Algebraic and Parametric Solvers for the Power Flow Problem: Towards Real-Time and Accuracy-Guaranteed Simulation of Electric Systems
The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction me...
Uložené v:
| Vydané v: | Archives of computational methods in engineering Ročník 25; číslo 4; s. 1003 - 1026 |
|---|---|
| Hlavní autori: | , , , |
| Médium: | Journal Article Publikácia |
| Jazyk: | English |
| Vydavateľské údaje: |
Dordrecht
Springer Netherlands
01.11.2018
Springer Nature B.V Springer Verlag |
| Predmet: | |
| ISSN: | 1134-3060, 1886-1784 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction method to the power flow problem is also detailed. This results in a family of iterative solvers that combined with Proper Generalized Decomposition technique allows to solve the parametric version of the equations. Once the solution is computed using this strategy, analyzing the network state or solving optimization problems, with inclusion of generation in real-time, becomes a straightforward procedure since the parametric solution is available. Complementing this approach, an error strategy is implemented at each step of the iterative solver. Thus, error indicators are used as an stopping criteria controlling the accuracy of the approximation during the construction process. The application of these methods to the model IEEE 57-bus network is taken as a numerical illustration. |
|---|---|
| AbstractList | The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction method to the power flow problem is also detailed. This results in a family of iterative solvers that combined with Proper Generalized Decomposition technique allows to solve the parametric version of the equations. Once the solution is computed using this strategy, analyzing the network state or solving optimization problems, with inclusion of generation in real-time, becomes a straightforward procedure since the parametric solution is available. Complementing this approach, an error strategy is implemented at each step of the iterative solver. Thus, error indicators are used as an stopping criteria controlling the accuracy of the approximation during the construction process. The application of these methods to the model IEEE 57-bus network is taken as a numerical illustration. The final publication is available at Springer via http://dx.doi.org/10.1007/s11831-017-9223-6 The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of those solvers for the power flow equations, in both algebraic and parametric version. The application of the Alternating Search Direction method to the power flow problem is also detailed. This results in a family of iterative solvers that combined with Proper Generalized Decomposition technique allows to solve the parametric version of the equations. Once the solution is computed using this strategy, analyzing the network state or solving optimization problems, with inclusion of generation in real-time, becomes a straightforward procedure since the parametric solution is available. Complementing this approach, an error strategy is implemented at each step of the iterative solver. Thus, error indicators are used as an stopping criteria controlling the accuracy of the approximation during the construction process. The application of these methods to the model IEEE 57-bus network is taken as a numerical illustration. Peer Reviewed |
| Author | Borzacchiello, Domenico Chinesta, Francisco Díez, Pedro García-Blanco, Raquel |
| Author_xml | – sequence: 1 givenname: Raquel surname: García-Blanco fullname: García-Blanco, Raquel organization: Universidad Politécnica de Cataluña (LaCàN) – sequence: 2 givenname: Pedro orcidid: 0000-0001-6464-6407 surname: Díez fullname: Díez, Pedro email: pedro.diez@upc.edu organization: Universidad Politécnica de Cataluña (LaCàN) – sequence: 3 givenname: Domenico surname: Borzacchiello fullname: Borzacchiello, Domenico organization: Ecole Central de Nantes (ICI) – sequence: 4 givenname: Francisco surname: Chinesta fullname: Chinesta, Francisco organization: Ecole Central de Nantes (ICI) |
| BackLink | https://hal.science/hal-04098457$$DView record in HAL |
| BookMark | eNp9kc1u1DAUhS1UJNrCA7CzxIqFwT-J7bAbVf1BGokRHdaW49y0qZy42E5H8wC8N54JKggJFpZ9rfude-xzhk6mMAFCbxn9wChVHxNjWjBCmSIN54LIF-iUaS0JU7o6KWcmKiKopK_QWUoPlNZV0_BT9GPl76CNdnDYTh3e2GhHyLGUt8E_QUy4DxHne8CbsIOIr3zY4U0MrYfxE96GnY1dwl_BerIdRjiKrJybo3V7cj0XuSkDdPh2GGdv8xAmHHp86cEtQ_Ypw5heo5e99Qne_NrP0bery-3FDVl_uf58sVoTV4k6E2VrzQXQtmVWAFesba3sFFW9FI0WXes4dyCkbLTlsump0FqpuqstZxJaKs7R-0X33nrzGIfRxr0JdjA3q7U53NGKNrqq1RMrvWzpdWl2JoKD6Gw-dj8Xh8Wp4oY3TDBVmHcL8xjD9xlSNg9hjlN5kuGMV7RSxdYfyjGkFKF_tsKoOaRpljRNSdMc0jSyMOovxg35-J-5hOf_S_KFTGXKdAfxt6d_Qz8BSgW04w |
| CitedBy_id | crossref_primary_10_1007_s11831_019_09378_0 crossref_primary_10_1016_j_finel_2021_103530 crossref_primary_10_1016_j_ijepes_2025_110602 crossref_primary_10_1007_s11831_020_09424_2 |
| Cites_doi | 10.1109/ISCAS.2014.6865508 10.1049/piee.1964.0259 10.1137/090766498 10.1016/S0142-0615(01)00067-9 10.1049/iet-gtd.2012.0269 10.1615/Int.J.UncertaintyQuantification.2013003479 10.1016/S0142-0615(01)00022-9 10.1109/T-PAS.1975.31855 10.1109/TPAS.1963.291392 10.1007/978-1-4612-1432-8 10.1109/ICEC.1998.700121 10.1109/TPWRS.2009.2016589 10.1016/j.cma.2010.02.012 10.1109/TPAS.1974.293985 10.1109/TPAS.1968.292150 10.1007/s11831-013-9080-x 10.1109/TPAS.1981.317018 10.1109/HICSS.2000.926773 10.1049/ip-gtd:19981980 10.1109/CDC.1990.203339 10.1109/TPWRS.2005.857921 10.1002/nme.2746 10.1090/qam/910462 10.1109/PESGM.2015.7286047 10.1109/APPEEC.2011.5748520 10.1109/TCSI.2015.2512723 10.1109/PESS.2002.1043458 10.1109/T-PAS.1977.32323 10.1016/j.epsr.2016.06.021 10.1109/59.867133 10.1016/j.cma.2012.03.016 10.1109/PESGM.2012.6345040 10.1049/piee.1974.0145 10.1201/9781420007275 10.1109/59.99396 10.1016/j.jcp.2003.08.010 10.1109/59.331463 10.1109/TPWRS.2007.894861 10.1049/iet-gtd.2015.0998 10.1109/TPAS.1981.316511 10.1109/TDC.2010.5484211 10.1145/2024724.2024850 10.1109/PES.2003.1270485 10.1109/TPAS.1984.318284 10.1109/TPWRS.2011.2165860 10.1016/S0142-0615(00)00002-8 10.1016/j.ijepes.2006.02.013 10.1615/IntJMultCompEng.v9.i1.30 10.1109/TPWRS.2012.2237043 10.1049/pi-a.1962.0078 10.1109/CDC.2015.7402990 10.1049/iet-gtd:20060310 10.1049/iet-rpg.2009.0011 10.1109/PESGM.2012.6344759 10.1109/TPAS.1968.292196 10.1016/0142-0615(90)90028-A 10.1109/ANDESCON.2010.5633415 10.1049/piee.1977.0027 10.1109/PSCE.2009.4840149 10.1016/j.cma.2014.09.025 10.1109/PES.2009.5275534 10.1109/TPWRS.2009.2036018 10.1109/POWERCON.2014.6993521 10.1109/TPAS.1967.291823 10.1109/SGE.2012.6463955 10.1007/978-3-642-22453-9_45 10.1109/59.476074 10.1109/TPWRS.2006.876696 10.1109/MPER.1982.5519878 10.1049/iet-gtd.2015.0822 10.1109/ENERGYCON.2016.7514119 10.1007/s11831-010-9049-y 10.1109/28.8993 10.1109/TPAS.1974.293973 10.1109/PROC.1974.9544 10.1049/piee.1971.0197 10.1049/ip-gtd:20020172 10.1109/NAPS.2013.6666940 10.1109/PESW.2001.916995 10.1109/CCECE.2005.1557013 10.1049/iet-gtd.2015.0679 10.1109/T-PAS.1977.32334 10.1109/TPWRS.2013.2252631 10.1109/AIEEPAS.1956.4499318 10.1007/s11831-011-9064-7 10.1049/pi-a.1961.0077 10.1137/120899042 10.1007/s12667-012-0056-y 10.1109/TPWRS.2003.818743 10.1109/59.76723 10.1109/ICECE.2014.7026900 10.1109/PESS.2000.868774 10.1016/j.crma.2004.08.006 10.1109/67.560872 10.1002/nme.5470 10.1109/TSTE.2016.2530049 |
| ContentType | Journal Article Publication |
| Contributor | Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental Universitat Politècnica de Catalunya. LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria |
| Contributor_xml | – sequence: 1 fullname: Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental – sequence: 2 fullname: Universitat Politècnica de Catalunya. LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria |
| Copyright | CIMNE, Barcelona, Spain 2017 Archives of Computational Methods in Engineering is a copyright of Springer, (2017). All Rights Reserved. info:eu-repo/semantics/openAccess Distributed under a Creative Commons Attribution 4.0 International License |
| Copyright_xml | – notice: CIMNE, Barcelona, Spain 2017 – notice: Archives of Computational Methods in Engineering is a copyright of Springer, (2017). All Rights Reserved. – notice: info:eu-repo/semantics/openAccess – notice: Distributed under a Creative Commons Attribution 4.0 International License |
