Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language
The problem of the optimal reactive power flow in transmission systems is addressed in this research from the point of view of combinatorial optimization. A discrete-continuous version of the Chu & Beasley genetic algorithm (CBGA) is proposed to model continuous variables such as voltage outputs...
- Autores:
-
Bernal-Romero, David Lionel
Montoya, Oscar Danilo
Arias-Londoño, Andres
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10433
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10433
https://doi.org/10.3390/computers10110151
- Palabra clave:
- DigSILENT programming language
Optimal reactive power flow
Combinatorial optimization
Power losses minimization
Discrete-continuous codification
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| id |
UTB2_629513f5e8cfcf3dd93156ab04c0935a |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/10433 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.es_CO.fl_str_mv |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| title |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| spellingShingle |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language DigSILENT programming language Optimal reactive power flow Combinatorial optimization Power losses minimization Discrete-continuous codification LEMB |
| title_short |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| title_full |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| title_fullStr |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| title_full_unstemmed |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| title_sort |
Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language |
| dc.creator.fl_str_mv |
Bernal-Romero, David Lionel Montoya, Oscar Danilo Arias-Londoño, Andres |
| dc.contributor.author.none.fl_str_mv |
Bernal-Romero, David Lionel Montoya, Oscar Danilo Arias-Londoño, Andres |
| dc.subject.keywords.es_CO.fl_str_mv |
DigSILENT programming language Optimal reactive power flow Combinatorial optimization Power losses minimization Discrete-continuous codification |
| topic |
DigSILENT programming language Optimal reactive power flow Combinatorial optimization Power losses minimization Discrete-continuous codification LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
The problem of the optimal reactive power flow in transmission systems is addressed in this research from the point of view of combinatorial optimization. A discrete-continuous version of the Chu & Beasley genetic algorithm (CBGA) is proposed to model continuous variables such as voltage outputs in generators and reactive power injection in capacitor banks, as well as binary variables such as tap positions in transformers. The minimization of the total power losses is considered as the objective performance indicator. The main contribution in this research corresponds to the implementation of the CBGA in the DigSILENT Programming Language (DPL), which exploits the advantages of the power flow tool at a low computational effort. The solution of the optimal reactive power flow problem in power systems is a key task since the efficiency and secure operation of the whole electrical system depend on the adequate distribution of the reactive power in generators, transformers, shunt compensators, and transmission lines. To provide an efficient optimization tool for academics and power system operators, this paper selects the DigSILENT software, since this is widely used for power systems for industries and researchers. Numerical results in three IEEE test feeders composed of 6, 14, and 39 buses demonstrate the efficiency of the proposed CBGA in the DPL environment from DigSILENT to reduce the total grid power losses (between 21.17% to 37.62% of the benchmark case) considering four simulation scenarios regarding voltage regulation bounds and slack voltage outputs. In addition, the total processing times for the IEEE 6-, 14-, and 39-bus systems were 32.33 s, 49.45 s, and 138.88 s, which confirms the low computational effort of the optimization methods directly implemented in the DPL environment |
| publishDate |
2021 |
| dc.date.issued.none.fl_str_mv |
2021-11-12 |
| dc.date.accessioned.none.fl_str_mv |
