On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks
The problem of the optimal siting and sizing of fixed-step capacitor banks is studied in this research from the standpoint of convex optimization. This problem is formulated through a mixed-integer nonlinear programming (MINLP) model, in which its binary/integer variables are related to the nodes wh...
- Autores:
-
Montoya, Oscar Danilo
Gil-González, Walter
Garcés, Alejandro
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10696
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10696
https:// doi.org/10.3390/computation10020032
- Palabra clave:
- Capacitor banks
Distribution networks
Second-order cone programming model
Power losses minimization
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
id |
UTB2_7f5dd7e33fca91799fe5e635abb47a46 |
---|---|
oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/10696 |
network_acronym_str |
UTB2 |
network_name_str |
Repositorio Institucional UTB |
repository_id_str |
|
dc.title.es_CO.fl_str_mv |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
title |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
spellingShingle |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks Capacitor banks Distribution networks Second-order cone programming model Power losses minimization LEMB |
title_short |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
title_full |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
title_fullStr |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
title_full_unstemmed |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
title_sort |
On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks |
dc.creator.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Garcés, Alejandro |
dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter Garcés, Alejandro |
dc.subject.keywords.es_CO.fl_str_mv |
Capacitor banks Distribution networks Second-order cone programming model Power losses minimization |
topic |
Capacitor banks Distribution networks Second-order cone programming model Power losses minimization LEMB |
dc.subject.armarc.none.fl_str_mv |
LEMB |
description |
The problem of the optimal siting and sizing of fixed-step capacitor banks is studied in this research from the standpoint of convex optimization. This problem is formulated through a mixed-integer nonlinear programming (MINLP) model, in which its binary/integer variables are related to the nodes where the capacitors will be installed. Simultaneously, the continuous variables are mainly associated with the power flow solution. The main contribution of this research is the reformulation of the exact MINLP model through a mixed-integer second-order cone programming model (MI-SOCP). This mixed-integer conic model maintains the nonlinearities of the original MINLP model; however, it can be solved efficiently with the branch & bound method combined with the interior point method adapted for conic programming models. The main advantage of the proposed MI-SOCP model is the possibility of finding the global optimum based on the convex nature of the power flow problem for each binary/integer variable combination in the branch & bound search tree. The numerical results in the IEEE 33- and IEEE 69-bus systems demonstrate the effectiveness and robustness of the proposed MI-SOCP model compared to different metaheuristic approaches. The MISOCP model finds the final power losses of the IEEE 33- and IEEE 69-bus systems of 138.416 kW and 145.397 kW, which improves the best literature results reached with the flower pollination algorithm, i.e., 139.075 kW, and 145.860 kW, respectively. The simulations are carried out in MATLAB software using its convex optimizer tool known as CVX with the Gurobi solver. |
