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Comparative Performance of a Hybrid Renewable Energy Generation System with Dynamic Load Demand
| dc.contributor.author | Rojas, Jhan Piero | |
| dc.contributor.other | Valencia Ochoa, Guillermo | |
| dc.contributor.other | Duarte Forero, Jorge | |
| dc.date.accessioned | 2022-11-15T21:02:11Z | |
| dc.date.available | 2022-11-15T21:02:11Z | |
| dc.date.issued | 2020-04-29 | |
| dc.date.submitted | 2020-03-10 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12834/926 | |
| dc.description.abstract | This article presents the modeling and simulation of a hybrid generation system, which uses solar energy generation, wind energy, and the regulation of a proton exchange membrane (PEM) cell to raise the demanded load, empowering the use of these hydride systems worldwide. This generation system was simulated for di erent locations in Puerto Bolivar (Colombia), Bremen (Germany), Beijing (China), and Texas (USA), for two demand profiles. The data used for the simulation was calculated using the mathematical solar model proposed by Beistow and Campbell for solar radiation. In contrast, for the wind resource evaluation, theWeibull probability distribution was used to calculate the most probable wind speed for each day, according to the historical data for each of the studied locations. Considering these data, the process transfer functions were used for tuning the control parameters for the hydrogen and oxygen production system. For the evaluation of the performance of these controllers, the indices of the absolute value of the error (IAE), the integral of the square of the error (ISE), the integral of the absolute value of the error for time (ITAE), and the integral of the square of the error for time (ITSE) were used. It was found that in the second load profile studied, better performance of the ITSE performance parameter was obtained, with stabilization times lower than those of the first profile. | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.language.iso | eng | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
| dc.source | MDPI AG | spa |
| dc.title | Comparative Performance of a Hybrid Renewable Energy Generation System with Dynamic Load Demand | spa |
| dcterms.bibliographicCitation | 1. Yono , R.E.; Ochoa, G.V.; Cardenas-Escorcia, Y.; Silva-Ortega, J.I.; Meriño-Stand, L. Research trends in proton exchange membrane fuel cells during 2008–2018: A bibliometric analysis. Heliyon 2019, 5, e01724. | spa |
| dcterms.bibliographicCitation | 2. Wolfram, C.; Shelef, O.; Gertler, P.Howwill energy demand develop in the developing world? J. Econ. Perspect. 2012, 26, 119–138. | spa |
| dcterms.bibliographicCitation | 3. Valencia, G.; Duarte, J.; Isaza-Roldan, C. Thermoeconomic analysis of di erent exhaust waste-heat recovery systems for natural gas engine based on ORC. Appl. Sci. 2019, 9, 4017. | spa |
| dcterms.bibliographicCitation | 4. Valencia, G.; Peñaloza, C.; Forero, J. Thermoeconomic optimization with PSO algorithm of waste heat recovery systems based on organic rankine cycle system for a natural gas engine. Energies 2019, 12, 4165. | spa |
| dcterms.bibliographicCitation | 5. Alibaba, M.; Pourdarbani, R.; Hasan, M.; Manesh, K.; Valencia, G.; Duarte, J. Thermodynamic, exergo-economic and exergo-environmental analysis of hybrid geothermal-solar power plant based on ORC cycle using emergy concept. Heliyon 2020, 6, e03758. | spa |
| dcterms.bibliographicCitation | 6. Goldemberg, J. The case for renewable energies. In Renewable Energy; Routledge: Thames, UK, 2012; pp. 31–42. | spa |
| dcterms.bibliographicCitation | 7. Duarte, J.; Duarte Forero, N.; Hernandez, B.; Vanegas, M.; Stand, R. Experimental study of partial fuel substitution with hydroxy and energy recovery in low displacement compression ignition engines. In ASME International Mechanical Engineering Congress and Exposition; American Society of Mechanical Engineers: New York, NY, USA, 2019; Volume 59452, p. V008T09A021. | spa |
| dcterms.bibliographicCitation | 8. Hache, E.; Palle, A. Renewable energy source integration into power networks, research trends and policy implications: A bibliometric and research actors survey analysis. Energy Policy 2019, 124, 23–35. | spa |
| dcterms.bibliographicCitation | 9. De Paulo, A.F.; Porto, G.S. Solar energy technologies and open innovation: A study based on bibliometric and social network analysis. Energy Policy 2017, 108, 228–238. | spa |