2022-02-02T20:40:33Z |
| dc.date.available.none.fl_str_mv |
2022-02-02T20:40:33Z |
| dc.date.submitted.none.fl_str_mv |
2022-02-01 |
| 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 |
Bernal-Romero, D.L.; Montoya, O.D.; Arias-Londoño, A. Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language. Computers 2021, 10, 151. https://doi.org/10.3390/computers10110151 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10433 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.3390/computers10110151 |
| 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 |
Bernal-Romero, D.L.; Montoya, O.D.; Arias-Londoño, A. Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language. Computers 2021, 10, 151. https://doi.org/10.3390/computers10110151 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10433 https://doi.org/10.3390/computers10110151 |
| 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 |
24 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 |
Computers - vol. 10 n° 11 (2021) |
| institution |
Universidad Tecnológica de Bolívar |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/1/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/2/license_rdf https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/3/license.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/4/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/5/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf.jpg |
| bitstream.checksum.fl_str_mv |
21b1b6e46c953327c4c7fd45b7252c86 4460e5956bc1d1639be9ae6146a50347 e20ad307a1c5f3f25af9304a7a7c86b6 bcdf20235c466e006298d7e4d255719e 9e8677dd54493080dd6aae690189e985 |
| 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_ |
1814021805329874944 |
| spelling |
Bernal-Romero, David Lionel92b4db2c-95be-4502-bb3c-74213711c838Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Arias-Londoño, Andresb78c3735-f81d-45a4-ab64-b27983ba96672022-02-02T20:40:33Z2022-02-02T20:40:33Z2021-11-122022-02-01Bernal-Romero, D.L.; Montoya, O.D.; Arias-Londoño, A. Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language. Computers 2021, 10, 151. https://doi.org/10.3390/computers10110151https://hdl.handle.net/20.500.12585/10433https://doi.org/10.3390/computers10110151Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe problem of the optimal reactive power flow in transmission systems is addressed in this research from the point of view of combinatorial optimization. A discrete-continuous version of the Chu & Beasley genetic algorithm (CBGA) is proposed to model continuous variables such as voltage outputs in generators and reactive power injection in capacitor banks, as well as binary variables such as tap positions in transformers. The minimization of the total power losses is considered as the objective performance indicator. The main contribution in this research corresponds to the implementation of the CBGA in the DigSILENT Programming Language (DPL), which exploits the advantages of the power flow tool at a low computational effort. The solution of the optimal reactive power flow problem in power systems is a key task since the efficiency and secure operation of the whole electrical system depend on the adequate distribution of the reactive power in generators, transformers, shunt compensators, and transmission lines. To provide an efficient optimization tool for academics and power system operators, this paper selects the DigSILENT software, since this is widely used for power systems for industries and researchers. Numerical results in three IEEE test feeders composed of 6, 14, and 39 buses demonstrate the efficiency of the proposed CBGA in the DPL environment from DigSILENT to reduce the total grid power losses (between 21.17% to 37.62% of the benchmark case) considering four simulation scenarios regarding voltage regulation bounds and slack voltage outputs. In addition, the total processing times for the IEEE 6-, 14-, and 39-bus systems were 32.33 s, 49.45 s, and 138.88 s, which confirms the low computational effort of the optimization methods directly implemented in the DPL environment24 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_abf2Computers - vol. 10 n° 11 (2021)Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Languageinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1DigSILENT