| DBID | AAYXX CITATION 3V. 7WY 7WZ 7XB 87Z 8AL 8FE 8FG 8FK 8FL ABJCF ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L6V M0C M0N M7S P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYYUZ Q9U XX2 1XC VOOES |
| DOI | 10.1007/s11831-017-9223-6 |
| DatabaseName | CrossRef ProQuest Central (Corporate) ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One ProQuest Central Korea Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database (ProQuest) ABI/INFORM Professional Advanced ProQuest Engineering Collection ABI/INFORM Global Computing Database Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest One Academic ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Business ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering collection ABI/INFORM Collection China ProQuest Central Basic Recercat Hyper Article en Ligne (HAL) Hyper Article en Ligne (HAL) (Open Access) |
| DatabaseTitle | CrossRef ABI/INFORM Global (Corporate) ProQuest Business Collection (Alumni Edition) ProQuest One Business Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ABI/INFORM Complete ProQuest Central ABI/INFORM Professional Advanced ProQuest One Applied & Life Sciences ProQuest Engineering Collection ProQuest Central Korea ProQuest Central (New) ABI/INFORM Complete (Alumni Edition) Engineering Collection Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global ProQuest Computing Engineering Database ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ABI/INFORM China ProQuest Technology Collection ProQuest SciTech Collection ProQuest Business Collection Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition Materials Science & Engineering Collection ProQuest One Business (Alumni) ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New) Business Premium Collection (Alumni) |
| DatabaseTitleList | ABI/INFORM Global (Corporate) |
| Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Engineering |
| EISSN | 1886-1784 |
| EndPage | 1026 |
| ExternalDocumentID | oai:HAL:hal-04098457v1 oai_recercat_cat_2072_291317 10_1007_s11831_017_9223_6 |
| GrantInformation_xml | – fundername: Ministerio de Economía y Competitividad grantid: DPI2014-51844-C2-2-R funderid: http://dx.doi.org/10.13039/501100003329 |
| GroupedDBID | -5B -5G -BR -EM -Y2 -~C -~X .4S .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 203 23M 28- 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2VQ 2~H 30V 3V. 4.4 406 408 40D 40E 5GY 5VS 67Z 6NX 7WY 8FE 8FG 8FL 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABDZT ABECU ABFTV ABHQN ABJCF ABJNI ABJOX ABKCH ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACZOJ ADHHG ADHIR ADINQ ADKNI ADKPE ADMLS ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARCEE ARCSS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ CAG CCPQU COF CS3 CSCUP DDRTE DNIVK DPUIP DWQXO EBLON EBS EDO EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GROUPED_ABI_INFORM_COMPLETE H13 HCIFZ HF~ HG5 HG6 HMJXF HRMNR HVGLF HZ~ I-F IJ- IKXTQ IWAJR IXC IXD IXE IZQ I~X I~Z J-C J0Z JBSCW K60 K6V K6~ K7- KDC KOV L6V LLZTM M0C M0N M4Y M7S MA- MK~ N2Q NB0 NDZJH NF0 NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM P19 P2P P62 P9P PF0 PQBIZ PQBZA PQQKQ PROAC PT4 PT5 PTHSS QOK QOS R4E R89 R9I RHV RNI RNS ROL RPX RSV RZK S16 S1Z S26 S27 S28 S3B SAP SCLPG SCV SDH SDM SEG SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TSG TSK TSV TUC TUS U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W48 WK8 YLTOR Z45 Z5O Z7R Z7X Z7Y Z7Z Z83 Z88 ZMTXR _50 ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION JZLTJ PHGZM PHGZT PQGLB 7XB 8AL 8FK JQ2 L.- PKEHL PQEST PQUKI PRINS PUEGO Q9U XX2 1XC VOOES |
| ID | FETCH-LOGICAL-c435t-7a5823e0bb1a3e271bba6d707f63983dbc22ce36698a269f0388775d5a216eb03 |
| IEDL.DBID | K7- |
| ISICitedReferencesCount | 4 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000447992300006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1134-3060 |
| IngestDate | Sat Nov 29 15:03:55 EST 2025 Fri Nov 07 13:40:40 EST 2025 Wed Sep 17 23:55:49 EDT 2025 Sat Nov 29 06:21:44 EST 2025 Tue Nov 18 21:57:24 EST 2025 Fri Feb 21 02:32:01 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Distributed generation Reduced order model Power flow problem Optimization Accuracy control |
| Language | English |
| License | Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c435t-7a5823e0bb1a3e271bba6d707f63983dbc22ce36698a269f0388775d5a216eb03 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0001-6464-6407 |
| OpenAccessLink | https://hal.science/hal-04098457 |
| PQID | 2124047269 |
| PQPubID | 1486352 |
| PageCount | 24 |
| ParticipantIDs | hal_primary_oai_HAL_hal_04098457v1 csuc_recercat_oai_recercat_cat_2072_291317 proquest_journals_2124047269 crossref_primary_10_1007_s11831_017_9223_6 crossref_citationtrail_10_1007_s11831_017_9223_6 springer_journals_10_1007_s11831_017_9223_6 |
| PublicationCentury | 2000 |
| PublicationDate | 20181100 2018-11-00 20181101 2018-11 |
| PublicationDateYYYYMMDD | 2018-11-01 |
| PublicationDate_xml | – month: 11 year: 2018 text: 20181100 |
| PublicationDecade | 2010 |
| PublicationPlace | Dordrecht |
| PublicationPlace_xml | – name: Dordrecht |
| PublicationSubtitle | State of the Art Reviews |
| PublicationTitle | Archives of computational methods in engineering |
| PublicationTitleAbbrev | Arch Computat Methods Eng |
| PublicationYear | 2018 |
| Publisher | Springer Netherlands Springer Nature B.V Springer Verlag |
| Publisher_xml | – name: Springer Netherlands – name: Springer Nature B.V – name: Springer Verlag |
| References | Zhu J, Abur A (2006) Identification of errors in power flow controller parameters. In: International Conference on probabilistic methods applied to power systems, 2006. PMAPS 2006, pp 1–6 AtwaYEl-SaadanyEProbabilistic approach for optimal allocation of wind-based distributed generation in distribution systemsRenew Power Generat IET201151798810.1049/iet-rpg.2009.0011 Borkowska B (1974) Probabilistic load flow. IEEE transactions on power apparatus and systems, vol PAS-93, No. 3, pp 752–759 Willis HL (2000) Analytical methods and rules of thumb for modeling dg-distribution interaction. In: Power engineering society summer meeting, 2000. IEEE, vol 3, pp 1643–1644 Kim KH, Lee YJ, Rhee SB, Lee SK, You SK (2002) Dispersed generator placement using fuzzy-ga in distribution systems. In: Power engineering society summer meeting, 2002 IEEE, vol 3, pp 1148–1153 Chaturantabut S, Sorensen D (2009) Application of POD and DEIM on dimension reduction of non-linear miscible viscous fingering in porous media. Math Comput Model Dyn Syst DerakhshandehSYPourbagherRApplication of high-order Newton-like methods to solve power flow equationsIET Gener Trans Distrib20161081853185910.1049/iet-gtd.2015.0998 RouhaniMMohammadiMKargarianAParzen window density estimator-based probabilistic power flow with correlated uncertaintiesIEEE Trans Sustain Energy2016731170118110.1109/TSTE.2016.2530049 BrownRodney J.TinneyWilliam F.Digital Solutions for Large Power NetworksTransactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems1957763347351 He J, Zhou B, Zhang Q, Zhao Y, Liu J (2012) An improved power flow algorithm for distribution networks based on Z-bus algorithm and forward/backward sweep method. In: 2012 international conference on control engineering and communication technology (ICCECT), pp 1–4 ChinestaFAmmarACuetoERecent advances and new challenges in the use of the proper generalized decomposition for solving multidimensional modelsArch Comput Methods Eng2010174327350273994210.1007/s11831-010-9049-y YangNien-CheThree-phase power flow calculations using direct Z BUS method for large-scale unbalanced distribution networksIET Generation, Transmission & Distribution20161041048105510.1049/iet-gtd.2015.0822 Ward JB, Hale HW (1956) Digital computer solution of power-flow problems [includes discussion]. Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems, vol 75, No. 3 SachdevMSMedicherlaTKPA second order load flow techniqueIEEE Trans Power Appar Syst197796118919710.1109/T-PAS.1977.32323 Zhao TQ, Chiang HD, Koyanagi K (2016) Convergence analysis of implicit Z-bus power flow method for general distribution networks with distributed generators. IET generation, transmission distribution, vol 10, No. 2, pp 412–420 Kabir S, Chowdhury A, Rahman M, Alam J (2014) Inclusion of slack bus in Newton Raphson load flow study. 