FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3175835633> ?p ?o ?g. }

• W3175835633 endingPage "818" @default.
• W3175835633 startingPage "811" @default.
• W3175835633 abstract "The increasing penetration of renewable energy sources has introduced great uncertainties and challenges into computation and analysis of electric power systems. To deal with uncertainties, probabilistic approaches need to be used. In this paper, we propose a new framework for probabilistic assessment of power systems taking into account uncertainties from input random variables such as load demands and renewable energy sources. It is based on the cumulant-based Probabilistic Power Flow (PPF) in combination with an improved clustering technique. The improved clustering technique is also developed in this study by making use of Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO) to reduce the range of variation in the input data, thus increasing the accuracy of the traditional cumulant-based PPF (TCPPF) method. In addition, thanks to adopting PCA for dimensionality reduction, the improved clustering technique can be effectively dealt with a large number of input random variables so that the proposed framework for probabilistic assessment can be applied for large power systems. The IEEE-118 bus test system is modified by adding five wind and eight solar photovoltaic power plants to examine the proposed method. Uncertainties from input random variables are represented by appropriate probabilistic models. Extensive testing on the test system indicates good performance of the proposed approach in comparison to the traditional cumulant-based PPF and Monte Carlo simulation. The IEEE-118 bus test system is modified by adding five wind and eight solar photovoltaic power plants to examine the proposed method. Extensive testing on the test system, using Matlab (R2015a) on an Intel Core i5 CPU 2.53 GHz/4.00 GB RAM PC, indicates good performance of the proposed approach (PPPF) in comparison to the TCPPF and Monte Carlo simulation (MCS): In terms of computation time, PPPF needs 4.54 seconds, while TCPPF and MCS require 2.63 and 251 seconds, respectively; ARMS errors are calculated for methods using benchmark MCS and their values clearly demonstrate the higher accuracy of PPPF in estimating probability distributions compared to TCPPF, i.e., the maximum (Max) and mean (Mean) values of ARMS errors of all output random variables are: ARMSPPPFmax = 0.11%, ARMSTCPPFmax = 0.55%, and ARMSPPPFmean = 0.06%, ARMSTCPPFmean = 0.35%." @default.
• W3175835633 created "2021-07-05" @default.
• W3175835633 creator A5046217912 @default.
• W3175835633 creator A5050792409 @default.
• W3175835633 creator A5053278929 @default.
• W3175835633 creator A5071010503 @default.
• W3175835633 date "2021-06-25" @default.
• W3175835633 modified "2023-09-27" @default.
• W3175835633 title "Probabilistic Assessment of Power Systems with Renewable Energy Sources based on an Improved Analytical Approach" @default.
• W3175835633 cites W1585002319 @default.
• W3175835633 cites W1882445960 @default.
• W3175835633 cites W1905830942 @default.
• W3175835633 cites W1973294042 @default.
• W3175835633 cites W1999075329 @default.
• W3175835633 cites W2004560847 @default.
• W3175835633 cites W2008765185 @default.
• W3175835633 cites W2034054792 @default.
• W3175835633 cites W2039895419 @default.
• W3175835633 cites W2040970088 @default.
• W3175835633 cites W2049006797 @default.
• W3175835633 cites W2061948033 @default.
• W3175835633 cites W2069722134 @default.
• W3175835633 cites W2084349814 @default.
• W3175835633 cites W2084769660 @default.
• W3175835633 cites W2115736354 @default.
• W3175835633 cites W2134917918 @default.
• W3175835633 cites W2157410673 @default.
• W3175835633 cites W2327178873 @default.
• W3175835633 cites W2512307705 @default.
• W3175835633 cites W2765339681 @default.
• W3175835633 cites W2889691632 @default.
• W3175835633 cites W2920501566 @default.
• W3175835633 cites W2922709255 @default.
• W3175835633 cites W3007777525 @default.
• W3175835633 doi "https://doi.org/10.14710/ijred.2021.38226" @default.