publishDate |
2022 |
dc.date.accessioned.none.fl_str_mv |
2022-05-19T21:17:09Z |
dc.date.available.none.fl_str_mv |
2022-05-19T21:17:09Z |
dc.date.issued.none.fl_str_mv |
2022-02-20 |
dc.date.submitted.none.fl_str_mv |
2022-05-19 |
dc.type.driver.es_CO.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.hasVersion.es_CO.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
dc.type.spa.es_CO.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.identifier.citation.es_CO.fl_str_mv |
Montoya, O.D.; Gil-González, W.; Garcés, A. On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks. Computation 2022, 10, 32. https://doi.org/10.3390/computation10020032 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10696 |
dc.identifier.doi.none.fl_str_mv |
https:// doi.org/10.3390/computation10020032 |
dc.identifier.instname.es_CO.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.es_CO.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
identifier_str_mv |
Montoya, O.D.; Gil-González, W.; Garcés, A. On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks. Computation 2022, 10, 32. https://doi.org/10.3390/computation10020032 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
url |
https://hdl.handle.net/20.500.12585/10696 https:// doi.org/10.3390/computation10020032 |
dc.language.iso.es_CO.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessRights.es_CO.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.cc.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.none.fl_str_mv |
14 Páginas |
dc.format.mimetype.es_CO.fl_str_mv |
application/pdf |
dc.publisher.place.es_CO.fl_str_mv |
Cartagena de Indias |
dc.source.es_CO.fl_str_mv |
Computation - Vol. 10 N° 8 (2022). |
institution |
Universidad Tecnológica de Bolívar |
bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/2/license_rdf https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/1/computation-10-00032-v2.pdf https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/3/license.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/4/computation-10-00032-v2.pdf.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/5/computation-10-00032-v2.pdf.jpg |
bitstream.checksum.fl_str_mv |
4460e5956bc1d1639be9ae6146a50347 59f3d189d492df04b054983a35423d61 e20ad307a1c5f3f25af9304a7a7c86b6 41615919808037901aaa58fb8abd486c be4e21ebb68176a657f585d39b467f14 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional UTB |
repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
_version_ |
1814021588848214016 |
spelling |
Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a08Garcés, Alejandro1f6fb709-fba4-4fc8-9381-be1f0ca81b822022-05-19T21:17:09Z2022-05-19T21:17:09Z2022-02-202022-05-19Montoya, O.D.; Gil-González, W.; Garcés, A. On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networks. Computation 2022, 10, 32. https://doi.org/10.3390/computation10020032https://hdl.handle.net/20.500.12585/10696https:// doi.org/10.3390/computation10020032Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe problem of the optimal siting and sizing of fixed-step capacitor banks is studied in this research from the standpoint of convex optimization. This problem is formulated through a mixed-integer nonlinear programming (MINLP) model, in which its binary/integer