2014 International conference on electrical and computer engineering (ICECE), Dhaka, pp 282–284 StottB.Effective starting process for Newton-Raphson load flowsProceedings of the Institution of Electrical Engineers1971118898310.1049/piee.1971.0197 BorzacchielloDMalikMChinestaFGarcía-BlancoRDiezPUnified formulation of a family of iterative solvers for power systems analysisElectr Power Syst Res201614020120810.1016/j.epsr.2016.06.021 BarraultMMadayYNguyenNCPateraATAn empirical interpolation method: application to efficient reduced-basis discretization of partial differential equationsComptes Rendus Math20043399667672210320810.1016/j.crma.2004.08.006 ZhangHLiPApplication of sparse-grid technique to chance constrained optimal power flowGener Transm Distrib IET20137549149910.1049/iet-gtd.2012.0269 LadevèzePSimmondsJNonlinear computational structural mechanics: new approaches and non-incremental methods of calculation1999New YorkSpringer10.1007/978-1-4612-1432-8 ThorpJSNaqaviSALoad-flow fractals draw clues to erratic behaviourIEEE Comput Appl Power1997101596210.1109/67.560872 IdemaRPapaefthymiouGLahayeDVuikCvan der SluisLTowards faster solution of large power flow problemsIEEE Trans Power Syst20132844918492510.1109/TPWRS.2013.2252631 LinWMTengJHThree-phase distribution network fast-decoupled power flow solutionsInt J Electr Power Energy Syst200022537538010.1016/S0142-0615(00)00002-8 LinGElizondoMLuSWanXUncertainty quantification in dynamic simulations of large-scale power system models using the high-order probabilistic collocation method on sparse gridsInt J Uncertain Quantif201443185204325652010.1615/Int.J.UncertaintyQuantification.2013003479 Subramanian MK, Feng Y, Tylavsky D (2013) PV bus modeling in a holomorphically embedded power-flow formulation. North American Power Symposium (NAPS) 2013, pp 1–6 Ou TC, Lin WM (2009) A novel Z-matrix algorithm for distribution power flow solution. In: PowerTech, 2009 IEEE Bucharest, pp 1–8 SuCLProbabilistic load-flow computation using point estimate methodIEEE Trans Power Syst200520418431851212000810.1109/TPWRS.2005.857921 Rao S, Feng Y, Tylavsky DJ, Subramanian MK (2015) The holomorphic embedding method applied to the power-flow problem. IEEE Transactions on Power Systems PP, No. 99, pp 1–13 Chen P, Chen Z, Bak-Jensen B (2008) Probabilistic load flow: a review. In: Third international conference on electric utility deregulation and restructuring and power technologies, 2008. DRPT 2008, pp 1586–1591 Tang J, Ni F, Ponci F, Monti A (2015) Dimension-adaptive sparse grid interpolation for uncertainty quantification in modern power systems: probabilistic power flow. In: IEEE Transactions on power systems, PP, No. 99, pp 1–13 Wirtz D, Sorensen D, Haasdonk B (2014) A-posteriori error estimation for DEIM reduced nonlinear dynamical systems. SIAM J Sci Comput 1–31 Li Y, Luo Y, Zhang B, Mao C (2011) A modified Newton-Raphson power flow method considering wind power. In: Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific, pp 1–5 ChinestaF.LeygueA.BordeuF.AguadoJ. V.CuetoE.GonzalezD.AlfaroI.AmmarA.HuertaA.PGD-Based Computational Vademecum for Efficient Design, Optimization and ControlArchives of Computational Methods in Engineering20132013159302405810.1007/s11831-013-9080-x El-Khattam W, Hegazy YG, Salama MMA (2003) Stochastic power flow analysis of electrical distributed generation systems. In: Power engineering society general meeting, 2003, IEEE, vol 2, p 1144 AmmarAChinestaFDiezPHuertaAAn error estimator for separated representations of highly multidimensional modelsComput Methods Appl Mech Eng201019925–2818721880264528810.1016/j.cma.2010.02.012 Yong T, Lasseter RH (2000) Stochastic optimal power flow: formulation and solution. In: Power engineering society summer meeting, 2000. IEEE, vol 1, pp 237–242 ChengCFZA modified Newton method for radial distribution system power flow analysisIEEE Trans Power Syst1997121389397 Idema R, Lahaye D, Vuik K, van der Sluis L (2010) Fast Newton load flow. IEEE PES Transmission and Distribution, pp 1–7 XuWLiuYSalmonJLeTChangGSeries load flow: a novel noniterative load flow methodIEEE Proc Gener Transm Distrib1998145325125610.1049/ip-gtd:19981980 ZhangPLeeSTProbabilistic load flow computation using the method of combined cumulants and gram-charlier expansionIEEE Trans Power Syst200419167668210.1109/TPWRS.2003.818743 DopazoJFKlitinOASassonAMStochastic load flowsIEEE Trans Power Apparat Syst197594229930910.1109/T-PAS.1975.31855 Gómez-ExpósitoAConejoAJCañizaresCElectric energy systems: analysis and operation2008Boca RatonCRC Press10.1201/9781420007275 LambertTGilmanPLilienthalPMicropower system modeling with HOMER2006New YorkWiley ChinestaFLeygueABordeuFAguadoJVCuetoEGonzalezDAlfaroIAmmarAHuertaAPgd-based computational vademecum for efficient design, optimization and controlArch Comput Methods Eng20132013159302405810.1007/s11831-013-9080-x Hochman A, Bond BN, White JK (2011) A stabilized discrete empirical interpolation method for model reduction of electrical, thermal, and microelectromechanical systems. In: Proceedings of the 48th Design Automation Conference on - DAC ’11, ACM Press, New York, USA, p 540 TripathyS. C.PrasadG. DurgaMalikO. P.HopeG. S.Load-Flow Solutions for Ill-Conditioned Power Systems by a Newton-Like MethodIEEE Power Engineering Review1982PER-210252610.1109/MPER.1982.5519878 IwamotoS.TamuraY.A Load Flow Calculation Method for Ill-Conditioned Power SystemsIEEE Transactions on Power Apparatus and Systems1981PAS-10041736174310.1109/TPAS.1981.316511 de SouzaAJuniorCLima LopesILemeRCarpinteiroONon-iterative load-flow method as a tool for voltage stability studiesIET Gener Transm Distrib20071349950510.1049/iet-gtd:20060310 Bijwe PR, Abhijith B, Raju GKV (2009) Robust three phase fast decoupled power flow. In: Power systems conference and exposition, 2009. PSCE ’09. IEEE/PES, pp 1–5 Dommel H, Tinney W (1968) Optimal power flow solutions. IEEE transactions on power apparatus and systems, vol PAS-87, No. 10, pp 1866–1876 Chaturantabut S, Sorensen D (2009) Discrete empirical interpolation for nonlinear model reduction. In: Proceedings of the 48th IEEE Conference on decision and control, 2009 held jointly with the 2009 28th Chinese control conference. CDC/CCC 2009, pp 4316–4321 Taylor D, Treece J (1967) Load flow analysis by the Gauss-Seidel method. Symposium on power systems, load flow analysis. University of Manchester Institute of Science and Technology, Manchester, UK ShareefSDMKumarTVA review on models and methods for optimal placement of distributed generation in power distribution systemInt J Educ Appl Res20144161169 Mithulananthan N, Oo T, Phu LV (2004) Distributed generator in power distribution placement system using genetic algorithm to reduce losses. Thammasat Int J Sci Technol 9(3) SirovichLTurbulence and the dynamics of coherent structuresI–III. Quart Appl Math19874556159091046210.1090/qam/910462 ChaturantabutSSorensenDNonlinear model reduction via discrete empirical interpolationSIAM J Sci Comput201032527372764268473510.1137/090766498 SchafferMDTylavskyDJA nondiverging polar-form Newton-based power flowIEEE 9223_CR74 CFZ Cheng (9223_CR25) 1997; 12 9223_CR77 9223_CR79 A Trias (9223_CR60) 2016; 63 P Georgilakis (9223_CR91) 2013; 28 F Chinesta (9223_CR127) 2013; 20 SDM Shareef (9223_CR92) 2014; 4 WM Lin (9223_CR44) 2000; 22 9223_CR71 9223_CR84 W Xu (9223_CR55) 1998; 145 S Frank (9223_CR109) 2012; 3 T Lambert (9223_CR131) 2006 9223_CR89 MD Schaffer (9223_CR50) 1988; 24 N Acharya (9223_CR98) 2006; 28 9223_CR80 9223_CR101 9223_CR102 9223_CR82 S Chaturantabut (9223_CR72) 2010; 32 9223_CR83 9223_CR100 JH Teng (9223_CR30) 2002; 24 9223_CR95 OI Elgerd (9223_CR3) 1972 9223_CR96 9223_CR106 M Hinze (9223_CR117) 2012 9223_CR97 9223_CR103 9223_CR10 9223_CR104 9223_CR11 9223_CR12 9223_CR13 9223_CR14 9223_CR15 9223_CR16 9223_CR17 9223_CR18 9223_CR19 G Lin (9223_CR119) 2014; 4 CL Su (9223_CR86) 2005; 20 M Abido (9223_CR107) 2002; 24 D Galbally (9223_CR70) 2010; 81 M Rouhani (9223_CR68) 2016; 7 9223_CR90 9223_CR113 9223_CR93 9223_CR110 9223_CR111 9223_CR116 9223_CR9 9223_CR20 9223_CR114 9223_CR8 9223_CR21 M Barrault (9223_CR73) 2004; 339 9223_CR7 9223_CR22 9223_CR6 9223_CR23 P Garcia (9223_CR26) 