflow scenario simulation

AU - Pereira, Guilherme

AU - Veiga, Álvaro

AU - Erhardt, Tobias

AU - Czado, Claudia

PY - 2016/8/10

Y1 - 2016/8/10

N2 - As there are spatial and temporal dependencies of streamflow at hydroelectric power plants (HPPs), we develop a high dimensional statistical model for streamflow scenario simulation which considers both. We use a pair-copula-based model reparametrized in terms of spatial variables derived from the river network, the distance between HPPs and precipitation measurements. This approach reduces the complexity of the model by reducing the number of parameters, preserves however the flexibility introduced by the pair-copulas. Based on simulations, we demonstrate that our model can capture spatial and temporal dependence between HPPs and thus, generate multivariate scenarios that reproduce historical features as shown in an empirical exercise with 39 HPPs.

AB - As there are spatial and temporal dependencies of streamflow at hydroelectric power plants (HPPs), we develop a high dimensional statistical model for streamflow scenario simulation which considers both. We use a pair-copula-based model reparametrized in terms of spatial variables derived from the river network, the distance between HPPs and precipitation measurements. This approach reduces the complexity of the model by reducing the number of parameters, preserves however the flexibility introduced by the pair-copulas. Based on simulations, we demonstrate that our model can capture spatial and temporal dependence between HPPs and thus, generate multivariate scenarios that reproduce historical features as shown in an empirical exercise with 39 HPPs.

KW - High dimensional dependence models

KW - spatial R-vine copulas

KW - streamflow scenario simulation

KW - vine copulas

UR - https://www.scopus.com/pages/publications/84986594037

U2 - 10.1109/PSCC.2016.7540939

DO - 10.1109/PSCC.2016.7540939

M3 - Conference contribution

AN - SCOPUS:84986594037

T3 - 19th Power Systems Computation Conference, PSCC 2016

BT - 19th Power Systems Computation Conference, PSCC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 19th Power Systems Computation Conference, PSCC 2016

Y2 - 20 June 2016 through 24 June 2016

ER -

Spatial R-vine copula for streamflow scenario simulation

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this