Matches in SemOpenAlex for { <https://semopenalex.org/work/W2990413853> ?p ?o ?g. }
- W2990413853 endingPage "114127" @default.
- W2990413853 startingPage "114127" @default.
- W2990413853 abstract "Wind power energy has been showing significant growth in installed capacity around the world. This opportunity presents big challenges to operate power systems with high wind power penetration levels, considering the variability and intermittent behavior of this type of power source. To reduce uncertainties associated with this kind of power systems, researchers have explored the integration of wind power energy with other renewable energy sources, like solar and hydropower. For instance, the integration of wind and hydro systems can deal with the spatial and temporal complementarity of hydrological and wind regimes to produce energy. Therefore, it is necessary to consider the stochastic behavior and the dependence structures between these variables to define better operational policies. This study explores the spatial correlation of hydrological and wind regimes in different regions of Brazil and defines an entropy-copula-based model for the joint simulation of monthly streamflow and wind speed time series to evaluate the potential integration of hydro and wind energy sources. The proposed model showed a good adherence to the periodic behavior for both variables, and the results indicate that simulated scenarios preserved statistical features of historical data." @default.
- W2990413853 created "2019-12-05" @default.
- W2990413853 creator A5011773427 @default.
- W2990413853 creator A5032656130 @default.
- W2990413853 creator A5035879803 @default.
- W2990413853 creator A5058484085 @default.
- W2990413853 creator A5064990496 @default.
- W2990413853 creator A5089481719 @default.
- W2990413853 creator A5090011403 @default.
- W2990413853 date "2020-02-01" @default.
- W2990413853 modified "2023-09-26" @default.
- W2990413853 title "Complementarity modeling of monthly streamflow and wind speed regimes based on a copula-entropy approach: A Brazilian case study" @default.
- W2990413853 cites W1487371587 @default.
- W2990413853 cites W1529468743 @default.
- W2990413853 cites W1590831612 @default.
- W2990413853 cites W1657787756 @default.
- W2990413853 cites W1927414870 @default.
- W2990413853 cites W1966262860 @default.
- W2990413853 cites W1970079012 @default.
- W2990413853 cites W1982063384 @default.
- W2990413853 cites W1985409483 @default.
- W2990413853 cites W1992105816 @default.
- W2990413853 cites W1994403842 @default.
- W2990413853 cites W2018490621 @default.
- W2990413853 cites W2019363555 @default.
- W2990413853 cites W2022687097 @default.
- W2990413853 cites W2032558547 @default.
- W2990413853 cites W2039240409 @default.
- W2990413853 cites W2042108805 @default.
- W2990413853 cites W2044611926 @default.
- W2990413853 cites W2049626702 @default.
- W2990413853 cites W2051416171 @default.
- W2990413853 cites W2067849377 @default.
- W2990413853 cites W2069175076 @default.
- W2990413853 cites W2084117721 @default.
- W2990413853 cites W2090337025 @default.
- W2990413853 cites W2098280243 @default.
- W2990413853 cites W2098381731 @default.
- W2990413853 cites W2105225820 @default.
- W2990413853 cites W2108886061 @default.
- W2990413853 cites W2180258175 @default.
- W2990413853 cites W2508267557 @default.
- W2990413853 cites W2529748212 @default.
- W2990413853 cites W2571254282 @default.
- W2990413853 cites W2733822397 @default.
- W2990413853 cites W2779986582 @default.
- W2990413853 cites W2791133525 @default.
- W2990413853 cites W2800392602 @default.
- W2990413853 cites W2801497915 @default.
- W2990413853 cites W2889921610 @default.
- W2990413853 cites W2904686902 @default.
- W2990413853 cites W2907486534 @default.
- W2990413853 cites W2993383518 @default.
- W2990413853 cites W4252028749 @default.
- W2990413853 cites W4300527566 @default.
- W2990413853 doi "https://doi.org/10.1016/j.apenergy.2019.114127" @default.
- W2990413853 hasPublicationYear "2020" @default.
- W2990413853 type Work @default.
- W2990413853 sameAs 2990413853 @default.
- W2990413853 citedByCount "13" @default.
- W2990413853 countsByYear W29904138532020 @default.
- W2990413853 countsByYear W29904138532021 @default.
- W2990413853 countsByYear W29904138532022 @default.
- W2990413853 countsByYear W29904138532023 @default.
- W2990413853 crossrefType "journal-article" @default.
- W2990413853 hasAuthorship W2990413853A5011773427 @default.
- W2990413853 hasAuthorship W2990413853A5032656130 @default.
- W2990413853 hasAuthorship W2990413853A5035879803 @default.
- W2990413853 hasAuthorship W2990413853A5058484085 @default.
- W2990413853 hasAuthorship W2990413853A5064990496 @default.
- W2990413853 hasAuthorship W2990413853A5089481719 @default.
- W2990413853 hasAuthorship W2990413853A5090011403 @default.
- W2990413853 hasConcept C106301342 @default.
- W2990413853 hasConcept C119599485 @default.
- W2990413853 hasConcept C121332964 @default.
- W2990413853 hasConcept C126645576 @default.
- W2990413853 hasConcept C127413603 @default.
- W2990413853 hasConcept C149782125 @default.
- W2990413853 hasConcept C153294291 @default.
- W2990413853 hasConcept C161067210 @default.
- W2990413853 hasConcept C163258240 @default.
- W2990413853 hasConcept C17618745 @default.
- W2990413853 hasConcept C188573790 @default.
- W2990413853 hasConcept C205649164 @default.
- W2990413853 hasConcept C33923547 @default.
- W2990413853 hasConcept C39432304 @default.
- W2990413853 hasConcept C40675005 @default.
- W2990413853 hasConcept C41008148 @default.
- W2990413853 hasConcept C53739315 @default.
- W2990413853 hasConcept C58640448 @default.
- W2990413853 hasConcept C62520636 @default.
- W2990413853 hasConcept C78600449 @default.
- W2990413853 hasConcept C89227174 @default.
- W2990413853 hasConceptScore W2990413853C106301342 @default.
- W2990413853 hasConceptScore W2990413853C119599485 @default.
- W2990413853 hasConceptScore W2990413853C121332964 @default.
- W2990413853 hasConceptScore W2990413853C126645576 @default.
- W2990413853 hasConceptScore W2990413853C127413603 @default.