2000; 15 9223_CR5 9223_CR24 E Florentin (9223_CR78) 2012; 225–228 9223_CR118 9223_CR4 NS Rau (9223_CR99) 1994; 9 9223_CR27 9223_CR28 JB Ward (9223_CR115) 1949; 68 9223_CR123 A Souza de (9223_CR56) 2007; 1 9223_CR121 9223_CR122 9223_CR128 9223_CR31 9223_CR32 R Idema (9223_CR38) 2013; 28 9223_CR129 9223_CR36 F Leon De (9223_CR40) 2002; 149 D Knoll (9223_CR39) 2004; 193 H Yu (9223_CR88) 2009; 24 9223_CR130 9223_CR1 Z Yi-Shan (9223_CR35) 2010; 25 9223_CR42 9223_CR45 9223_CR46 9223_CR48 9223_CR49 A Gómez-Expósito (9223_CR34) 2008 Y Chen (9223_CR41) 2006; 21 MS Sachdev (9223_CR57) 1977; 96 B Stott (9223_CR33) 1974; 62 JS Thorp (9223_CR52) 1997; 10 Y Atwa (9223_CR94) 2011; 5 P Ladevèze (9223_CR63) 1999 SY Derakhshandeh (9223_CR29) 2016; 10 9223_CR51 9223_CR53 9223_CR54 H Zhang (9223_CR120) 2013; 7 F Chinesta (9223_CR125) 2011; 18 9223_CR58 9223_CR59 P Zhang (9223_CR85) 2004; 19 R Idema (9223_CR37) 2012; 27 A Ammar (9223_CR75) 2011; 9 L Sirovich (9223_CR112) 1987; 45 RD Zimmerman (9223_CR43) 1995; 10 S Favuzza (9223_CR105) 2007; 22 D Borzacchiello (9223_CR64) 2016; 140 9223_CR62 F Chinesta (9223_CR126) 2010; 17 9223_CR65 9223_CR67 9223_CR69 A Monticelli (9223_CR47) 1990; 5 J Chen (9223_CR66) 2012; 7 M Huneault (9223_CR108) 1991; 6 GW Stagg (9223_CR2) 1968 A Ammar (9223_CR76) 2010; 199 N Rau (9223_CR87) 1990; 12 F Chinesta (9223_CR124) 2005; 8 9223_CR61 JF Dopazo (9223_CR81) 1975; 94 |
| References_xml | – reference: SachdevMSMedicherlaTKPA second order load flow techniqueIEEE Trans Power Appar Syst197796118919710.1109/T-PAS.1977.32323 – reference: IdemaRLahayeDJVuikCVan der SluisLScalable Newton-Krylov solver for very large power flow problemsIEEE Trans Power Syst201227139039610.1109/TPWRS.2011.2165860 – reference: Fang S, Cheng H, Xu G, Yao L, Zeng P (2014) A stochastic power flow method based on polynomial normal transformation and quasi monte carlo simulation. In: 2014 international conference on power system technology (POWERCON), pp 75–82 – reference: ChenYShenCA Jacobian-free Newton-GMRES (m) method with adaptive preconditioner and its application for power flow calculationsIEEE Trans Power Syst20062131096110310.1109/TPWRS.2006.876696 – reference: StottBReview of load-flow calculation methodsProc IEEE197462791692910.1109/PROC.1974.9544 – reference: Rios R, Espinosa J, Mejı’a C (2010) A multi-dimensional residual functional for obtaining the proper orthogonal decomposition coefficients in model reduction. In: ANDESCON, 2010 IEEE – reference: XuWLiuYSalmonJLeTChangGSeries load flow: a novel noniterative load flow methodIEEE Proc Gener Transm Distrib1998145325125610.1049/ip-gtd:19981980 – reference: ChinestaFLeygueABordeuFAguadoJVCuetoEGonzalezDAlfaroIAmmarAHuertaAPgd-based computational vademecum for efficient design, optimization and controlArch Comput Methods Eng20132013159302405810.1007/s11831-013-9080-x – reference: ChenJLiaoYState estimation and power flow analysis of power systemsJ Comput201273685 – reference: FlorentinEDíezPAdaptive reduced basis strategy based on goal oriented error assessment for stochastic problemsComput Methods Appl Mech Eng2012225–228116127291750010.1016/j.cma.2012.03.016 – reference: RauNSWanYHOptimum location of resources in distributed planningIEEE Trans Power Syst1994942014202010.1109/59.331463 – reference: AmmarAChinestaFDiezPHuertaAAn error estimator for separated representations of highly multidimensional modelsComput Methods Appl Mech Eng201019925–2818721880264528810.1016/j.cma.2010.02.012 – reference: Parrilo P, Lall S, Paganini F, Verghese GC, Lesieutre B, Marsden J (1999) Model reduction for analysis of cascading failures in power systems. In: Proceedings of the American control conference, 1999, vol 6, pp 4208–4212 – reference: Power systems test case archive [resources]. http://www2.ee.washington.edu/research/pstca/ – reference: SunDavidAshleyBruceBrewerBrianHughesArtTinneyWilliamOptimal Power Flow By Newton ApproachIEEE Transactions on Power Apparatus and Systems1984PAS-103102864288010.1109/TPAS.1984.318284 – reference: LinGElizondoMLuSWanXUncertainty quantification in dynamic simulations of large-scale power system models using the high-order probabilistic collocation method on sparse gridsInt J Uncertain Quantif201443185204325652010.1615/Int.J.UncertaintyQuantification.2013003479 – reference: LinWMTengJHThree-phase distribution network fast-decoupled power flow solutionsInt J Electr Power Energy Syst200022537538010.1016/S0142-0615(00)00002-8 – reference: YuHChungCYWongKPLeeHWZhangJHProbabilistic load flow evaluation with hybrid latin hypercube sampling and cholesky decompositionIEEE Trans Power Syst200924266166710.1109/TPWRS.2009.2016589 – reference: Mozolevski I, Prudhomme S (2015) Goal-oriented error estimation based on equilibrated-flux reconstruction for finite element approximations of elliptic problems. Comput Methods Appl Mech Eng 288:127–145. Error Estimation and adaptivity for nonlinear and time-dependent problems – reference: Dommel H, Tinney W (1968) Optimal power flow solutions. IEEE transactions on power apparatus and systems, vol PAS-87, No. 10, pp 1866–1876 – reference: Kim JO, Park SK, Park KW, Singh C (1998) Dispersed generation planning using improved hereford ranch algorithm. In: 1998 IEEE international conference on evolutionary computation proceedings. IEEE world congress on computational intelligence, pp 0–5 – reference: AtwaYEl-SaadanyEProbabilistic approach for optimal allocation of wind-based distributed generation in distribution systemsRenew Power Generat IET201151798810.1049/iet-rpg.2009.0011 – reference: BrownHomerCarterGordonHappHarveyPersonConradZ-Matrix Algorithms in Load-Flow ProgramsIEEE Transactions on Power Apparatus and Systems1968PAS-87380781410.1109/TPAS.1968.292196 – reference: ThorpJSNaqaviSALoad-flow fractals draw clues to erratic behaviourIEEE Comput Appl Power1997101596210.1109/67.560872 – reference: GarciaPPereiraJCarneiroSDa CostaVMMartinsNThree-phase power flow calculations using the current injection methodIEEE Trans Power Syst200015250851410.1109/59.867133 – reference: FavuzzaSGraditiGIppolitoMSanseverinoEOptimal electrical distribution systems reinforcement planning using gas micro turbines by dynamic ant colony search algorithmIEEE Trans Power Syst200722258058710.1109/TPWRS.2007.894861 – reference: SuCLProbabilistic load-flow computation using point estimate methodIEEE Trans Power Syst200520418431851212000810.1109/TPWRS.2005.857921 – reference: BorzacchielloDMalikMChinestaFGarcía-BlancoRDiezPUnified formulation of a family of iterative solvers for power systems analysisElectr Power Syst Res201614020120810.1016/j.epsr.2016.06.021 – reference: Chen P, Chen Z, Bak-Jensen B (2008) Probabilistic load flow: a review. In: Third international conference on electric utility deregulation and restructuring and power technologies, 2008. DRPT 2008, pp 1586–1591 – reference: BrownH. E.PersonC. E.KirchmayerL. K.StaggG. W.Digital Calculation of 3-Phase Short Circuits by Matrix MethodTransactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems196079312771281 – reference: LaughtonM.A.Humphrey DaviesM.W.Numerical techniques in solution of power-system load-flow problemsProceedings of the Institution of Electrical Engineers19641119157510.1049/piee.1964.0259 – reference: Griffin T, Tomsovic K, Law A (2000) Placement of dispersed generation systems for reduced losses. In: Proceedings of the 33rd Hawaii international conference on system sciences 2000, pp 1–9 – reference: Borzacchiello D, Chinesta F, García-Blanco R, Diez P (2016) Introduction to the proper generalized decomposition for the solution of the parametrized power equations. Submitted – reference: Yi-ShanZHsiao-DongCFast Newton-FGMRES solver for large-scale power flow studyIEEE Trans Power Syst201025276977610.1109/TPWRS.2009.2036018 – reference: AcharyaNMahatPMithulananthanNAn analytical approach for DG allocation in primary distribution networkInt J Elect Power Energy Syst2006281066967810.1016/j.ijepes.2006.02.013 – reference: El-Khattam W, Hegazy YG, Salama MMA (2003) Stochastic power flow analysis of electrical distributed generation systems. In: Power engineering society general meeting, 2003, IEEE, vol 2, p 1144 – reference: Tang J, Ni F, Ponci F, Monti A (2015) Dimension-adaptive sparse grid interpolation for uncertainty