| dcterms.bibliographicCitation | 10. Koo, Y.; Oh, M.; Kim, S.-M.; Park, H.-D. Estimation and mapping of solar irradiance for korea by using COMS MI satellite images and an artificial neural network model. Energies 2020, 13, 301. | spa |
| dcterms.bibliographicCitation | 11. Alghamdi, A.S. Potential for rooftop-mounted pv power generation to meet domestic electrical demand in saudi arabia: Case Study of a villa in jeddah. Energies 2019, 12, 4411. | spa |
| dcterms.bibliographicCitation | 12. Mao, G.; Liu, X.; Du, H.; Zuo, J.; Wang, L. Way forward for alternative energy research: A bibliometric analysis during 1994–2013. Renew. Sustain. Energy Rev. 2015, 48, 276–286. | spa |
| dcterms.bibliographicCitation | 13. Yue, C.-D.; Chiu, Y.-S.; Tu, C.-C.; Lin, T.-H. Evaluation of an o shore wind farm by using data from the weather station, floating LiDAR, mast, and MERRA. Energies 2020, 13, 185. | spa |
| dcterms.bibliographicCitation | 14. Perea-Moreno, A.-J.; Alcalá, G.; Hernandez-Escobedo, Q. Seasonal wind energy characterization in the gulf of mexico. Energies 2019, 13, 93. | spa |
| dcterms.bibliographicCitation | 15. KC, A.; Whale, J.; Urmee, T. Urban wind conditions and small wind turbines in the built environment: A review. Renew. Energy 2019, 131, 268–283. | spa |
| dcterms.bibliographicCitation | 16. Pinheiro, E.; Bandeiras, F.; Gomes, M.; Coelho, P.; Fernandes, J. Performance analysis of wind generators and PV systems in industrial small-scale applications. Renew. Sustain. Energy Rev. 2019, 110, 392–401. | spa |
| dcterms.bibliographicCitation | 17. Tsay, M.-Y. A bibliometric analysis of hydrogen energy literature, 1965–2005. Scientometrics 2008, 75, 421–438. | spa |
| dcterms.bibliographicCitation | 18. He, M.; Zhang, Y.; Gong, L.; Zhou, Y.; Song, X.; Zhu, W.; Zhang, M.; Zhang, Z. Bibliometrical analysis of hydrogen storage. Int. J. Hydrogen Energy 2019, 44, 28206–28226. | spa |
| dcterms.bibliographicCitation | 19. Tanç, B.; Arat, H.T.; Conker, Ç.; Baltacio˘ glu, E.; Aydin, K. Energy distribution analyses of an additional traction battery on hydrogen fuel cell hybrid electric vehicle. Int. J. Hydrogen Energy 2019. | spa |
| dcterms.bibliographicCitation | 20. Prashanth, B.N.; Pramod, R.; Kumar, G.B.V. Design and development of hybrid wind and solar energy system for power generation. Mater. Today Proc. 2018, 5, 11415–11422. | spa |
| dcterms.bibliographicCitation | 21. Haddad, A.; Ramadan, M.; Khaled, M.; Ramadan, H.S.; Becherif, M. Triple hybrid system coupling fuel cell with wind turbine and thermal solar system. Int. J. Hydrogen Energy 2019, 45, 11484–11491. | spa |
| dcterms.bibliographicCitation | 22. Zhang,W.; Maleki, A.; Rosen, M.A.; Liu, J. Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Convers. Manag. 2019, 180, 609–621. | spa |
| dcterms.bibliographicCitation | 23. Ishaq, H.; Dincer, I.; Naterer, G.F. Development and assessment of a solar, wind and hydrogen hybrid trigeneration system. Int. J. Hydrogen Energy 2018, 43, 23148–23160. | spa |
| dcterms.bibliographicCitation | 24. Elliott, D.; Schwartz, M.; Haymes, S.; Heimiller, D.; Scott, G.; Flowers, L.; Brower, M.; Hale, E.; Phelps, B. 80 and 100 Meter Wind Energy Resource Potential for the United States; Windpower 2010; National Renewable Energy Lab. (NREL): Golden, CO, USA, 2010. | spa |
| dcterms.bibliographicCitation | 25. Lütkehus, I.; Salecker, H.; Umweltbundesamt, D.E. Onshore wind energy potential in Germany. DEWI Mag. 2013, 43, 23–28. | spa |
| dcterms.bibliographicCitation | 26. Liu, F.; Sun, F.; Liu,W.;Wang, T.;Wang, H.;Wang, X.; Lim,W.H. On wind speed pattern and energy potential in China. Appl. Energy 2019, 236, 867–876. | spa |
| dcterms.bibliographicCitation | 27. Antonio, F.; Barrozo, F.; Valencia, G.; Obregon, L.; Arango-Manrique, A.; Núñez Alvarez, J. Energy, economic, and environmental evaluation of a proposed solar-wind power on-grid system using HOMER Pro®: A case study in Colombia. Energies 2020, 13, 761307. | spa |
| dcterms.bibliographicCitation | 28. Pandiarajan, N.; Muthu, R. Mathematical modeling of photovoltaic module with Simulink. In Proceedings of the 1st International Conference on Electrical Energy Systems (ICEES), Newport Beach, CA, USA, 3–5 January 2011; pp. 258–263. | spa |
| dcterms.bibliographicCitation | 29. Khan, M.J.; Iqbal, M.T. Dynamic modeling and simulation of a small wind–fuel cell hybrid energy system. Renew. Energy 2005, 30, 421–439. | spa |