variables are related to the nodes where the capacitors will be installed. Simultaneously, the continuous variables are mainly associated with the power flow solution. The main contribution of this research is the reformulation of the exact MINLP model through a mixed-integer second-order cone programming model (MI-SOCP). This mixed-integer conic model maintains the nonlinearities of the original MINLP model; however, it can be solved efficiently with the branch & bound method combined with the interior point method adapted for conic programming models. The main advantage of the proposed MI-SOCP model is the possibility of finding the global optimum based on the convex nature of the power flow problem for each binary/integer variable combination in the branch & bound search tree. The numerical results in the IEEE 33- and IEEE 69-bus systems demonstrate the effectiveness and robustness of the proposed MI-SOCP model compared to different metaheuristic approaches. The MISOCP model finds the final power losses of the IEEE 33- and IEEE 69-bus systems of 138.416 kW and 145.397 kW, which improves the best literature results reached with the flower pollination algorithm, i.e., 139.075 kW, and 145.860 kW, respectively. The simulations are carried out in MATLAB software using its convex optimizer tool known as CVX with the Gurobi solver.14 Páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Computation - Vol. 10 N° 8 (2022).On the Conic Convex Approximation to Locate and Size Fixed-Step Capacitor Banks in Distribution Networksinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Capacitor banksDistribution networksSecond-order cone programming modelPower losses minimizationLEMBCartagena de IndiasRidzuan, M.I.M.; Fauzi, N.F.M.; Roslan, N.N.R.; Saad, N.M. Urban and rural medium voltage networks reliability assessment. SN Appl. Sci. 2020, 2, 241Kien, L.C.; Nguyen, T.T.; Pham, T.D.; Nguyen, T.T. Cost reduction for energy loss and capacitor investment in radial distribution networks applying novel algorithms. Neural Comput. Appl. 2021, 33, 15495–15522.Riaño, F.E.; Cruz, J.F.; Montoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L. Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization. Electronics 2021, 10, 419Lavorato, M.; Franco, J.F.; Rider, M.J.; Romero, R. Imposing Radiality Constraints in Distribution System Optimization Problems. IEEE Trans. Power Syst. 2012, 27, 172–180.Paz-Rodríguez, A.; Castro-Ordoñez, J.F.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm. Appl. Sci. 2021, 11, 4418Águila, A.; Ortiz, L.; Orizondo, R.; López, G. Optimal location and dimensioning of capacitors in microgrids using a multicriteria decision algorithm. Heliyon 2021, 7, e08061Madruga, E.P.; Canha, L.N. Allocation and integrated configuration of capacitor banks and voltage regulators considering multi-objective variables in smart grid distribution system. In Proceedings of the 2010 9th IEEE/IAS International Conference on Industry Applications—INDUSCON 2010, Sao Paulo, Brazil, 8–10 November 2010Pareja, L.A.G.; Lezama, J.M.L.; Carmona, O.G. Optimal Placement of Capacitors, Voltage Regulators, and Distributed Generators in Electric Power Distribution Systems. Ingeniería 2020, 25, 334–354Mishra, S.; Das, D.; Paul, S. A comprehensive review on power distribution network reconfiguration. Energy Syst. 2016, 8, 227–284.Dhivya, S.; Arul, R. Demand Side Management Studies on Distributed Energy Resources: A Survey. Trans. Energy Syst. Eng. Appl. 2021, 2, 