quantification in modern power systems: probabilistic power flow. In: IEEE Transactions on power systems, PP, No. 99, pp 1–13 – reference: DerakhshandehSYPourbagherRApplication of high-order Newton-like methods to solve power flow equationsIET Gener Trans Distrib20161081853185910.1049/iet-gtd.2015.0998 – reference: Trias A (2012) The holomorphic embedding load flow method. In: Power and energy society general meeting, 2012 IEEE, San Diego, California, pp 1–8 – reference: Chaturantabut S, Sorensen D (2009) Application of POD and DEIM on dimension reduction of non-linear miscible viscous fingering in porous media. Math Comput Model Dyn Syst – reference: De LeonFSemlyenAIterative solvers in the Newton power flow problem: preconditioners, inexact solutions, and partial jacobian updatesIEEE Proc—Gener Transm Distrib2002149447948410.1049/ip-gtd:20020172 – reference: Ness JV (1959) Iteration methods for digital load flow studies. Power apparatus and systems. Transactions of the American Institute of Electrical Engineers, vol 78, pp 583–588 – reference: Subramanian MK, Feng Y, Tylavsky D (2013) PV bus modeling in a holomorphically embedded power-flow formulation. North American Power Symposium (NAPS) 2013, pp 1–6 – reference: KnollDKeyesDJacobian-free Newton-Krylov methods: a survey of approaches and applicationsJ Comput Phys20041932357397203047110.1016/j.jcp.2003.08.010 – reference: ChinestaF.LeygueA.BordeuF.AguadoJ. V.CuetoE.GonzalezD.AlfaroI.AmmarA.HuertaA.PGD-Based Computational Vademecum for Efficient Design, Optimization and ControlArchives of Computational Methods in Engineering20132013159302405810.1007/s11831-013-9080-x – reference: Chaturantabut S, Sorensen D (2009) Discrete empirical interpolation for nonlinear model reduction. In: Proceedings of the 48th IEEE Conference on decision and control, 2009 held jointly with the 2009 28th Chinese control conference. CDC/CCC 2009, pp 4316–4321 – reference: TriasAMarínJLThe holomorphic embedding loadflow method for dc power systems and nonlinear dc circuitsIEEE Trans Circuits Syst I: Regul Pap2016632322333347986310.1109/TCSI.2015.2512723 – reference: StottB.Effective starting process for Newton-Raphson load flowsProceedings of the Institution of Electrical Engineers1971118898310.1049/piee.1971.0197 – reference: Ou TC, Lin WM (2009) A novel Z-matrix algorithm for distribution power flow solution. In: PowerTech, 2009 IEEE Bucharest, pp 1–8 – reference: Bijwe PR, Abhijith B, Raju GKV (2009) Robust three phase fast decoupled power flow. In: Power systems conference and exposition, 2009. PSCE ’09. IEEE/PES, pp 1–5 – reference: TengJHA modified Gauss-Seidel algorithm of three-phase power flow analysis in distribution networksInt J Electr Power Energy Syst200224297102188385010.1016/S0142-0615(01)00022-9 – reference: IwamotoS.TamuraY.A Load Flow Calculation Method for Ill-Conditioned Power SystemsIEEE Transactions on Power Apparatus and Systems1981PAS-10041736174310.1109/TPAS.1981.316511 – reference: Yong T, Lasseter RH (2000) Stochastic optimal power flow: formulation and solution. In: Power engineering society summer meeting, 2000. IEEE, vol 1, pp 237–242 – reference: Chiang HD, Zhao TQ, Deng JJ, Koyanagi K (2014) Convergence/divergence analysis of implicit Z-bus power flow for general distribution networks. In: 2014 IEEE international symposium on circuits and systems (ISCAS), pp 1808–1811 – reference: ShareefSDMKumarTVA review on models and methods for optimal placement of distributed generation in power distribution systemInt J Educ Appl Res20144161169 – reference: Willis HL (2000) Analytical methods and rules of thumb for modeling dg-distribution interaction. In: Power engineering society summer meeting, 2000. IEEE, vol 3, pp 1643–1644 – reference: Li G, Zhang XP (2009) Comparison between two probabilistic load flow methods for reliability assessment. In: 2009 IEEE power energy society general meeting, pp 1–7 – reference: Dimitrovski A, Tomsovic K (2004) Slack bus treatment in load flow solutions with uncertain nodal powers. In: Probabilistic methods applied to power systems, 2004 international conference onm, Ames (Iowa), pp 532–537 – reference: ChaturantabutSSorensenDNonlinear model reduction via discrete empirical interpolationSIAM J Sci Comput201032527372764268473510.1137/090766498 – reference: ChengCFZA modified Newton method for radial distribution system power flow analysisIEEE Trans Power Syst1997121389397 – reference: DopazoJFKlitinOASassonAMStochastic load flowsIEEE Trans Power Apparat Syst197594229930910.1109/T-PAS.1975.31855 – reference: Trias A (2015) Fundamentals of the holomorphic embedding load-flow method. ArXiv e-prints (1509), 02,421 – reference: GalballyDFidkowskiKWillcoxKGhattasONon-linear model reduction for uncertainty quantification in large-scale inverse problemsInt J Numer Methods Eng201081121581160826428211183.76837 – reference: Grainer JJ, Stevenson W (2008) McGraw-Hill Education, New York – reference: AllanR.N.Al-ShakarchiM.R.GProbabilistic techniques in a.c. load-flow analysisProceedings of the Institution of Electrical Engineers1977124215410.1049/piee.1977.0027 – reference: Zhu J, Abur A (2006) Identification of errors in power flow controller parameters. In: International Conference on probabilistic methods applied to power systems, 2006. PMAPS 2006, pp 1–6 – reference: BarraultMMadayYNguyenNCPateraATAn empirical interpolation method: application to efficient reduced-basis discretization of partial differential equationsComptes Rendus Math20043399667672210320810.1016/j.crma.2004.08.006 – reference: Zhang Z, Nguyen HD, Turitsyn K, Daniel L (2015) Probabilistic power flow computation via low-rank and sparse tensor recovery. IEEE Trans Power Syst – reference: HinzeMKunkelMMichielsenBPoirierJRDiscrete empirical interpolation in POD model order reduction of drift-diffusion equations in electrical networksScientific computing in electrical engineering SCEE 2010, mathematics in industry2012BerlinSpringer42343110.1007/978-3-642-22453-9_45 – reference: AmmarAChinestaFCuetoECoupling finite elements and proper generalized decompositionsInt J Multiscale Comput Eng201191173310.1615/IntJMultCompEng.v9.i1.30 – reference: AbidoMOptimal power flow using particle swarm optimizationInt J Electr Power Energy Syst200224756357110.1016/S0142-0615(01)00067-9 – reference: BrownH.CarterG.HappH.PersonC.Power Flow Solution by Impedance Matrix Iterative MethodIEEE Transactions on Power Apparatus and Systems1963826511010.1109/TPAS.1963.291392 – reference: YangNien-CheThree-phase power flow calculations using direct Z BUS method for large-scale unbalanced distribution networksIET Generation, Transmission & Distribution20161041048105510.1049/iet-gtd.2015.0822 – reference: Martinez JA, Guerra G (2012) Optimum placement of distributed generation in three-phase distribution systems with time varying load using a Monte Carlo approach. In: Power and Energy Society General Meeting, 2012 IEEE, San Diego, California, pp 1–7 – reference: de SouzaAJuniorCLima LopesILemeRCarpinteiroONon-iterative load-flow method as a tool for voltage stability studiesIET Gener Transm Distrib20071349950510.1049/iet-gtd:20060310 – reference: SchafferMDTylavskyDJA nondiverging polar-form Newton-based power flowIEEE Trans Ind Appl198824587087710.1109/28.8993 – reference: Borkowska B (1974) Probabilistic load flow. IEEE transactions on power apparatus and systems, vol PAS-93, No. 3, pp 752–759 – reference: Maffei A, Iannelli L, Glielmo L (2015) A colored Gauss-Seidel approach for the distributed network flow problem. In: 2015 54th IEEE conference on decision and control (CDC), pp 4934–4939 – reference: Stott, B., Alsac, O.: Fast Decoupled Load Flow. IEEE transactions on power apparatus and systems, PAS-93, No. 3, pp 859–869 – reference: MonticelliAGarciaASaavedraOFast decoupled load flow: hypothesis, derivations, and testingIEEE Trans Power Syst1990541425143110.1109/59.99396 – reference: ChinestaFLadevezePCuetoEA short review on model order reduction based on proper generalized decompositionArch Comput Methods Eng201118439540410.1007/s11831-011-9064-7 – reference: García-Blanco R, Borzacchiello D, Chinesta F, Diez P (2016) A reduced order modeling approach for optimal allocation of distributed generation in power distribution systems. In: 2016 IEEE International energy conference (ENERGYCON), Leuven, Belgium – reference: Rao S, Feng Y, Tylavsky DJ, Subramanian MK (2015) The holomorphic embedding method applied to the power-flow problem. IEEE Transactions on Power Systems PP, No. 99, pp 1–13 – reference: Hochman A, Bond BN, White JK (2011) A stabilized discrete empirical interpolation method for model reduction of electrical, thermal, and microelectromechanical systems. In: Proceedings of the 48th Design Automation Conference on - DAC ’11, ACM Press, New York, USA, p 540 – reference: ZhangPLeeSTProbabilistic load flow computation using the method of combined cumulants and gram-charlier expansionIEEE Trans Power Syst200419167668210.1109/TPWRS.2003.818743 – reference: Ward JB, Hale HW (1956) Digital computer solution of power-flow problems [includes discussion]. Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems, vol 75, No. 3 – reference: LambertTGilmanPLilienthalPMicropower system modeling with HOMER2006New YorkWiley – reference: FrankSSteponaviceIRebennackSOptimal power flow: a bibliographic survey IEnergy Syst20123322125810.1007/s12667-012-0056-y – reference: Rathinam M, Petzold LR (2000) An iterative method for simulation of large scale. In: Proceedings of the 39th IEEE conference on decision and control, Sydney 2000, pp 4630–4635 – reference: ZhangHLiPApplication of sparse-grid technique to chance constrained optimal power flowGener Transm Distrib IET20137549149910.1049/iet-gtd.2012.0269 – reference: Kabir S, Chowdhury A, Rahman M, Alam J (2014) Inclusion of slack bus in Newton Raphson load flow study. 2014 International conference on electrical and computer engineering (ICECE), Dhaka, pp 282–284 – reference: Kim KH, Lee YJ, Rhee SB, Lee SK, You SK (2002) Dispersed generator placement using fuzzy-ga in distribution systems. In: Power engineering society summer meeting, 2002 IEEE, vol 3, pp 1148–1153 – reference: BrownRodney J.TinneyWilliam F.Digital Solutions for Large Power NetworksTransactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems1957763347351 – reference: GuptaP.P.Humphrey DaviesM.W.Digital computers in power system analysisProceedings of the IEE Part A: Power Engineering19611084138310.1049/pi-a.1961.0077 – reference: WardJBEquivalent circuits for power-flow studiesAIEE Trans Power Apparat Syst1949689373382 – reference: Nara K, Hayashi Y, Ikeda K, Ashizawa T (2001) Application of Tabu search to optimal placement of distributed generators, pp 918–923. IEEE – reference: WasleyR.G.ShlashM.A.Newton-Raphson algorithm for 3-phase load flowProceedings of the Institution of Electrical Engineers1974121763010.1049/piee.1974.0145 – reference: GlimnA. F.StaggG. W.Automatic Calculation of Load FlowsTransactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems1957763817825 – reference: Pinnau R. In: W Schilders, H Vorst, J Rommes (eds) Model order reduction: theory, research aspects and applications, Mathematics in Industry, vol 13 – reference: Wirtz D, Sorensen D, Haasdonk B (2014) A-posteriori error estimation for DEIM reduced nonlinear dynamical systems. SIAM J Sci Comput 1–31 – reference: García-Blanco R, Borzacchiello D, Chinesta F, Diez P (2016) Monitoring a PGD solver for parametric power flow problems with goal-oriented error assessment (article in review). Int J Numer Methods – reference: Taylor D, Treece J (1967) Load flow analysis by the Gauss-Seidel method. Symposium on power systems, load flow analysis. University of Manchester Institute of Science and Technology, Manchester, UK – reference: GeorgilakisPHatziargyriouNOptimal distributed generation placement in power distribution networks: models, methods, and future researchIEEE Trans Power Syst20132833420342810.1109/TPWRS.2012.2237043 – reference: TripathyS. C.PrasadG. DurgaMalikO. P.HopeG. S.Load-Flow Solutions for Ill-Conditioned Power Systems by a Newton-Like MethodIEEE Power Engineering Review1982PER-210252610.1109/MPER.1982.5519878 – reference: SauerP.Explicit Load Flow Series and FunctionsIEEE Transactions on Power Apparatus and Systems1981PAS-10083754376310.1109/TPAS.1981.317018 – reference: RauNNecsulescuCSolution of probabilistic load flow equations using combinatoricsInt J Electr Power Energy Syst199012315616410.1016/0142-0615(90)90028-A – reference: StaggGWEl-AbiadAHComputer methods in power system-analysis1968New YorkMcGraw-Hill – reference: Shrivastava VK, Rahi O, Gupta VK, Kuntal JS (2012) Optimal placement methods of distributed generation: a review. IEEE Transactions on Power Systems, pp. 978–981 – reference: ChinestaFAmmarACuetoEOn the use of proper generalized decompositions for multidimensional modelsRevue européenne des éléments finis20058112 – reference: Sameni A, Nassif AB, Opathella C, Venkatesh B (2012) A modified Newton-Raphson method for unbalanced distribution systems. In: 2012 IEEE international conference on smart grid engineering (SGE), pp 1–7 – reference: Gómez-ExpósitoAConejoAJCañizaresCElectric energy systems: analysis and operation2008Boca RatonCRC Press10.1201/9781420007275 – reference: Mithulananthan N, Oo T, Phu LV (2004) Distributed generator in power distribution placement system using genetic algorithm to reduce losses. Thammasat Int J Sci Technol 9(3) – reference: Li Y, Luo Y, Zhang B, Mao C (2011) A modified Newton-Raphson power flow method considering wind power. In: Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific, pp 1–5 – reference: WuF.F.Theoretical study of the convergence of the fast decoupled load flowIEEE Transactions on Power Apparatus and Systems197796126827510.1109/T-PAS.1977.32334 – reference: ChinestaFAmmarACuetoERecent advances and new challenges in the use of the proper generalized decomposition for solving multidimensional modelsArch Comput Methods Eng2010174327350273994210.1007/s11831-010-9049-y – reference: Idema R, Lahaye D, Vuik K, van der Sluis L (2010) Fast Newton load flow. IEEE PES Transmission and Distribution, pp 1–7 – reference: RouhaniMMohammadiMKargarianAParzen window density estimator-based probabilistic power flow with correlated uncertaintiesIEEE Trans Sustain Energy2016731170118110.1109/TSTE.2016.2530049 – reference: Zhao TQ, Chiang HD, Koyanagi K (2016) Convergence analysis of implicit Z-bus power flow method for general distribution networks with distributed generators. IET generation, transmission distribution, vol 10, No. 2, pp 412–420 – reference: Hale H, Goodrich R (1959) Digital computation or power flow—some new aspects. Power apparatus and systems, Part III. Transactions of the American Institute of Electrical Engineers, vol 78, No. 3, pp 919–923 – reference: TinneyWilliam.HartCliffordPower Flow Solution by Newton's MethodIEEE Transactions on Power Apparatus and Systems1967PAS-86111449146010.1109/TPAS.1967.291823 – reference: LadevèzePSimmondsJNonlinear computational structural mechanics: new approaches and non-incremental methods of calculation1999New YorkSpringer10.1007/978-1-4612-1432-8 – reference: HuneaultMGalianaFA survey of the optimal power flow literatureIEEE Trans Power Syst19916276277010.1109/59.76723 – reference: Amini MH, Ilić MD, Karabasoglu O (2015) DC power flow estimation utilizing bayesian-based lmmse estimator. In: 2015 IEEE power energy society general meeting, pp 1–5 – reference: ElgerdOIElectric energy systems theory1972New YorkMcGraw-Hill – reference: SirovichLTurbulence and the dynamics of coherent structuresI–III. Quart Appl Math19874556159091046210.1090/qam/910462 – reference: He J, Zhou B, Zhang Q, Zhao Y, Liu J (2012) An improved power flow algorithm for distribution networks based on Z-bus algorithm and forward/backward sweep method. In: 2012 international conference on control engineering and communication technology (ICCECT), pp 1–4 – reference: Thorp JS, Naqavi SA, Chiang HD (1990) More load flow fractals. In: Proceedings of the 29th IEEE conference on decision and control, 1990, vol 6, pp. 3028–3030 – reference: BramellerA.DenmeadJ.K.Some improved methods for digital network analysisProceedings of the IEE Part A: Power Engineering19621094310910.1049/pi-a.1962.0078 – reference: Gandomkar M, Vakilian M, Ehsan M (2005) A combination of genetic algorithm and simulated annealing for optimal dg allocation in distribution networks. In: Canadian conference on electrical and computer engineering 2005, pp 645–648 – reference: IdemaRPapaefthymiouGLahayeDVuikCvan der SluisLTowards faster solution of large power flow problemsIEEE Trans Power Syst20132844918492510.1109/TPWRS.2013.2252631 – reference: ZimmermanRDChiangHDFast decoupled power flow for unbalanced radial distribution systemsIEEE Trans Power Syst19951042045205210.1109/59.476074 – ident: 9223_CR19 doi: 10.1109/ISCAS.2014.6865508 – volume: 12 start-page: 389 issue: 1 year: 1997 ident: 9223_CR25 publication-title: IEEE Trans Power Syst – ident: 9223_CR32 doi: 10.1049/piee.1964.0259 – volume: 32 start-page: 2737 issue: 5 year: 2010 ident: 9223_CR72 publication-title: SIAM J Sci Comput doi: 10.1137/090766498 – volume: 24 start-page: 563 issue: 7 year: 2002 ident: 9223_CR107 publication-title: Int J Electr Power Energy Syst doi: 10.1016/S0142-0615(01)00067-9 – volume: 7 start-page: 491 issue: 5 year: 2013 ident: 9223_CR120 publication-title: Gener Transm Distrib IET doi: 10.1049/iet-gtd.2012.0269 – volume: 4 start-page: 185 issue: 3 year: 2014 ident: 9223_CR119 publication-title: Int J Uncertain Quantif doi: 10.1615/Int.J.UncertaintyQuantification.2013003479 – ident: 9223_CR130 – volume: 24 start-page: 97 issue: 2 year: 2002 ident: 9223_CR30 publication-title: Int J Electr Power Energy Syst doi: 10.1016/S0142-0615(01)00022-9 – volume: 94 start-page: 299 issue: 2 year: 1975 ident: 9223_CR81 publication-title: IEEE Trans Power Apparat Syst doi: 10.1109/T-PAS.1975.31855 – ident: 9223_CR15 doi: 10.1109/TPAS.1963.291392 – ident: 9223_CR110 – volume-title: Nonlinear computational structural mechanics: new approaches and non-incremental methods of calculation year: 1999 ident: 9223_CR63 doi: 10.1007/978-1-4612-1432-8 – ident: 9223_CR69 – ident: 9223_CR17 – ident: 9223_CR101 doi: 10.1109/ICEC.1998.700121 – volume: 24 start-page: 661 issue: 2 year: 2009 ident: 9223_CR88 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2016589 – volume: 199 start-page: 1872 issue: 25–28 year: 2010 ident: 9223_CR76 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2010.02.012 – ident: 9223_CR11 – ident: 9223_CR5 – ident: 9223_CR42 doi: 10.1109/TPAS.1974.293985 – ident: 9223_CR89 doi: 10.1109/TPAS.1968.292150 – ident: 9223_CR123 doi: 10.1007/s11831-013-9080-x – ident: 9223_CR54 doi: 10.1109/TPAS.1981.317018 – volume: 68 start-page: 373 issue: 9 year: 1949 ident: 9223_CR115 publication-title: AIEE Trans Power Apparat Syst – ident: 9223_CR95 doi: 10.1109/HICSS.2000.926773 – volume: 145 start-page: 251 issue: 3 year: 1998 ident: 9223_CR55 publication-title: IEEE Proc Gener Transm Distrib doi: 10.1049/ip-gtd:19981980 – ident: 9223_CR23 – ident: 9223_CR53 doi: 10.1109/CDC.1990.203339 – volume: 20 start-page: 1843 issue: 4 year: 2005 ident: 9223_CR86 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2005.857921 – volume: 81 start-page: 1581 issue: 12 year: 2010 ident: 9223_CR70 publication-title: Int J Numer Methods Eng doi: 10.1002/nme.2746 – volume: 45 start-page: 561 year: 1987 ident: 9223_CR112 publication-title: I–III. Quart Appl Math doi: 10.1090/qam/910462 – ident: 9223_CR6 – volume-title: Electric energy systems theory year: 1972 ident: 9223_CR3 – ident: 9223_CR67 doi: 10.1109/PESGM.2015.7286047 – volume: 4 start-page: 161 year: 2014 ident: 9223_CR92 publication-title: Int J Educ Appl Res – ident: 9223_CR27 doi: 10.1109/APPEEC.2011.5748520 – volume: 63 start-page: 322 issue: 2 year: 2016 ident: 9223_CR60 publication-title: IEEE Trans Circuits Syst I: Regul Pap doi: 10.1109/TCSI.2015.2512723 – ident: 9223_CR104 doi: 10.1109/PESS.2002.1043458 – volume: 96 start-page: 189 issue: 1 year: 1977 ident: 9223_CR57 publication-title: IEEE Trans Power Appar Syst doi: 10.1109/T-PAS.1977.32323 – volume: 140 start-page: 201 year: 2016 ident: 9223_CR64 publication-title: Electr Power Syst Res doi: 10.1016/j.epsr.2016.06.021 – volume: 15 start-page: 508 issue: 2 year: 2000 ident: 9223_CR26 publication-title: IEEE Trans Power Syst doi: 10.1109/59.867133 – volume: 225–228 start-page: 116 year: 2012 ident: 9223_CR78 publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2012.03.016 – ident: 9223_CR93 doi: 10.1109/PESGM.2012.6345040 – ident: 9223_CR22 – ident: 9223_CR4 doi: 10.1049/piee.1974.0145 – volume-title: Electric energy systems: analysis and operation year: 2008 ident: 9223_CR34 doi: 10.1201/9781420007275 – volume: 5 start-page: 1425 issue: 4 year: 1990 ident: 9223_CR47 publication-title: IEEE Trans Power Syst doi: 10.1109/59.99396 – volume: 193 start-page: 357 issue: 2 year: 2004 ident: 9223_CR39 publication-title: J Comput Phys doi: 10.1016/j.jcp.2003.08.010 – volume: 9 start-page: 2014 issue: 4 year: 1994 ident: 9223_CR99 publication-title: IEEE Trans Power Syst doi: 10.1109/59.331463 – volume: 22 start-page: 580 issue: 2 year: 2007 ident: 9223_CR105 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2007.894861 – volume: 10 start-page: 1853 issue: 8 year: 2016 ident: 9223_CR29 publication-title: IET Gener Trans Distrib doi: 10.1049/iet-gtd.2015.0998 – ident: 9223_CR49 doi: 10.1109/TPAS.1981.316511 – ident: 9223_CR36 doi: 10.1109/TDC.2010.5484211 – ident: 9223_CR118 doi: 10.1145/2024724.2024850 – volume: 8 start-page: 1 year: 2005 ident: 9223_CR124 publication-title: Revue européenne des éléments finis – ident: 9223_CR100 doi: 10.1109/PES.2003.1270485 – ident: 9223_CR121 – ident: 9223_CR59 – ident: 9223_CR90 doi: 10.1109/TPAS.1984.318284 – volume: 27 start-page: 390 issue: 1 year: 2012 ident: 9223_CR37 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2011.2165860 – volume: 22 start-page: 375 issue: 5 year: 2000 ident: 9223_CR44 publication-title: Int J Electr Power Energy Syst doi: 10.1016/S0142-0615(00)00002-8 – volume: 28 start-page: 669 issue: 10 year: 2006 ident: 9223_CR98 publication-title: Int J Elect Power Energy Syst doi: 10.1016/j.ijepes.2006.02.013 – volume: 9 start-page: 17 issue: 1 year: 2011 ident: 9223_CR75 publication-title: Int J Multiscale Comput Eng doi: 10.1615/IntJMultCompEng.v9.i1.30 – volume: 28 start-page: 3420 issue: 3 year: 2013 ident: 9223_CR91 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2012.2237043 – ident: 9223_CR13 doi: 10.1049/pi-a.1962.0078 – ident: 9223_CR31 doi: 10.1109/CDC.2015.7402990 – volume: 1 start-page: 499 issue: 3 year: 2007 ident: 9223_CR56 publication-title: IET Gener Transm Distrib doi: 10.1049/iet-gtd:20060310 – volume: 5 start-page: 79 issue: 1 year: 2011 ident: 9223_CR94 publication-title: Renew Power Generat IET doi: 10.1049/iet-rpg.2009.0011 – volume: 20 start-page: 31 issue: 1 year: 2013 ident: 9223_CR127 publication-title: Arch Comput Methods Eng doi: 10.1007/s11831-013-9080-x – ident: 9223_CR58 doi: 10.1109/PESGM.2012.6344759 – ident: 9223_CR129 – ident: 9223_CR14 – ident: 9223_CR16 doi: 10.1109/TPAS.1968.292196 – volume: 12 start-page: 156 issue: 3 year: 1990 ident: 9223_CR87 publication-title: Int J Electr Power Energy Syst doi: 10.1016/0142-0615(90)90028-A – ident: 9223_CR62 – ident: 9223_CR114 – ident: 9223_CR113 doi: 10.1109/ANDESCON.2010.5633415 – ident: 9223_CR84 doi: 10.1049/piee.1977.0027 – ident: 9223_CR45 doi: 10.1109/PSCE.2009.4840149 – ident: 9223_CR77 doi: 10.1016/j.cma.2014.09.025 – ident: 9223_CR82 doi: 10.1109/PES.2009.5275534 – volume: 25 start-page: 769 issue: 2 year: 2010 ident: 9223_CR35 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2009.2036018 – ident: 9223_CR83 doi: 10.1109/POWERCON.2014.6993521 – ident: 9223_CR24 doi: 10.1109/TPAS.1967.291823 – ident: 9223_CR9 – ident: 9223_CR28 doi: 10.1109/SGE.2012.6463955 – start-page: 423 volume-title: Scientific computing in electrical engineering SCEE 2010, mathematics in industry year: 2012 ident: 9223_CR117 doi: 10.1007/978-3-642-22453-9_45 – volume: 10 start-page: 2045 issue: 4 year: 1995 ident: 9223_CR43 publication-title: IEEE Trans Power Syst doi: 10.1109/59.476074 – volume: 21 start-page: 1096 issue: 3 year: 2006 ident: 9223_CR41 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2006.876696 – ident: 9223_CR51 doi: 10.1109/MPER.1982.5519878 – ident: 9223_CR65 – ident: 9223_CR21 doi: 10.1049/iet-gtd.2015.0822 – ident: 9223_CR128 doi: 10.1109/ENERGYCON.2016.7514119 – ident: 9223_CR71 – volume: 17 start-page: 327 issue: 4 year: 2010 ident: 9223_CR126 publication-title: Arch Comput Methods Eng doi: 10.1007/s11831-010-9049-y – volume: 24 start-page: 870 issue: 5 year: 1988 ident: 9223_CR50 publication-title: IEEE Trans