programming languageOptimal reactive power flowCombinatorial optimizationPower losses minimizationDiscrete-continuous codificationLEMBCartagena de IndiasMurty, P. Power Flow Studies. In Power Systems Analysis; Elsevier: Amsterdam, The Netherlands, 2017; pp. 205–276Alamri, B.; Hossain, M.A.; Asghar, M.S.J. Electric Power Network Interconnection: A Review on Current Status, Future Prospects and Research Direction. Electronics 2021, 10, 2179Lam, C.S.; Wong, M.C.; Han, Y.D. Voltage Swell and Overvoltage Compensation With Unidirectional Power Flow Controlled Dynamic Voltage Restorer. IEEE Trans. Power Deliv. 2008, 23, 2513–2521Montoya, O.D.; Fuentes, J.E.; Moya, F.D.; Barrios, J.Á.; Chamorro, H.R. Reduction of Annual Operational Costs in Power Systems through the Optimal Siting and Sizing of STATCOMs. Appl. Sci. 2021, 11, 4634Villa-Acevedo, W.; López-Lezama, J.; Valencia-Velásquez, J. A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem. Energies 2018, 11, 2352.Londoño, D.C.; Villa-Acevedo, W.M.; López-Lezama, J.M. Assessment of Metaheuristic Techniques Applied to the Optimal Reactive Power Dispatch. In Communications in Computer and Information Science; Springer International Publishing: New York, NY, USA, 2019; pp. 250–262Rojas, D.G.; Lezama, J.L.; Villa, W. Metaheuristic Techniques Applied to the Optimal Reactive Power Dispatch: A Review. IEEE Lat. Am. Trans. 2016, 14, 2253–2263.Ara, A.L.; Kazemi, A.; Gahramani, S.; Behshad, M. Optimal reactive power flow using multi-objective mathematical programming. Sci. Iran. 2012, 19, 1829–1836Duong, T.L.; Duong, M.Q.; Phan, V.D.; Nguyen, T.T. Optimal Reactive Power Flow for Large-Scale Power Systems Using an Effective Metaheuristic Algorithm. J. Electr. Comput. Eng. 2020, 2020, 6382507Aghbolaghi, A.J.; Tabatabaei, N.M.; Boushehri, N.S.; Parast, F.H. Reactive Power Optimization in AC Power Systems. In Power Systems; Springer International Publishing: New York, NY, USA, 2017; pp. 345–409Naderi, E.; Narimani, H.; Fathi, M.; Narimani, M.R. A novel fuzzy adaptive configuration of particle swarm optimization to solve large-scale optimal reactive power dispatch. Appl. Soft Comput. 2017, 53, 441–456Saddique, M.S.; Bhatti, A.R.; Haroon, S.S.; Sattar, M.K.; Amin, S.; Sajjad, I.A.; ul Haq, S.S.; Awan, A.B.; Rasheed, N. Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques—Status and technological review. Electr. Power Syst. Res. 2020, 178, 106031Zhao, J.; Zhang, Z.; Yao, J.; Yang, S.; Wang, K. A distributed optimal reactive power flow for global transmission and distribution network. Int. J. Electr. Power Energy Syst. 2019, 104, 524–536Yoshida, H.; Kawata, K.; Fukuyama, Y.; Takayama, S.; Nakanishi, Y. A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Trans. Power Syst. 2000, 15, 1232–1239.Esmin, A.; Lambert-Torres, G.; de Souza, A.Z. A hybrid particle swarm optimization applied to loss power minimization. IEEE Trans. Power Syst. 2005, 20, 859–866Mahadevan, K.; Kannan, P. Comprehensive learning particle swarm optimization for reactive power dispatch. Appl. Soft Comput. 2010, 10, 641–652. [Singh, R.P.; Mukherjee, V.; Ghoshal, S. Optimal reactive power dispatch by particle swarm optimization with an aging leader and challengers. Appl. Soft Comput. 2015, 29, 298–309.Gutiérrez, D.; Villa, W.M.; López-Lezama, J.M. Flujo Óptimo Reactivo mediante Optimización por Enjambre de Partículas. Inf. Tecnológica 2017, 28, 215–224Duman, S.; Sonmez, Y.; Guvencc, U.; Yorukeren, N. Optimal reactive power dispatch using a gravitational search algorithm. IET Gener. Transm. Distrib. 2012, 6, 563.Shaw, B.; Mukherjee, V.; Ghoshal, S. Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm. Int. J. Electr. Power Energy Syst. 2014, 55, 29–40Mei, R.N.S.; Sulaiman, M.H.; Mustaffa, Z.; Daniyal, H. Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique. Appl. Soft Comput. 2017, 59, 210–222Ela, A.A.E.; Abido, M.; Spea, S. Differential evolution algorithm for optimal reactive power dispatch. Electr. Power Syst. Res. 2011, 81, 458–464.. Bhongade, S.; Tomar, A.; Goigowal, S.R. Minimization of Optimal Reactive Power Dispatch Problem using BAT Algorithm. In Proceedings of the 2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control (STPEC), Online, 25–26 September 2020. Bakirtzis, A.; Biskas, P.; Zoumas, C.; Petridis, V. Optimal power flow by enhanced genetic algorithm. IEEE Trans. Power Syst. 2002, 17, 229–236.Abido, M.A. Optimal Power Flow Using Tabu Search Algorithm. Electr. Power Compon. Syst. 2002, 30, 469–483Lenin, K. Reduction of active power loss by improved tabu search algorithm. Int. J. Res.