Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs

The problem of the optimal siting and placement of static compensates (STATCOMs) in power systems is addressed in this paper from an exact mathematical optimization point of view. A mixed-integer nonlinear programming model to present the problem was developed with the aim of minimizing the annual o...

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Autores:
Montoya, Oscar Danilo
Fuentes, Jose Eduardo
Moya, Francisco David
Barrios, José Ángel
Chamorro, Harold R.
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:20.500.12585/10371
Acceso en línea:
https://hdl.handle.net/20.500.12585/10371
https://doi.org/10.3390/app11104634
Palabra clave:
Annual operative costs minimization
Electric power systems
Mathematical optimization
Mixed-integer nonlinear programming
Optimal power flow
Static compensators
LEMB
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openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
title Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
spellingShingle Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
Annual operative costs minimization
Electric power systems
Mathematical optimization
Mixed-integer nonlinear programming
Optimal power flow
Static compensators
LEMB
title_short Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
title_full Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
title_fullStr Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
title_full_unstemmed Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
title_sort Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMs
dc.creator.fl_str_mv Montoya, Oscar Danilo
Fuentes, Jose Eduardo
Moya, Francisco David
Barrios, José Ángel
Chamorro, Harold R.
dc.contributor.author.none.fl_str_mv Montoya, Oscar Danilo
Fuentes, Jose Eduardo
Moya, Francisco David
Barrios, José Ángel
Chamorro, Harold R.
dc.subject.keywords.spa.fl_str_mv Annual operative costs minimization
Electric power systems
Mathematical optimization
Mixed-integer nonlinear programming
Optimal power flow
Static compensators
topic Annual operative costs minimization
Electric power systems
Mathematical optimization
Mixed-integer nonlinear programming
Optimal power flow
Static compensators
LEMB
dc.subject.armarc.none.fl_str_mv LEMB
description The problem of the optimal siting and placement of static compensates (STATCOMs) in power systems is addressed in this paper from an exact mathematical optimization point of view. A mixed-integer nonlinear programming model to present the problem was developed with the aim of minimizing the annual operating costs of the power system, which is the sum of the costs of the energy losses and of the installation of the STATCOMs. The optimization model has constraints regarding the active and reactive power balance equations and those associated with the devices’ capabilities, among others. To characterize the electrical behavior of the power system, different load profiles such as residential, industrial, and commercial are considered for a period of 24 h of operation. The solution of the proposed model is reached with the general algebraic modeling system optimization package. The numerical results indicate the positive effect of the dynamic reactive power injections in the power systems on annual operating cost reduction. A Pareto front was built to present the multi-objective behavior of the studied problem when compared to investment and operative costs. The complete numerical validations are made in the IEEE 24-, IEEE 33-, and IEEE 69-bus systems, respectively.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-09-28T14:29:46Z
dc.date.available.none.fl_str_mv 2021-09-28T14:29:46Z
dc.date.issued.none.fl_str_mv 2021-04-17
dc.date.submitted.none.fl_str_mv 2021-09-27
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.citation.spa.fl_str_mv Montoya, 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, 4634. https://doi.org/10.3390/app11104634
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/10371
dc.identifier.doi.none.fl_str_mv https://doi.org/10.3390/app11104634
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Montoya, 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, 4634. https://doi.org/10.3390/app11104634
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/10371
https://doi.org/10.3390/app11104634
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.rights.accessrights.spa.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 18 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Appl. Sci. 2021, 11, 4634
institution Universidad Tecnológica de Bolívar