Ind Appl doi: 10.1109/28.8993 – ident: 9223_CR96 – ident: 9223_CR1 – volume: 7 start-page: 685 issue: 3 year: 2012 ident: 9223_CR66 publication-title: J Comput – ident: 9223_CR80 doi: 10.1109/TPAS.1974.293973 – ident: 9223_CR102 – volume: 62 start-page: 916 issue: 7 year: 1974 ident: 9223_CR33 publication-title: Proc IEEE doi: 10.1109/PROC.1974.9544 – ident: 9223_CR48 doi: 10.1049/piee.1971.0197 – ident: 9223_CR122 – volume: 149 start-page: 479 issue: 4 year: 2002 ident: 9223_CR40 publication-title: IEEE Proc—Gener Transm Distrib doi: 10.1049/ip-gtd:20020172 – ident: 9223_CR61 doi: 10.1109/NAPS.2013.6666940 – ident: 9223_CR106 doi: 10.1109/PESW.2001.916995 – ident: 9223_CR103 doi: 10.1109/CCECE.2005.1557013 – ident: 9223_CR20 doi: 10.1049/iet-gtd.2015.0679 – ident: 9223_CR46 doi: 10.1109/T-PAS.1977.32334 – ident: 9223_CR116 – volume: 28 start-page: 4918 issue: 4 year: 2013 ident: 9223_CR38 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2013.2252631 – ident: 9223_CR8 doi: 10.1109/AIEEPAS.1956.4499318 – volume: 18 start-page: 395 issue: 4 year: 2011 ident: 9223_CR125 publication-title: Arch Comput Methods Eng doi: 10.1007/s11831-011-9064-7 – volume-title: Computer methods in power system-analysis year: 1968 ident: 9223_CR2 – ident: 9223_CR12 doi: 10.1049/pi-a.1961.0077 – ident: 9223_CR74 doi: 10.1137/120899042 – volume: 3 start-page: 221 issue: 3 year: 2012 ident: 9223_CR109 publication-title: Energy Syst doi: 10.1007/s12667-012-0056-y – volume: 19 start-page: 676 issue: 1 year: 2004 ident: 9223_CR85 publication-title: IEEE Trans Power Syst doi: 10.1109/TPWRS.2003.818743 – volume: 6 start-page: 762 issue: 2 year: 1991 ident: 9223_CR108 publication-title: IEEE Trans Power Syst doi: 10.1109/59.76723 – ident: 9223_CR7 doi: 10.1109/ICECE.2014.7026900 – ident: 9223_CR111 – ident: 9223_CR97 doi: 10.1109/PESS.2000.868774 – volume-title: Micropower system modeling with HOMER year: 2006 ident: 9223_CR131 – ident: 9223_CR18 – volume: 339 start-page: 667 issue: 9 year: 2004 ident: 9223_CR73 publication-title: Comptes Rendus Math doi: 10.1016/j.crma.2004.08.006 – volume: 10 start-page: 59 issue: 1 year: 1997 ident: 9223_CR52 publication-title: IEEE Comput Appl Power doi: 10.1109/67.560872 – ident: 9223_CR79 doi: 10.1002/nme.5470 – ident: 9223_CR10 – volume: 7 start-page: 1170 issue: 3 year: 2016 ident: 9223_CR68 publication-title: IEEE Trans Sustain Energy doi: 10.1109/TSTE.2016.2530049 |
| SSID | ssj0054992 |
| Score | 2.1996756 |
| Snippet | The power flow model performs the analysis of electric distribution and transmission systems. With this statement at hand, in this work we present a summary of... The final publication is available at Springer via http://dx.doi.org/10.1007/s11831-017-9223-6 The power flow model performs the analysis of electric... |
| SourceID | hal csuc proquest crossref springer |
| SourceType | Open Access Repository Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 1003 |
| SubjectTerms | 49 Calculus of variations and optimal control; optimization 49K Necessary conditions and sufficient conditions for optimality 90 Operations research, mathematical programming 90B Operations research and management science Accuracy Accuracy control Algebra Anàlisi matemàtica Approximation Classificació AMS Computer simulation Construction Càlcul de variacions Data buses Distributed generation Engineering Engineering Sciences Flow equations IEEE standards Investigació operativa Iterative methods Matemàtiques i estadística Mathematical and Computational Engineering Mathematical models Mathematical optimization Operations research Optimització Optimització matemàtica Optimization Original Paper Power flow Power flow problem Real time Reduced order model Solvers Àrees temàtiques de la UPC |
| SummonAdditionalLinks | – databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Rb9MwED5B4QEeGAwQYRuyEE8gS4nT2M7eKrRqD9NUbWPam2U7DlTqWtS0Q_wA_jd3TtIOxJDgIQ9JnLNln32fc-fvAN45WVRWVzXPrHR8iICYu7TykfeWyEGUj1x6lyfq9FRfXZWT7hx300e79y7JuFJvD7uh9tHWV_ESbRqX9-EBWjtNs_Hs_LJffmm_E12cWU6__OXGlfknEb8Yo4Fv1h5NzBeKiLwFN3_zkEbDM975ryY_hScdzmSjVjGewb0w34WdDnOybkY3u_D4FiHhc_gxmn0mT_LUMzuv2MRS6BZx-LPzBYVQNwwxLkPMyCaUXY2NZ4tvbNLmpDlkFzEEt2FnCD45nS2JQkber5fWf-ekjTSOVP_0uksbxhY1O4qpeKiSlj79BXwaH118POZdogbuEW2tuLKFFnlInctsHoTKnLOyUqmqEf_ovHJeCB9yKUtthSxrYqBRqqgKKzIZXJq_hMF8MQ-vgBW4vSl0XqMch7JzVwSReiUqjQJcXiSQ9iNmfMdiTsk0ZmbLv0ydbrDTDXW6kQm833zytaXw-HthVAOD5iYsvV0Zot_e3NAlUiWMKDMEXgm8RWXZCKWix6MTQ89wbSz1sFA3WQL7vS6Zbn1oDAKGIfF0yjKBD73ubF_f2bzX_1R6Dx4hvtPt0cl9GKyW63AAD_3Natos38Rp8xMXAA9I priority: 102 providerName: Springer Nature |
| Title | Algebraic and Parametric Solvers for the Power Flow Problem: Towards Real-Time and Accuracy-Guaranteed Simulation of Electric Systems |
| URI | https://link.springer.com/article/10.1007/s11831-017-9223-6 https://www.proquest.com/docview/2124047269 https://recercat.cat/handle/2072/291317 https://hal.science/hal-04098457 |
| Volume | 25 |
| WOSCitedRecordID | wos000447992300006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1886-1784 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0054992 issn: 1134-3060 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3fb9MwELZYxwMvjJ9aYFQW4glkkTi1nfCCytRqEqOK2jEGL5btJFCpNKNph_gD-L-5S5wWkNgLD7XUJrlEvcvdZ9_5O0KeWSlyk-Qli4y0bACAmNkwdw3vLZKDKNdw6Z2fqskkubhIM7_gVvuyys4nNo46rxyukb8EFztAZkOZvr78xrBrFGZXfQuNPbIfcR6hnb9VrPPEOPVpsp1RjKv_cpvVbLbOgS3jRFqxFCIkk3_EpZ6rNw6izRcsjvwNef6VLG1i0Pjgf5_-Drnt0ScdtuZyl9wolvfIgUei1L_n9X3yc7j4jBnluaNmmdPMYAkXcvnTWYWl1DUFrEsBO9IMu6zR8aL6TrO2N80retaU4tZ0CiCU4R6TRsjQuc3KuB8MrRL1iXecf_Xtw2hV0lHTkgdv0tKoPyDvx6Oz4xPmGzYwB6hrzZQRCY-L0NrIxAVXkbVG5ipUJeCgJM6t49wVsZRpYuCvKJGJRimRC8MjWdgwfkh6y2pZHBIqYJojkrgEORZkx1YUPHSK5wkIsLEISNipSzvPZo5NNRZ6x8OMGtagYY0a1jIgz7eXXLZUHtefDDagIewUK2fWGmm4t1_ww0PFNU8jAGABeQqWshWKp54MTzX-Bj4yTQZCXUUBOepMQ3s_UeudXQTkRWdcu8P_fLxH1wt7TG4BsEvaPZNHpLdebYon5Ka7Ws_rVZ_sqQ8f-2T_zWiSTfvNKwPju_AYRzWDMROfYJzOzn8ByuUbkg |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9NAEB2VgAQXyqcwFFghuIBW2OvYayMhFJVGqRqiCALqbdldr2mkNC5x0qo_gL_Db2TGHwkg0VsPHHJI4sxGzpuZt5nZNwDPTRxlOslyHujY8C4SYm78zFa6tyQOIm2lpfdlKEej5PAwHW_Bz_YsDLVVtjGxCtRZYek_8tcYYrukbBin706-c5oaRdXVdoRGDYsDd36GW7by7f57_H1fCNHfm-wOeDNVgFukBksudZSI0PnGBDp0QgbG6DiTvswxWSdhZqwQ1oVxnCYaV8tJLkXKKIu0CGJn_BDtXoGr3S66A7UK-rtt5KetVlVdDUKqNsTrKmp1VA99hzbukqeYkXn8Rx7s2HJlMbsdUTPmb0z3r-JslfP62__b3boFNxt2zXq1O9yGLTe_A9sN02ZNHCvvwo_e7BtVzKeW6XnGxppa1GhWAftUUKt4yZDLM-TGbExT5Fh_VpyxcT175w2bVK3GJfuIJJvTGZrKSM_a1ULbc05eR3ilFafHzXg0VuRsrxo5RIvUMvH34POl3Iz70JkXc_cAWITbuCgJc7Rj0HZoIid8K0WWoAETRh74LTyUbdTaaWjITG10pglRChGlCFEq9uDl-iMntVTJxRcj5hSmVbeweqlIZnz9hB7Cl0KJNECC6cEzRObaKF066A0VvYY5IE26kTwNPNhpoaiaOFiqDQ49eNWCefP2P7_ew4uNPYXrg8mHoRrujw4ewQ0ksUl9PnQHOsvFyj2Ga_Z0OS0XTyoHZfD1sjH-C1SNcJY |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3fb9MwED5BQWg8MBhMBAZYiCeQtcRp7GRvFawaoqoiNqa9WbaTsEpdOjXpEH8A__fu8qMdCJAQD3lI4pwt--z7nDt_B_DGyigzcVbwwEjLhwiIufUz1_DeEjmIcg2X3ulETafx2VmSdnlOqz7avXdJtmcaiKWprPcvs2J_c_ANNZG2wYonaN-4vA13hpQziLbrx6f9Ukx7n8bdGYT0-1-u3Zq_E_GTYRq4auXQ3JxTdOQN6PmLt7QxQuPt_27-Q3jQ4U82ahXmEdzKyx3Y7rAo62Z6tQP3bxAVPoYfo_lX8jDPHDNlxlJDIV3E7c-OFxRaXTHEvgyxJEsp6xobzxffWNrmqjlgJ01obsU-IyjldOakETJybrU07jsnLaXxpfpnF106MbYo2GGToocqaWnVn8CX8eHJ-yPeJXDgDlFYzZWJYhHmvrWBCXOhAmuNzJSvCsRFcZhZJ4TLQymT2AiZFMRMo1SURUYEMrd-uAuDclHmT4FFuO2J4rBAORZlhzbKhe-UyGIUYMPIA78fPe06dnNKsjHXG15m6nSNna6p07X04O36k8uW2uPvhVElNJqhfOlMrYmWe31Dl_CV0CIJEJB58BoVZy2Uih6NJpqe4ZqZxMNIXQUe7PV6pbt1o9IIJIbE3ykTD971erR5_cfmPfun0q_gXvphrCcfp5-ewxZCwLg9XbkHg3q5yl_AXXdVz6rly2Y2XQON1hsQ |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Algebraic+and+Parametric+Solvers+for+the+Power+Flow+Problem%3A+Towards+Real-Time+and+Accuracy-Guaranteed+Simulation+of+Electric+Systems&rft.jtitle=Archives+of+computational+methods+in+engineering&rft.au=Garc%C3%ADa-Blanco%2C+Raquel&rft.au=D%C3%ADez%2C+Pedro&rft.au=Borzacchiello%2C+Domenico&rft.au=Chinesta%2C+Francisco&rft.date=2018-11-01&rft.issn=1134-3060&rft.eissn=1886-1784&rft.volume=25&rft.issue=4&rft.spage=1003&rft.epage=1026&rft_id=info:doi/10.1007%2Fs11831-017-9223-6&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s11831_017_9223_6 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1134-3060&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1134-3060&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1134-3060&client=summon |