—GRANTHAALAYAH 2018, 6, 1–9ElSayed, S.K.; Elattar, E.E. Slime Mold Algorithm for Optimal Reactive Power Dispatch Combining with Renewable Energy Sources. Sustainability 2021, 13, 5831Ganesh, S.; Perilla, A.; Torres, J.R.; Palensky, P.; van der Meijden, M. Validation of EMT Digital Twin Models for Dynamic Voltage Performance Assessment of 66 kV Offshore Transmission Network. Appl. Sci. 2020, 11, 244Tabatabaei, N.M.; Aghbolaghi, A.J.; Boushehri, N.S.; Parast, F.H. Reactive Power Optimization Using MATLAB and DIgSILENT. In Power Systems; Springer International Publishing: New York, NY, USA, 2017; pp. 411–474Castiblanco-Pérez, C.M.; Toro-Rodríguez, D.E.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Placement and Sizing of DSTATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm. Electronics 2021, 10, 1452.Villena-Ruiz, R.; Honrubia-Escribano, A.; Fortmann, J.; Gómez-Lázaro, E. Field validation of a standard Type 3 wind turbine model implemented in DIgSILENT-PowerFactory following IEC 61400-27-1 guidelines. Int. J. Electr. Power Energy Syst. 2020, 116, 105553Bifaretti, S.; Bonaiuto, V.; Pipolo, S.; Terlizzi, C.; Zanchetta, P.; Gallinelli, F.; Alessandroni, S. Power Flow Management by Active Nodes: A Case Study in Real Operating Conditions. Energies 2021, 14, 4519.Barboza, L.V.; Ziirn, H.H.; Salgado, R. Load Tap Change Transformers: A Modeling Reminder. IEEE Power Eng. Rev. 2001, 21, 51–52Londoño-Tamayo, D.; Villa-Acevedo, J.L.L.W. Mean-Variance Mapping Optimization Algorithm Applied to the Optimal Reactive Power Dispatch. INGECUC 2021, 17, 239–255Sharif, S.; Taylor, J. MINLP formulation of optimal reactive power flow. In Proceedings of the 1997 American Control Conference (Cat. No.97CH36041), Albuquerque, NM, USA, 6 June 1997Morán-Burgos, J.A.; Sierra-Aguilar, J.E.; Villa-Acevedo, W.M.; López-Lezama, J.M. A Multi-Period Optimal Reactive Power Dispatch Approach Considering Multiple Operative Goals. Appl. Sci. 2021, 11, 8535DIgSILENT GmbH. DIgSILENT PowerFactory Version 15, User Manual; DIgSILENT GmbH: Gomaringen, Germany, 2014.Gaitán, L.F.; Gómez, J.D.; Rivas-Trujillo, E. Quasi-Dynamic Analysis of a Local Distribution System with Distributed Generation. Study Case: The IEEE 13 Node System. TecnoLógicas 2019, 22, 195–212.Cortés-Caicedo, B.; Avellaneda-Gómez, L.S.; Montoya, O.D.; Alvarado-Barrios, L.; Chamorro, H.R. Application of the Vortex Search Algorithm to the Phase-Balancing Problem in Distribution Systems. Energies 2021, 14, 128Gonzalez-Longatt, F.M.; Rueda, J.L. (Eds.) PowerFactory Applications for Power System Analysis; Springer International Publishing: New York, NY, USA, 2014http://purl.org/coar/resource_type/c_2df8fbb1ORIGINAL[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdf[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdfapplication/pdf1342009https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/1/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf21b1b6e46c953327c4c7fd45b7252c86MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXT[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdf.txt[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdf.txtExtracted texttext/plain77597https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/4/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf.txtbcdf20235c466e006298d7e4d255719eMD54THUMBNAIL[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdf.jpg[Art. 47] Solution of the Optimal Reactive Po_Oscar Danilo Montoya.pdf.jpgGenerated Thumbnailimage/jpeg101712https://repositorio.utb.edu.co/bitstream/20.500.12585/10433/5/%5bArt.%2047%5d%20Solution%20of%20the%20Optimal%20Reactive%20Po_Oscar%20Danilo%20Montoya.pdf.jpg9e8677dd54493080dd6aae690189e985MD5520.500.12585/10433oai:repositorio.utb.edu.co:20.500.12585/104332022-02-03 02:14:36.611Repositorio Institucional UTBrepositorioutb@utb.edu.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 |