Mostrar el registro sencillo del ítem

dc.contributor.authorGrisales-Noreña, Luis Fernando
dc.contributor.authorMontoya, Oscar Danilo
dc.contributor.authorCortés-Caicedo, Brandon
dc.contributor.authorZishan, Farhad
dc.contributor.authorRosero-García, Javier
dc.coverage.spatialColombia
dc.date.accessioned2023-05-05T19:25:09Z
dc.date.available2023-05-05T19:25:09Z
dc.date.issued2023-01-16
dc.date.submitted2023-05-05
dc.identifier.citationGrisales-Noreña, L.F.; Montoya, O.D.; Cortés-Caicedo, B.; Zishan, F.; Rosero-García, J. Optimal Power Dispatch of PV Generators in AC Distribution Networks by Considering Solar, Environmental, and Power Demand Conditions from Colombia. Mathematics 2023, 11, 484. https://doi.org/10.3390/math11020484spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/11840
dc.description.abstractThis paper deals with the problem regarding the optimal operation of photovoltaic (PV) generation sources in AC distribution networks with a single-phase structure, taking into consid eration different objective functions. The problem is formulated as a multi-period optimal power flow applied to AC distribution grids, which generates a nonlinear programming (NLP) model with a non-convex structure. Three different objective functions are considered in the optimization model, each optimized using a single-objective function approach. These objective functions are (i) an operating costs function composed of the energy purchasing costs at the substation bus, added with the PV maintenance costs; (ii) the costs of energy losses; and (iii) the total CO2 emissions at the substation bus. All these functions are minimized while considering a frame of operation of 24 h, i.e., in a day-ahead operation environment. To solve the NLP model representing the studied problem, the General Algebraic Modeling System (GAMS) and its SNOPT solver are used. Two different test feeders are used for all the numerical validations, one of them adapted to the urban operation characteristics in the Metropolitan Area of Medellín, which is composed of 33 nodes, and the other one adapted to isolated rural operating conditions, which has 27 nodes and is located in the department of Chocó, Colombia (municipality of Capurganá). Numerical comparisons with multiple combinatorial optimization methods (particle swarm optimization, the continuous genetic algorithm, the Vortex Search algorithm, and the Ant Lion Optimizer) demonstrate the effectiveness of the GAMS software to reach the optimal day-ahead dispatch of all the PV sources in both distribution grids.spa
dc.format.extent20 Páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceMathematics Vol. 11 No. 2 (2023)spa
dc.titleOptimal Power Dispatch of PV Generators in AC Distribution Networks by Considering Solar, Environmental, and Power Demand Conditions from Colombiaspa
dcterms.bibliographicCitationAhmed, I.; Rehan, M.; Basit, A.; Hong, K.S. Greenhouse gases emission reduction for electric power generation sector by efficient dispatching of thermal plants integrated with renewable systems. Sci. Rep. 2022, 12, 12380.spa
dcterms.bibliographicCitationakhrani, A.Q.; Othman, A.K.; Rigit, A.R.H.; Samo, S.R. Estimation of carbon footprints from diesel generator emissions. In Proceedings of the 2012 International Conference on Green and Ubiquitous Technology, Besancon, France, 20–23 November 2012.spa
dcterms.bibliographicCitationIssa, M.; Ibrahim, H.; Hosni, H.; Ilinca, A.; Rezkallah, M. Effects of Low Charge and Environmental Conditions on Diesel Generators Operation. Eng 2020, 1, 137–152.spa
dcterms.bibliographicCitationYang, L.; Sun, Q.; Zhang, N.; Li, Y. Indirect Multi-Energy Transactions of Energy Internet With Deep Reinforcement Learning Approach. IEEE Trans. Power Syst. 2022, 37, 4067–4077.spa
dcterms.bibliographicCitationAhmad, L.; Khordehgah, N.; Malinauskaite, J.; Jouhara, H. Recent advances and applications of solar photovoltaics and thermal technologies. Energy 2020, 207, 118254.spa