17–31. [Valencia, A.; Hincapie, R.A.; Gallego, R.A. Optimal location, selection, and operation of battery energy storage systems and renewable distributed generation in medium–low voltage distribution networks. J. Energy Storage 2021, 34, 102158Sirjani, R.; Jordehi, A.R. Optimal placement and sizing of distribution static compensator (D-STATCOM) in electric distribution networks: A review. Renew. Sustain. Energy Rev. 2017, 77, 688–694.. Tamilselvan, V.; Jayabarathi, T.; Raghunathan, T.; Yang, X.S. Optimal capacitor placement in radial distribution systems using flower pollination algorithm. Alex. Eng. J. 2018, 57, 2775–2786.Gil-González, W.; Montoya, O.D.; Rajagopalan, A.; Grisales-Noreña, L.F.; Hernández, J.C. Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm. Energies 2020, 13, 4914Griot, S.; Moreau, A. Vacuum circuit breakers electrical life for shunt capacitor switching. In Proceedings of the 24th ISDEIV 2010, Braunschweig, Germany, 30 August–3 September 2010.Velásquez, R.M.A.; Lara, J.V.M. Reliability, availability and maintainability study for failure analysis in series capacitor bank. Eng. Fail. Anal. 2018, 86, 158–167.Benson, H.Y.; Sa ˘glam, Ü. Mixed-Integer Second-Order Cone Programming: A Survey. In Theory Driven by Influential Applications; INFORMS: Catonsville, MD, USA, 2013; pp. 13–36Abdelaziz, A.Y.; Ali, E.S.; Elazim, S.M.A. Flower Pollination Algorithm for Optimal Capacitor Placement and Sizing in Distribution Systems. Electr. Power Components Syst. 2016, 44, 544–555.Abril, I.P. Capacitors placement in distribution systems with nonlinear load by using the variables’ inclusion and interchange algorithm. Dyna 2021, 88, 13–22Augugliaro, A.; Dusonchet, L.; Favuzza, S.; Ippolito, M.G.; Mangione, S.; Sanseverino, E.R. A Modified Genetic Algorithm for Optimal Allocation of Capacitor Banks in MV Distribution Networks. Intell. Ind. Syst. 2015, 1, 201–212.El-Fergany, A.A.; Abdelaziz, A.Y. Capacitor placement for net saving maximization and system stability enhancement in distribution networks using artificial bee colony-based approach. Int. J. Electr. Power Energy Syst. 2014, 54, 235–243.Prakash, K.; Sydulu, M. Particle Swarm Optimization Based Capacitor Placement on Radial Distribution Systems. In Proceedings of the 2007 IEEE Power Engineering Society General Meeting, Tampa, FL, USA, 24–28 June 2007Ogita, Y.; Mori, H. Parallel Dual Tabu Search for Capacitor Placement in Smart Grids. Procedia Comput. Sci. 2012, 12, 307–313.Shuaib, Y.M.; Kalavathi, M.S.; Rajan, C.C.A. Optimal capacitor placement in radial distribution system using Gravitational Search Algorithm. Int. J. Electr. Power Energy Syst. 2015, 64, 384–397.Devabalaji, K.; Yuvaraj, T.; Ravi, K. An efficient method for solving the optimal sitting and sizing problem of capacitor banks based on cuckoo search algorithm. Ain Shams Eng. J. 2018, 9, 589–597.Heliodore, F.; Nakib, A.; Ismail, B.; Ouchraa, S.; Schmitt, L. Performance Evaluation of Metaheuristics. In Metaheuristics for Intelligent Electrical Networks; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2017; pp. 43–58.Rocktäschel, S. A basic Branch-and-Bound algorithm for (MOMICP). In A Branch-and-Bound Algorithm for Multiobjective Mixedinteger Convex Optimization; Springer Fachmedien Wiesbaden: Berlin/Heidelberg, Germany, 2020; pp. 17–39Borchers, B.; Mitchell, J.E. An improved branch and bound algorithm for mixed integer nonlinear programs. Comput. Oper. Res. 1994, 21, 359–367YUAN, Z.; Hesamzadeh, M.R. Second-order cone AC optimal power flow: Convex relaxations and feasible solutions. J. Mod Power Syst. Clean Energy 2018, 7, 268–280.Kaur, S.; Kumbhar, G.; Sharma, J. A MINLP technique for optimal placement of multiple DG units in distribution systems. Int. J. Electr. Power Energy Syst. 2014, 63, 609–617.Kumar, D.; Singh, A.; Kansal, S. To Improve the Voltage Profile of Distribution System with the Optimal Placement of Capacitor. Indian J. Sci. Technol. 