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spelling Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Fuentes, Jose Eduardo1015474b-238e-43e4-800c-c1fa9d66f1feMoya, Francisco David096b5df2-93da-46ad-ac99-025502e8f56bBarrios, José Ángel8afd8a99-e332-45ac-a2aa-6d555675de1aChamorro, Harold R.59e2dcd8-f603-4e1f-8459-da694d5a324d2021-09-28T14:29:46Z2021-09-28T14:29:46Z2021-04-172021-09-27Montoya, 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, 4634. https://doi.org/10.3390/app11104634https://hdl.handle.net/20.500.12585/10371https://doi.org/10.3390/app11104634Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe problem of the optimal siting and placement of static compensates (STATCOMs) in power systems is addressed in this paper from an exact mathematical optimization point of view. A mixed-integer nonlinear programming model to present the problem was developed with the aim of minimizing the annual operating costs of the power system, which is the sum of the costs of the energy losses and of the installation of the STATCOMs. The optimization model has constraints regarding the active and reactive power balance equations and those associated with the devices’ capabilities, among others. To characterize the electrical behavior of the power system, different load profiles such as residential, industrial, and commercial are considered for a period of 24 h of operation. The solution of the proposed model is reached with the general algebraic modeling system optimization package. The numerical results indicate the positive effect of the dynamic reactive power injections in the power systems on annual operating cost reduction. A Pareto front was built to present the multi-objective behavior of the studied problem when compared to investment and operative costs. The complete numerical validations are made in the IEEE 24-, IEEE 33-, and IEEE 69-bus systems, respectively.18 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_abf2Appl. Sci. 2021, 11, 4634Reduction of annual operational costs in power systems through the optimal siting and sizing of STATCOMsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Annual operative costs minimizationElectric power systemsMathematical optimizationMixed-integer nonlinear programmingOptimal power flowStatic compensatorsLEMBCartagena de IndiasInvestigadoresMazur, A. Does increasing energy or electricity consumption improve quality of life in industrial nations? Energy Policy 2011, 39, 2568–2572.Rao, N.D.; Pachauri, S. Energy access and living standards: Some observations on recent trends. Environ. Res. Lett. 2017, 12, 025011Gonzalez-Romero, I.C.; Wogrin, S.; Gómez, T. Review on generation and transmission expansion co-planning models under a market environment. IET Gener. Transm. Distrib. 2020, 14, 931–944Löhr, L.; Houben, R.; Moser, A. Optimal power and gas flow for large-scale transmission systems. Electr. Power Syst. Res. 2020, 189, 106724.Zhou, J.; Shi, P.; Gan, D.; Xu, Y.; Xin, H.; Jiang, C.; Xie, H.; Wu, T. Large-Scale Power System Robust Stability Analysis Based on Value Set Approach. IEEE Trans. Power Syst. 2017, 32, 4012–4023Khan, J.; Arsalan, M.H. Solar power technologies for sustainable electricity generation—A review. Renew. Sustain. Energy Rev. 2016, 55, 414–425Li, H.; Cui, H.; Li, C. Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations. Sustainability 2019, 11, 1311Montoya, O.D.; Serra, F.M.; Angelo, C.H.D. On the Efficiency in Electrical Networks with AC and DC Operation Technologies: A Comparative Study at the Distribution Stage. Electronics 2020, 9, 1352Ara, A.L.; Kazemi, A.; Gahramani, S.; Behshad, M. Optimal reactive power flow using multi-objective mathematical programming. Sci. Iran. 2012, 19, 1829–1836.Villa-Acevedo, W.; López-Lezama, J.; Valencia-Velásquez, J. A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem. Energies 2018, 11, 2352Montoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L.; Gil-González, W.; Orozco-Henao, C. Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs. Appl. Sci. 2021, 11, 3353Shahnia, F.; Rajakaruna, S.; Ghosh, A. (Eds.) Static Compensators (STATCOMs) in Power Systems; Springer: Singapore, 2015Valencia, 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, 102158Montoya, O.D.; Gil-González, W.; Rivas-Trujillo, E. Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids. Energies 2020, 13, 2289. [Xiao, J.; Zhang, Z.; Bai, L.; Liang, H. Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation. IET Gener. Transm. Distrib. 2016, 10, 601–607.Montoya, O.D.; Gil-González, W.; Hernández, J.C. Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA. Appl. Sci. 2021, 11, 2175Hamidi, S.A.; Ionel, D.M.; Nasiri, A. Modeling and Management of Batteries and Ultracapacitors for Renewable Energy Support in Electric Power Systems–An Overview. Electr. Power Components Syst. 2015, 43, 1434–1452Knutel, B.; Pierzy ´nska, A.; D ˛ebowski, M.; Bukowski, P.; Dyjakon, A. Assessment of Energy Storage from Photovoltaic Installations in Poland Using Batteries or Hydrogen. Energies 2020, 13, 4023Ma, Y.; Huang, A.; Zhou, X. A review of STATCOM on the electric power system. In Proceedings of the 2015 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, 2–5 August 2015. [Tareen, W.; Aamir, M.; Mekhilef, S.; Nakaoka, M.; Seyedmahmoudian, M.; Horan, B.; Memon, M.; Baig, N. Mitigation of Power Quality Issues Due to High Penetration of Renewable Energy Sources in Electric Grid Systems Using Three-Phase APF/STATCOM Technologies: A Review. Energies 2018, 11, 1491Abd-Elazim, S.; Ali, E. Optimal location of STATCOM in multimachine power system for increasing loadability by Cuckoo Search algorithm. Int. J. Electr. Power Energy Syst. 2016, 80, 240–251Dutta, S.; Roy, P.K.; Nandi, D. Optimal location of STATCOM using chemical reaction optimization for reactive power dispatch problem. Ain Shams Eng. J. 2016, 7, 233–247Sirjani, R. Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization. Sustainability 2018, 10, 727de Koster, O.A.C.; Domínguez-Navarro, J.A. Multi-Objective Tabu Search for the Location and Sizing of Multiple Types of FACTS and DG in Electrical Networks. Energies 2020, 13, 2722. [Yuvaraj, T.; Ravi, K.; Devabalaji, K. DSTATCOM allocation in distribution networks considering load variations using bat algorithm. Ain Shams Eng. J. 2017, 8, 391–403. [Kumar, D.; Bhowmik, P.S. Genetic Algorithm-based Optimal Placement of STATCOM in Pre-islanding and Post-islanding Condition. In Proceedings of the 2020 IEEE Calcutta Conference (CALCON), Kolkata, India, 28–29 February 2020Singh, B.; Singh, S. GA-based optimization for integration of DGs, STATCOM and PHEVs in distribution systems. Energy Rep. 2019, 5, 84–103. [Farhoodnea, M.; Mohamed, A.; Shareef, H.; Zayandehroodi, H. Optimum D-STATCOM placement using firefly algorithm for power quality enhancement. In Proceedings of the 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO), Langkawi, Malaysia, 3–4 June 2013Soroudi, A. Power System Optimization Modeling in GAMS; Springer International Publishing: Cham, Switzerland, 2017Naghiloo, A.; Abbaspour, M.; Mohammadi-Ivatloo, B.; Bakhtari, K. GAMS based approach for optimal design and sizing of a pressure retarded osmosis power plant in Bahmanshir river of Iran. Renew. Sustain. Energy Rev. 2015, 52, 1559–1565Chao, W.; Yao, Z. Approach on nonlinear control theory for designing STATCOM controller. In Proceedings of the 2007 IEEE International Conference on Grey Systems and Intelligent Services, Nanjing, China, 18–20 November 2007Javadi, M.; Amraee, T. Economic Dispatch: A Mixed-Integer Linear Model for Thermal Generating Units. In Proceedings of the 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Palermo, Italy, 12–15 June 2018.Saldarriaga-Zuluaga, S.D.; López-Lezama, J.M.; Mu noz-Galeano, N. Integrated Transmission and Generation Expansion Planning considering Safety Constraints. Inf. Tecnol. 2018, 29, 167–176Jonuzaj, S.; Gupta, A.; Adjiman, C.S. The design of optimal mixtures from atom groups using Generalized Disjunctive Programming. Comput. Chem. Eng. 2018, 116, 401–421He, H.; Chen, A.; Yin, M.; Ma, Z.; You, J.; Xie, X.; Wang, Z.; An, Q. Optimal Allocation Model of Water Resources Based on the Prospect Theory. Water 2019, 11, 1289Calasan, M.P.; Nikitovi´c, L.; Mujovi´c, S. CONOPT solver embedded in GAMS for optimal power flow. ´ J. Renew. Sustain. Energy 2019, 11, 046301Bocanegra, S.Y.; Montoya, O.D.; Molina-Cabrera, A. Parameter estimation in singe-phase transformers employing voltage and current measures. Rev. UIS Ing. 2020, 19, 63–75. (In SpanishMontoya, O.D.; Gil-González, W.; Grisales-Nore na, L. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Eng. J. 2020, 11, 409–418Morais, H.; Sousa, T.; Castro, R.; Vale, Z. Multi-Objective Electric Vehicles Scheduling Using Elitist Non-Dominated Sorting Genetic Algorithm. Appl. Sci. 2020, 10, 7978.Montoya, O.D.; Gil-González, W.; Grisales-Nore na, L.F. On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach. Electr. Power Syst. Res. 2021, 194, 107072.Molina-Martin, F.; Montoya, O.D.; Grisales-Nore na, L.F.; Hernández, J.C.; Ramírez-Vanegas, C.A. Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS. Electronics 2021, 10, 1002Buitrago-Velandia, A.F.; Montoya, O.D.; Gil-González, W. Dynamic Reactive Power Compensation in Power Systems through the Optimal Siting and Sizing of Photovoltaic Sources. Resources 2021, 10, 47Allen, B.D. Building and solving mathematical programming models in engineering and science by Enrique Castillo, Antonio J. Conejo, Pablo Pedregal, Ricardo Garcia, and Natalia Alguacil. J. Appl. Math. Stoch. Anal. 2002, 15, 389–391Marjani, S.R.; Talavat, V.; Galvani, S. Optimal allocation of D-STATCOM and reconfiguration in radial distribution network using MOPSO algorithm in TOPSIS framework. Int. Trans. Electr. Energy Syst. 2018, 29, e2723Sharma, A.K.; Saxena, A.; Tiwari, R. Optimal Placement of SVC Incorporating Installation Cost. Int. J. Hybrid Inf. Technol. 2016, 9, 289–302.Montoya, O.D.; Gil-González, W.; Grisales-Nore na, L. Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches. Int. J. Electr. Power Energy Syst. 2020, 115, 105442http://purl.org/coar/resource_type/c_2df8fbb1ORIGINAL[Art. 24] Reduction of Annual Operational Cos_Oscar Danilo Montoya.pdf[Art. 24] Reduction of Annual Operational Cos_Oscar Danilo Montoya.pdfapplication/pdf311876https://repositorio.utb.edu.co/bitstream/20.500.12585/10371/1/%5bArt.%2024%5d%20Reduction%20of%20Annual%20Operational%20Cos_Oscar%20Danilo%20Montoya.pdf3d3f43d34c4668b9c16eceecda735d62MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/10371/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/10371/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXT[Art. 24] Reduction of Annual Operational Cos_Oscar Danilo Montoya.pdf.txt[Art. 24] Reduction of Annual Operational Cos_Oscar Danilo Montoya.pdf.txtExtracted 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