dcterms.bibliographicCitationTan, J.D.; Chang, C.C.W.; Bhuiyan, M.A.S.; Minhad, K.N.; Ali, K. Advancements of wind energy conversion systems for low-wind urban environments: A review. Energy Rep. 2022, 8, 3406–3414.spa
dcterms.bibliographicCitationZhang, N.; Sun, Q.; Yang, L.; Li, Y. Event-Triggered Distributed Hybrid Control Scheme for the Integrated Energy System. IEEE Trans. Ind. Inform. 2022, 18, 835–846spa
dcterms.bibliographicCitationAybar-Mejía, M.; Villanueva, J.; Mariano-Hernández, D.; Santos, F.; Molina-García, A. A Review of Low-Voltage Renewable Microgrids: Generation Forecasting and Demand-Side Management Strategies. Electronics 2021, 10, 2093spa
dcterms.bibliographicCitationShafiullah, G. Impacts of renewable energy integration into the high voltage (HV) networks. In Proceedings of the 2016 4th International Conference on the Development in the in Renewable Energy Technology (ICDRET), Shenzhen, China, 30–31 December 2016spa
dcterms.bibliographicCitationZheng, H.; Yuan, X.; Cai, J.; Sun, P.; Zhou, L. Large-Signal Stability Analysis of DC Side of VSC-HVDC System Based on Estimation of Domain of Attraction. IEEE Trans. Power Syst. 2022, 37, 3630–3641.spa
dcterms.bibliographicCitationSurinkaew, T.; Ngamroo, I. Coordinated Robust Control of DFIG Wind Turbine and PSS for Stabilization of Power Oscillations Considering System Uncertainties. IEEE Trans. Sustain. Energy 2014, 5, 823–833.spa
dcterms.bibliographicCitationLópez, A.R.; Krumm, A.; Schattenhofer, L.; Burandt, T.; Montoya, F.C.; Oberländer, N.; Oei, P.Y. Solar PV generation in Colombia - A qualitative and quantitative approach to analyze the potential of solar energy market. Renew. Energy 2020, 148, 1266–1279.spa
dcterms.bibliographicCitationMontoya, O.D.; Grisales-Noreña, L.F.; Perea-Moreno, A.J. Optimal Investments in PV Sources for Grid-Connected Distribution Networks: An Application of the Discrete–Continuous Genetic Algorithm. Sustainability 2021, 13, 13633spa
dcterms.bibliographicCitationSaidi, A.S. Impact of grid-tied photovoltaic systems on voltage stability of tunisian distribution networks using dynamic reactive power control. Ain Shams Eng. J. 2022, 13, 101537spa
dcterms.bibliographicCitationSchultz, H.S.; Carvalho, M. Design, Greenhouse Emissions, and Environmental Payback of a Photovoltaic Solar Energy System. Energies 2022, 15, 6098spa
dcterms.bibliographicCitationValencia, 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, 102158spa
dcterms.bibliographicCitationMontoya, O.D.; Ramos-Paja, C.A.; Grisales-Noreña, L.F. An Efficient Methodology for Locating and Sizing PV Generators in Radial Distribution Networks Using a Mixed-Integer Conic Relaxation. Mathematics 2022, 10, 2626.spa
dcterms.bibliographicCitationCortés-Caicedo, B.; Molina-Martin, F.; Grisales-Noreña, L.F.; Montoya, O.D.; Hernández, J.C. Optimal Design of PV Systems in Electrical Distribution Networks by Minimizing the Annual Equivalent Operative Costs through the Discrete-Continuous Vortex Search Algorithm. Sensors 2022, 22, 851spa
dcterms.bibliographicCitationPal, P.; Krishnamoorthy, P.A.; Rukmani, D.K.; Antony, S.J.; Ocheme, S.; Subramanian, U.; Elavarasan, R.M.; Das, N.; Hasanien, H.M. Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework. Appl. Sci. 2021, 11, 3814spa
dcterms.bibliographicCitationNASA. NASA Prediction of Worldwide Energy Resources. Available online: https://power.larc.nasa.gov/ (accessed on 21 September 2022).spa
dcterms.bibliographicCitationInstituto de Planificación y Promoción de Soluciones Energéticas para Zonas No Interconectadas. Informes Mensuales de Telimetría, Colombia. Available online: https://ipse.gov.co/cnm/informe-mensuales-telemetria/ (accessed on 21 September 2022).spa
dcterms.bibliographicCitationXM SA ESP. Sinergox Database, Colombia. Available online: https://sinergox.xm.com.co/Paginas/Home.aspx (accessed on 21 September 2022)spa