| dcterms.bibliographicCitation | 30. ¸Sen, S.; Demirer, G. Anaerobic treatment of real textile wastewater with a fluidized bed reactor. Water Res. 2003, 37, 1868–1878. | spa |
| dcterms.bibliographicCitation | 31. Kader, A.A.; Colina-Irezabal, M.L. Métodos de mezclado, muestreo y análisis de gases. Tecnología Postcosecha de Cultivos Hortofrutícolas 2007, 24, 169–174. | spa |
| dcterms.bibliographicCitation | 32. Valencia, G.; Benavides, A.; Cárdenas, Y. Economic and environmental multiobjective optimization of a wind-solar-fuel cell hybrid energy system in the Colombian Caribbean region. Energies 2019, 12, 2119. | spa |
| dcterms.bibliographicCitation | 33. Meshram, P.M.; Kanojiya, R.G. Tuning of PID controller using ziegler-nichols method for speed control of DC motor. In Proceedings of the IEEE International Conference on Advances in Engineering, Science and Management (ICAESM), Nagapattinam, India, 30–31 March 2012; pp. 117–122. | spa |
| dcterms.bibliographicCitation | 34. Smith, C.A.; Corripio, A.B. Principles and Practice of Automatic Process Control;Wiley: New York, NY, USA, 1985; Volume 2. | spa |
| dcterms.bibliographicCitation | 35. Shinskey, F.G. Feedback Controllers for the Process Industries; McGraw-Hill: New York, NY, USA, 1994. | spa |
| dcterms.bibliographicCitation | 36. Dorf, R.C.; Bishop, R.H. Modern Control Systems, 12th ed.; Pearson Education, Inc.: Upper Saddle River, NJ, USA, 2011. | spa |
| dcterms.bibliographicCitation | 37. Valencia Ochoa, G.; Núñez Alvarez, J.; Vanegas Chamorro, M. Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar—Colombia. Data Brief 2019, 27, 104753. | spa |
| dcterms.bibliographicCitation | 38. De la Cruz Buelvas, J.; Valencia Ochoa, G.; Vanegas Chamorro, M. Estudio estadístico de la velocidad y la dirección del viento en los departamentos de Atlántico y Bolívar en Colombia. Ingeniare Revista Chilena de Ingeniería 2018, 26, 319–328. | spa |
| dcterms.bibliographicCitation | 39. Carta, J.A.; Ramírez, P. Analysis of two-component mixtureWeibull statistics for estimation of wind speed distributions. Renew. Energy 2007, 32, 518–531. | spa |
| dcterms.bibliographicCitation | 40. Seguro, J.V.; Lambert, T.W. Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. J. Wind Eng. Ind. Aerodyn. 2000, 85, 75–84. | spa |
| dcterms.bibliographicCitation | 41. He, J.; Choe, S.-Y.; Hong, C.-O. Analysis and control of a hybrid fuel delivery system for a polymer electrolyte membrane fuel cell. J. Power Sources 2008, 185, 973–984. | spa |
| dcterms.bibliographicCitation | 42. Granda-Gutiérrez, E.E.; Orta, O.A.; Díaz-Guillén, J.C.; Jimenez, M.A.; Osorio, M.; Gonzleáz, M.A. Modelado y simulación de celdas y paneles solares. Congreso Internacional de Ingeniería Electrónica 2013, 35, 17–22. | spa |
| dcterms.bibliographicCitation | 43. Valencia, G.; Glen, G.; Turizo, J.; Chamorro Coneo, R.J. Mimo generalized predictive control for a small wind turbine–fuel cell hybrid energy system. In Proceedings of the ASME 2009 3rd International Conference on Energy Sustainability collocated with the Heat Transfer and InterPACK09 Conferences, San Francisco, CA, USA, 19–23 July 2009; pp. 557–562. | spa |
| dcterms.bibliographicCitation | 44. Ochoa, G.V.; Isaza-Roldan, C.; Forero, J.D. A phenomenological base semi-physical thermodynamic model for the cylinder and exhaust manifold of a natural gas 2-megawatt four-stroke internal combustion engine. Heliyon 2019, 5, e02700. | spa |
| datacite.rights | http://purl.org/coar/access_right/c_abf2 | spa |
| oaire.resourcetype | http://purl.org/coar/resource_type/c_6501 | spa |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | spa |
| dc.audience | Público general | spa |
| dc.identifier.doi | 10.3390/app10093093 | |
| dc.identifier.instname | Universidad del Atlántico | spa |
| dc.identifier.reponame | Repositorio Universidad del Atlántico | spa |
| dc.rights.cc | Attribution-NonCommercial 4.0 International | * |
| dc.subject.keywords | hybrid system; wind turbine; photovoltaic system; PEM fuel cell; performance indicators | spa |
| dc.type.driver | info:eu-repo/semantics/article | spa |
| dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | spa |
| dc.type.spa | Artículo | spa |
| dc.publisher.place | Barranquilla | spa |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | spa |
| dc.publisher.sede | Sede Norte | spa |
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