2017, 10, 1–7Molina-Martin, F.; Montoya, O.D.; Grisales-Noreña, L.F.; Hernández, J.C. A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks. Electronics 2021, 10, 176Garces, A.; Gil-González, W.; Montoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L. A Mixed-Integer Quadratic Formulation of the Phase-Balancing Problem in Residential Microgrids. Appl. Sci. 2021, 11, 1972.. Alizadeh, F.; Goldfarb, D. Second-order cone programming. Math. Program. 2003, 95, 3–51. [Karmarkar, N. A new polynomial-time algorithm for linear programming. Combinatorica 1984, 4, 373–395Atamtürk, A.; Gómez, A. Submodularity in Conic Quadratic Mixed Optimization. Oper. Res. 2020.. Grant, M.; Boyd, S. CVX: Matlab Software for Disciplined Convex Programming, Version 2.1. 2014. Available online: http: //cvxr.com/cvx (accessed on 3 July 2021).Abul’Wafa, A.R. Optimal capacitor allocation in radial distribution systems for loss reduction: A two stage method. Electr. Power Syst. Res. 2013, 95, 168–174.Abul’Wafa, A.R. Optimal capacitor placement for enhancing voltage stability in distribution systems using analytical algorithm and Fuzzy-Real Coded GA. Int. J. Electr. Power Energy Syst. 2014, 55, 246–252.Sultana, S.; Roy, P.K. Optimal capacitor placement in radial distribution systems using teaching learning based optimization. Int. J. Electr. Power Energy Syst. 2014, 54, 387–398.http://purl.org/coar/resource_type/c_2df8fbb1CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52ORIGINALcomputation-10-00032-v2.pdfcomputation-10-00032-v2.pdfapplication/pdf357987https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/1/computation-10-00032-v2.pdf59f3d189d492df04b054983a35423d61MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXTcomputation-10-00032-v2.pdf.txtcomputation-10-00032-v2.pdf.txtExtracted texttext/plain46903https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/4/computation-10-00032-v2.pdf.txt41615919808037901aaa58fb8abd486cMD54THUMBNAILcomputation-10-00032-v2.pdf.jpgcomputation-10-00032-v2.pdf.jpgGenerated Thumbnailimage/jpeg97091https://repositorio.utb.edu.co/bitstream/20.500.12585/10696/5/computation-10-00032-v2.pdf.jpgbe4e21ebb68176a657f585d39b467f14MD5520.500.12585/10696oai:repositorio.utb.edu.co:20.500.12585/106962022-05-20 00:18:22.09Repositorio Institucional UTBrepositorioutb@utb.edu.coQXV0b3Jpem8gKGF1dG9yaXphbW9zKSBhIGxhIEJpYmxpb3RlY2EgZGUgbGEgSW5zdGl0dWNpw7NuIHBhcmEgcXVlIGluY2x1eWEgdW5hIGNvcGlhLCBpbmRleGUgeSBkaXZ1bGd1ZSBlbiBlbCBSZXBvc2l0b3JpbyBJbnN0aXR1Y2lvbmFsLCBsYSBvYnJhIG1lbmNpb25hZGEgY29uIGVsIGZpbiBkZSBmYWNpbGl0YXIgbG9zIHByb2Nlc29zIGRlIHZpc2liaWxpZGFkIGUgaW1wYWN0byBkZSBsYSBtaXNtYSwgY29uZm9ybWUgYSBsb3MgZGVyZWNob3MgcGF0cmltb25pYWxlcyBxdWUgbWUobm9zKSBjb3JyZXNwb25kZShuKSB5IHF1ZSBpbmNsdXllbjogbGEgcmVwcm9kdWNjacOzbiwgY29tdW5pY2FjacOzbiBww7pibGljYSwgZGlzdHJpYnVjacOzbiBhbCBww7pibGljbywgdHJhbnNmb3JtYWNpw7NuLCBkZSBjb25mb3JtaWRhZCBjb24gbGEgbm9ybWF0aXZpZGFkIHZpZ2VudGUgc29icmUgZGVyZWNob3MgZGUgYXV0b3IgeSBkZXJlY2hvcyBjb25leG9zIHJlZmVyaWRvcyBlbiBhcnQuIDIsIDEyLCAzMCAobW9kaWZpY2FkbyBwb3IgZWwgYXJ0IDUgZGUgbGEgbGV5IDE1MjAvMjAxMiksIHkgNzIgZGUgbGEgbGV5IDIzIGRlIGRlIDE5ODIsIExleSA0NCBkZSAxOTkzLCBhcnQuIDQgeSAxMSBEZWNpc2nDs24gQW5kaW5hIDM1MSBkZSAxOTkzIGFydC4gMTEsIERlY3JldG8gNDYwIGRlIDE5OTUsIENpcmN1bGFyIE5vIDA2LzIwMDIgZGUgbGEgRGlyZWNjacOzbiBOYWNpb25hbCBkZSBEZXJlY2hvcyBkZSBhdXRvciwgYXJ0LiAxNSBMZXkgMTUyMCBkZSAyMDEyLCBsYSBMZXkgMTkxNSBkZSAyMDE4IHkgZGVtw6FzIG5vcm1hcyBzb2JyZSBsYSBtYXRlcmlhLgoKQWwgcmVzcGVjdG8gY29tbyBBdXRvcihlcykgbWFuaWZlc3RhbW9zIGNvbm9jZXIgcXVlOgoKLSBMYSBhdXRvcml6YWNpw7NuIGVzIGRlIGNhcsOhY3RlciBubyBleGNsdXNpdmEgeSBsaW1pdGFkYSwgZXN0byBpbXBsaWNhIHF1ZSBsYSBsaWNlbmNpYSB0aWVuZSB1bmEgdmlnZW5jaWEsIHF1ZSBubyBlcyBwZXJwZXR1YSB5IHF1ZSBlbCBhdXRvciBwdWVkZSBwdWJsaWNhciBvIGRpZnVuZGlyIHN1IG9icmEgZW4gY3VhbHF1aWVyIG90cm8gbWVkaW8sIGFzw60gY29tbyBsbGV2YXIgYSBjYWJvIGN1YWxxdWllciB0aXBvIGRlIGFjY2nDs24gc29icmUgZWwgZG9jdW1lbnRvLgoKLSBMYSBhdXRvcml6YWNpw7NuIHRlbmRyw6EgdW5hIHZpZ2VuY2lhIGRlIGNpbmNvIGHDsW9zIGEgcGFydGlyIGRlbCBtb21lbnRvIGRlIGxhIGluY2x1c2nDs24gZGUgbGEgb2JyYSBlbiBlbCByZXBvc2l0b3JpbywgcHJvcnJvZ2FibGUgaW5kZWZpbmlkYW1lbnRlIHBvciBlbCB0aWVtcG8gZGUgZHVyYWNpw7NuIGRlIGxvcyBkZXJlY2hvcyBwYXRyaW1vbmlhbGVzIGRlbCBhdXRvciB5IHBvZHLDoSBkYXJzZSBwb3IgdGVybWluYWRhIHVuYSB2ZXogZWwgYXV0b3IgbG8gbWFuaWZpZXN0ZSBwb3IgZXNjcml0byBhIGxhIGluc3RpdHVjacOzbiwgY29uIGxhIHNhbHZlZGFkIGRlIHF1ZSBsYSBvYnJhIGVzIGRpZnVuZGlkYSBnbG9iYWxtZW50ZSB5IGNvc2VjaGFkYSBwb3IgZGlmZXJlbnRlcyBidXNjYWRvcmVzIHkvbyByZXBvc2l0b3Jpb3MgZW4gSW50ZXJuZXQgbG8gcXVlIG5vIGdhcmFudGl6YSBxdWUgbGEgb2JyYSBwdWVkYSBzZXIgcmV0aXJhZGEgZGUgbWFuZXJhIGlubWVkaWF0YSBkZSBvdHJvcyBzaXN0ZW1hcyBkZSBpbmZvcm1hY2nDs24gZW4gbG9zIHF1ZSBzZSBoYXlhIGluZGV4YWRvLCBkaWZlcmVudGVzIGFsIHJlcG9zaXRvcmlvIGluc3RpdHVjaW9uYWwgZGUgbGEgSW5zdGl0dWNpw7NuLCBkZSBtYW5lcmEgcXVlIGVsIGF1dG9yKHJlcykgdGVuZHLDoW4gcXVlIHNvbGljaXRhciBsYSByZXRpcmFkYSBkZSBzdSBvYnJhIGRpcmVjdGFtZW50ZSBhIG90cm9zIHNpc3RlbWFzIGRlIGluZm9ybWFjacOzbiBkaXN0aW50b3MgYWwgZGUgbGEgSW5zdGl0dWNpw7NuIHNpIGRlc2VhIHF1ZSBzdSBvYnJhIHNlYSByZXRpcmFkYSBkZSBpbm1lZGlhdG8uCgotIExhIGF1dG9yaXphY2nDs24gZGUgcHVibGljYWNpw7NuIGNvbXByZW5kZSBlbCBmb3JtYXRvIG9yaWdpbmFsIGRlIGxhIG9icmEgeSB0b2RvcyBsb3MgZGVtw6FzIHF1ZSBzZSByZXF1aWVyYSBwYXJhIHN1IHB1YmxpY2FjacOzbiBlbiBlbCByZXBvc2l0b3Jpby4gSWd1YWxtZW50ZSwgbGEgYXV0b3JpemFjacOzbiBwZXJtaXRlIGEgbGEgaW5zdGl0dWNpw7NuIGVsIGNhbWJpbyBkZSBzb3BvcnRlIGRlIGxhIG9icmEgY29uIGZpbmVzIGRlIHByZXNlcnZhY2nDs24gKGltcHJlc28sIGVsZWN0csOzbmljbywgZGlnaXRhbCwgSW50ZXJuZXQsIGludHJhbmV0LCBvIGN1YWxxdWllciBvdHJvIGZvcm1hdG8gY29ub2NpZG8gbyBwb3IgY29ub2NlcikuCgotIExhIGF1dG9yaXphY2nDs24gZXMgZ3JhdHVpdGEgeSBzZSByZW51bmNpYSBhIHJlY2liaXIgY3VhbHF1aWVyIHJlbXVuZXJhY2nDs24gcG9yIGxvcyB1c29zIGRlIGxhIG9icmEsIGRlIGFjdWVyZG8gY29uIGxhIGxpY2VuY2lhIGVzdGFibGVjaWRhIGVuIGVzdGEgYXV0b3JpemFjacOzbi4KCi0gQWwgZmlybWFyIGVzdGEgYXV0b3JpemFjacOzbiwgc2UgbWFuaWZpZXN0YSBxdWUgbGEgb2JyYSBlcyBvcmlnaW5hbCB5IG5vIGV4aXN0ZSBlbiBlbGxhIG5pbmd1bmEgdmlvbGFjacOzbiBhIGxvcyBkZXJlY2hvcyBkZSBhdXRvciBkZSB0ZXJjZXJvcy4gRW4gY2FzbyBkZSBxdWUgZWwgdHJhYmFqbyBoYXlhIHNpZG8gZmluYW5jaWFkbyBwb3IgdGVyY2Vyb3MgZWwgbyBsb3MgYXV0b3JlcyBhc3VtZW4gbGEgcmVzcG9uc2FiaWxpZGFkIGRlbCBjdW1wbGltaWVudG8gZGUgbG9zIGFjdWVyZG9zIGVzdGFibGVjaWRvcyBzb2JyZSBsb3MgZGVyZWNob3MgcGF0cmltb25pYWxlcyBkZSBsYSBvYnJhIGNvbiBkaWNobyB0ZXJjZXJvLgoKLSBGcmVudGUgYSBjdWFscXVpZXIgcmVjbGFtYWNpw7NuIHBvciB0ZXJjZXJvcywgZWwgbyBsb3MgYXV0b3JlcyBzZXLDoW4gcmVzcG9uc2FibGVzLCBlbiBuaW5nw7puIGNhc28gbGEgcmVzcG9uc2FiaWxpZGFkIHNlcsOhIGFzdW1pZGEgcG9yIGxhIGluc3RpdHVjacOzbi4KCi0gQ29uIGxhIGF1dG9yaXphY2nDs24sIGxhIGluc3RpdHVjacOzbiBwdWVkZSBkaWZ1bmRpciBsYSBvYnJhIGVuIMOtbmRpY2VzLCBidXNjYWRvcmVzIHkgb3Ryb3Mgc2lzdGVtYXMgZGUgaW5mb3JtYWNpw7NuIHF1ZSBmYXZvcmV6Y2FuIHN1IHZpc2liaWxpZGFkCgo= |