dcterms.bibliographicCitationZagirnyak, M.; Rodkin, D.; Romashykhin, I. The possibilities of Tellegen’s theorem in the identification electrotechnical problems. In Proceedings of the 2017 International Conference on Modern Electrical and Energy Systems (MEES), Kremenchuk, Ukraine, 15–17 November 2017spa
dcterms.bibliographicCitationEl-Sobky, B.; Abo-Elnaga, Y.; Mousa, A.A.A.; El-Shorbagy, M.A. Trust-Region Based Penalty Barrier Algorithm for Constrained Nonlinear Programming Problems: An Application of Design of Minimum Cost Canal Sections. Mathematics 2021, 9, 1551.spa
dcterms.bibliographicCitationGrisales-Noreña, L.F.; Rosales-Mu noz, A.A.; Cortés-Caicedo, B.; Montoya, O.D.; Andrade, F. Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow. Mathematics 2022, 11, 93spa
dcterms.bibliographicCitationMontoya, O.D.; Gil-González, W. Dynamic active and reactive power compensation in distribution networks with batteries: A day-ahead economic dispatch approach. Comput. Electr. Eng. 2020, 85, 106710.spa
dcterms.bibliographicCitationNaghiloo, 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, 1559–1565spa
dcterms.bibliographicCitationSoroudi, A. Power System Optimization Modeling in GAMS; Springer International Publishing: Berlin/Heidelberg, Germany, 2017.spa
dcterms.bibliographicCitationMontoya, O.D.; Gil-González, W.; Grisales-Noreña, 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, 409–418spa
dcterms.bibliographicCitationKaur, 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.spa
dcterms.bibliographicCitationTartibu, L.; Sun, B.; Kaunda, M. Multi-objective optimization of the stack of a thermoacoustic engine using GAMS. Appl. Soft Comput. 2015, 28, 30–43spa
dcterms.bibliographicCitationSkworcow, P.; Paluszczyszyn, D.; Ulanicki, B.; Rudek, R.; Belrain, T. Optimisation of Pump and Valve Schedules in Complex Large-scale Water Distribution Systems Using GAMS Modelling Language. Procedia Eng. 2014, 70, 1566–1574.spa
dcterms.bibliographicCitationBocanegra, S.Y.; Montoya, O.D.; Molina-Cabrera, A. Parameter estimation in singe-phase transformers employing voltage and current measures (In Spanish). Rev. Uis Ing. 2020, 19, 63–75spa
dcterms.bibliographicCitationDubey, S.; Sarvaiya, J.N.; Seshadri, B. Temperature Dependent Photovoltaic (PV) Efficiency and Its Effect on PV Production in the World—A Review. Energy Procedia 2013, 33, 311–321.spa
dcterms.bibliographicCitationJaya, S.; Vijay, A.S.; Khan, I.; Shukla, A.; Doolla, S. Mode Transition in DC Microgrids with Non-Dispatchable Sources. In Proceedings of the 2021 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, Vancouver, BC, Canada, 10–14 October 2021.spa
dcterms.bibliographicCitationRamirez-Vergara, J.; Bosman, L.B.; Leon-Salas, W.D.; Wollega, E. Ambient temperature and solar irradiance forecasting prediction horizon sensitivity analysis. Mach. Learn. Appl. 2021, 6, 100128.spa
dcterms.bibliographicCitationHassan, Q.; Jaszczur, M.; Przenzak, E.; Abdulateef, J. The PV cell temperature effect on the energy production and module efficiency. Contemp. Probl. Power Eng. Environ. Prot. 2016, 33, 33–40.spa
dcterms.bibliographicCitationSchwingshackl, C.; Petitta, M.; Wagner, J.; Belluardo, G.; Moser, D.; Castelli, M.; Zebisch, M.; Tetzlaff, A. Wind Effect on PV Module Temperature: Analysis of Different Techniques for an Accurate Estimation. Energy Procedia 2013, 40, 77–86.spa
dcterms.bibliographicCitationSistema Único de Información de Servicios Públicos Domicialiarios. Consolidado de Energía por Empresa y Departamento, Colombia. Available online: https://sui.superservicios.gov.co/Reportes-del-sector/Energia/Reportes-comerciales/Consolidado de-energia-por-empresa-y-departamento (accessed on 21 September 2022).spa
dcterms.bibliographicCitationWang, P.; Wang, W.; Xu, D. Optimal Sizing of Distributed Generations in DC Microgrids With Comprehensive Consideration of System Operation Modes and Operation Targets. IEEE Access 2018, 6, 31129–31140spa