• W3175835633 hasPublicationYear "2021" @default.
• W3175835633 type Work @default.
• W3175835633 sameAs 3175835633 @default.
• W3175835633 citedByCount "1" @default.
• W3175835633 countsByYear W31758356332023 @default.
• W3175835633 crossrefType "journal-article" @default.
• W3175835633 hasAuthorship W3175835633A5046217912 @default.
• W3175835633 hasAuthorship W3175835633A5050792409 @default.
• W3175835633 hasAuthorship W3175835633A5053278929 @default.
• W3175835633 hasAuthorship W3175835633A5071010503 @default.
• W3175835633 hasConcept C105795698 @default.
• W3175835633 hasConcept C119599485 @default.
• W3175835633 hasConcept C119857082 @default.
• W3175835633 hasConcept C121332964 @default.
• W3175835633 hasConcept C126255220 @default.
• W3175835633 hasConcept C127413603 @default.
• W3175835633 hasConcept C154945302 @default.
• W3175835633 hasConcept C163258240 @default.
• W3175835633 hasConcept C188573790 @default.
• W3175835633 hasConcept C19499675 @default.
• W3175835633 hasConcept C200601418 @default.
• W3175835633 hasConcept C27438332 @default.
• W3175835633 hasConcept C33923547 @default.
• W3175835633 hasConcept C41008148 @default.
• W3175835633 hasConcept C41291067 @default.
• W3175835633 hasConcept C49937458 @default.
• W3175835633 hasConcept C62520636 @default.
• W3175835633 hasConcept C70518039 @default.
• W3175835633 hasConcept C73555534 @default.
• W3175835633 hasConcept C78600449 @default.
• W3175835633 hasConcept C89227174 @default.
• W3175835633 hasConceptScore W3175835633C105795698 @default.
• W3175835633 hasConceptScore W3175835633C119599485 @default.
• W3175835633 hasConceptScore W3175835633C119857082 @default.
• W3175835633 hasConceptScore W3175835633C121332964 @default.
• W3175835633 hasConceptScore W3175835633C126255220 @default.
• W3175835633 hasConceptScore W3175835633C127413603 @default.
• W3175835633 hasConceptScore W3175835633C154945302 @default.
• W3175835633 hasConceptScore W3175835633C163258240 @default.
• W3175835633 hasConceptScore W3175835633C188573790 @default.
• W3175835633 hasConceptScore W3175835633C19499675 @default.
• W3175835633 hasConceptScore W3175835633C200601418 @default.
• W3175835633 hasConceptScore W3175835633C27438332 @default.
• W3175835633 hasConceptScore W3175835633C33923547 @default.
• W3175835633 hasConceptScore W3175835633C41008148 @default.
• W3175835633 hasConceptScore W3175835633C41291067 @default.
• W3175835633 hasConceptScore W3175835633C49937458 @default.
• W3175835633 hasConceptScore W3175835633C62520636 @default.
• W3175835633 hasConceptScore W3175835633C70518039 @default.
• W3175835633 hasConceptScore W3175835633C73555534 @default.
• W3175835633 hasConceptScore W3175835633C78600449 @default.
• W3175835633 hasConceptScore W3175835633C89227174 @default.
• W3175835633 hasIssue "4" @default.
• W3175835633 hasLocation W31758356331 @default.
• W3175835633 hasOpenAccess W3175835633 @default.
• W3175835633 hasPrimaryLocation W31758356331 @default.
• W3175835633 hasRelatedWork W1964158745 @default.
• W3175835633 hasRelatedWork W2091172698 @default.
• W3175835633 hasRelatedWork W2099242680 @default.
• W3175835633 hasRelatedWork W2164993107 @default.
• W3175835633 hasRelatedWork W2269254511 @default.
• W3175835633 hasRelatedWork W2972414525 @default.
• W3175835633 hasRelatedWork W3017823056 @default.

• next