dcterms.bibliographicCitationXM SA EPS. En Colombia Factor de Emisión de CO2 por Generación eléCtrica del Sistema Interconectado: 164.38 Gramos de CO2 por Kilovatio Hora, Colombia. Available online: https://www.xm.com.co/noticias/en-colombia-factor-de-emision-de-co2 -por-generacion-electrica-del-sistema-interconectado (accessed on 21 September 2022)spa
dcterms.bibliographicCitationAcademia Colombiana de Ciencias Exactas, Físicas y Naturales. Factores de Emisión de los Combustibles Colombianos, Colombia, 2016. Available online: https://www.scribd.com/document/157258400/18-FECOC-factores-emision-colombia-docx# (accessed on 21 September 2022).spa
dcterms.bibliographicCitationNormas Técnicas y Certificación (ICONTEC). Tensiones y Frecuencia Nominales en Sistemas de Energía Elécrica en Redes de Servicio Público NTC1340; ICONTEC: Bogotá, Colombia, 2004.spa
dcterms.bibliographicCitationBaran, M.; Wu, F. Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans. Power Deliv. 1989, 4, 1401–1407.spa
dcterms.bibliographicCitationFalaghi, H.; Ramezani, M.; Haghifam, M.R.; Milani, K. Optimal selection of conductors in radial distribution systems with time varying load. In Proceedings of the 18th International Conference and Exhibition on Electricity Distribution (CIRED 2005), Turin, Italy, 6–9 June 2005.spa
dcterms.bibliographicCitationEberhart, R.; Kennedy, J. Particle swarm optimization. In Proceedings of the IEEE International Conference on Neural Networks, Perth, WA, Australia, 27 November–1 December 1995; Citeseer: Piscataway, NJ, USA, 1995; Volume 4, pp. 1942–1948spa
dcterms.bibliographicCitationChu, P.C.; Beasley, J.E. A genetic algorithm for the multidimensional knapsack problem. J. Heuristics 1998, 4, 63–86.spa
dcterms.bibliographicCitationDo ˘gan, B.; Ölmez, T. A new metaheuristic for numerical function optimization: Vortex Search algorithm. Inf. Sci. 2015, 293, 125–145spa
dcterms.bibliographicCitationMirjalili, S. The ant lion optimizer. Adv. Eng. Softw. 2015, 83, 80–98.spa
dcterms.bibliographicCitationWicaksana, M.G.S.; Putranto, L.M.; Waskito, F.; Yasirroni, M. Optimal placement and sizing of PV as DG for losses minimization using PSO algorithm: A case in Purworejo area. In Proceedings of the 2020 International Conference on Sustainable Energy Engineering and Application (ICSEEA), Online, 18–20 November 2020; pp. 1–6.spa
dcterms.bibliographicCitationKS, G.D. Hybrid genetic algorithm and particle swarm optimization algorithm for optimal power flow in power system. J. Comput. Mech. Power Syst. Control 2019, 2, 31–37spa
dcterms.bibliographicCitationRamavath, D.; Sharma, M. Optimal Power Flow Using Modified ALO. In Proceedings of the 2020 International Conference on Renewable Energy Integration into Smart Grids: A Multidisciplinary Approach to Technology Modelling and Simulation (ICREISG), Bhubaneshwar, India, 14–15 February 2020; pp. 84–89.spa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_b1a7d7d4d402bccespa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/draftspa
dc.identifier.doihttps://doi.org/10.3390/math11020484
dc.subject.keywordsDay-ahead operation of PV sourcesspa
dc.subject.keywordsEnergy purchasing costsspa
dc.subject.keywordsOperation and maintenance costs of PV sourcesspa
dc.subject.keywordsEnergy losses costsspa
dc.subject.keywordsNonlinear programming formulationspa
dc.subject.keywordsGAMS softwarespa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
dc.type.spahttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.audiencePúblico generalspa
dc.publisher.sedeCampus Tecnológicospa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa


Ficheros en el ítem

Thumbnail
Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

http://creativecommons.org/licenses/by-nc-nd/4.0/
http://creativecommons.org/licenses/by-nc-nd/4.0/

Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.