Revisión bibliográfica de sistemas de control para gestión de micro-redes de energía
Barra lateral del artículo
Publicado:
Nov 9, 2018
Palabras clave:
Régimen Especial, Contratación Pública, Presupuesto, Auditoría, Finanzas.
Contenido principal del artículo
Resumen
El presente artículo presenta una revisión de la literatura la cual está enfocada en determinar el grado de importancia que tienen los sistemas de control para la gestión energética en micro-redes. Se describen las principales razones por las que se lleva a cabo el proceso de migración de plantas de uso de combustible fósil hacia plantas industriales de energía renovables, enfatizando en algunos tipos de energía renovable existentes. Adicionalmente, se resumen las técnicas de control existentes, entre las que figuran el control óptimo y jerárquico, para las micro-redes. Asimismo, se esbozan las principales tecnologías utilizadas en la actualidad para la implementación de sistemas de control predictivo basado en modelos (MPC, siglas en inglés) y el control económico predictivo basado en modelos (EMPC siglas en inglés). En este último, se realiza un análisis en términos económicos en función del coste.
Detalles del artículo
Cómo citar
Revisión bibliográfica de sistemas de control para gestión de micro-redes de energía. (2018). MASKAY, 8(2), 60-66. https://doi.org/10.24133/maskay.v8i2.971
Número
Sección
ARTÍCULOS TÉCNICOS
Los autores que publican en esta revista están de acuerdo con los siguientes términos: Los autores conservan los derechos de autor y garantizan a la revista el derecho de ser la primera publicación del trabajo al igual que licenciado bajo una Creative Commons Attribution License que permite a otros compartir el trabajo con un reconocimiento de la autoría del trabajo y la publicación inicial en esta revista. Los autores pueden establecer por separado acuerdos adicionales para la distribución no exclusiva de la versión de la obra publicada en la revista (por ejemplo, situarlo en un repositorio institucional o publicarlo en un libro), con un reconocimiento de su publicación inicial en esta revista. Se permite y se anima a los autores a difundir sus trabajos electrónicamente (por ejemplo, en repositorios institucionales o en su propio sitio web) antes y durante el proceso de envío, ya que puede dar lugar a intercambios productivos, así como a una citación más temprana y mayor de los trabajos publicados.
Cómo citar
Revisión bibliográfica de sistemas de control para gestión de micro-redes de energía. (2018). MASKAY, 8(2), 60-66. https://doi.org/10.24133/maskay.v8i2.971
Referencias
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[41] C. R. Touretzky and M. Baldea, “Nonlinear model reduction and model predictive control of residential buildings with energy recovery,” J. Process Control, vol. 24, no. 6, pp. 723–739, 2014.
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[43] D. I. Mendoza-Serrano and D. J. Chmielewski, “Smart grid coordination in building HVAC systems: EMPC and the impact of forecasting,” J. Process Control, vol. 24, no. 8, pp. 1301–1310, 2014.
[2] J. Conti, P. Holtberg, J. Diefenderfer, A. LaRose, J. T. Turnure, and L. Westfall, International Energy Outlook 2016 With Projections to 2040, vol. 0484, no. May. 2016.
[3] L. G. G. Moncada, F. Asdrubali, and A. Rotili, “Influence of new fac tors on global energy prospects in the medium term: compar ison among the 2010, 2011 and 2012 editions of the IEA’s World Energy Outlook reports,” Econ. Policy Energy Environ., no. 3, pp. 67–89, 2013.
[4] A. Galkina, V. Kulagin, and I. Mironova, “Renewable Energy Sources : Global and Russian Outlook Up to 2040,” J. Technol. Innov. Renew. Energy, vol. 007, no. 499, pp. 185–194, 2014.
[5] P. H. Shaikh, N. B. M. Nor, P. Nallagownden, I. Elamvazuthi, and T. Ibrahim, “A review on optimized control systems for building energy and comfort management of smart sustainable buildings,” Renew. Sustain. Energy Rev., vol. 34, pp. 409–429, 2014.
[6] J. de Matos, F. e Silva, and L. Ribeiro, “Power Control in AC Isolated Microgrids with Renewable Energy Sources and Energy Storage Systems,” IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 1–1, 2014.
[7] C. Graves, S. D. Ebbesen, M. Mogensen, and K. S. Lackner, “Sustainable hydrocarbon fuels by recycling CO2and H2O with renewable or nuclear energy,” Renew. Sustain. Energy Rev., vol. 15, no. 1, pp. 1–23, 2011.
[8] A. Omri, N. Ben Mabrouk, and A. Sassi-Tmar, “Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries,” Renew. Sustain. Energy Rev., vol. 42, pp. 1012–1022, 2015.
[9] P. G. Arul, V. K. Ramachandaramurthy, and R. K. Rajkumar, “Control strategies for a hybrid renewable energy system: A review,” Renew. Sustain. Energy Rev., vol. 42, pp. 597–608, 2015.
[10] N. Hatziargyriou, Microgrids: architectures and control. John Wiley & Sons, 2014.
[11] C. Diáz and D. Hernandez, “Smart Grid : Las TICs y la modernización de las redes de energía eléctrica – Estado del Arte,” Rev. Ssitemas y Telemat., vol. 9, pp. 53–81, 2011.
[12] E. Crisostomi, M. Raugi, A. Franco, and G. Giunta, “The smart gas grid: State of the art and perspectives,” in 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013, 2013, pp. 1–5.
[13] E. Herrera, R. Bourdais, and H. Guéguen, “Predictive and interactive controllers for solar absorption cooling systems in buildings,” J. Process Control, vol. 24, no. 6, pp. 836–845, 2014.
[14] B. Prasartkaew and S. Kumar, “The Quasi-steady State Performance of a Solar-Biomass Hybrid Cooling System,” in Proceedings of the Second TSME International Conference on Mechanical Engineering, 2011.
[15] Y. L. Yin, Z. P. Song, Y. Li, R. Z. Wang, and X. Q. Zhai, “Experimental investigation of a mini-type solar absorption cooling system under different cooling modes,” Energy Build., vol. 47, pp. 131–138, 2012.
[16] H. F. Scherer, M. Pasamontes, J. L. Guzmán, J. D. Álvarez, E. Camponogara, and J. E. Normey-Rico, “Efficient building energy management using distributed model predictive control,” J. Process Control, vol. 24, no. 6, pp. 740–749, 2014.
[17] X. Wang, H. Teichgraeber, A. Palazoglu, and N. H. El-Farra, “An economic receding horizon optimization approach for energy management in the chlor-alkali process with hybrid renewable energy generation,” J. Process Control, vol. 24, no. 8, pp. 1318–1327, 2014.
[18] A. Parisio, E. Rikos, and L. Glielmo, “A Model Predictive Control Approach to Microgrid Operation Optimization,” IEEE Trans. Control Syst. Technol., vol. 22, no. 99, p. 1, 2014.
[19] G. Kyriakarakos, D. D. Piromalis, A. I. Dounis, K. G. Arvanitis, and G. Papadakis, “Intelligent demand side energy management system for autonomous polygeneration microgrids,” Appl. Energy, vol. 103, pp. 39–51, 2013.
[20] A. Parisio, E. Rikos, G. Tzamalis, and L. Glielmo, “Use of model predictive control for experimental microgrid optimization,” Appl. Energy, vol. 115, pp. 37–46, 2014.
[21] J. Patino, A. Marquez, and J. Espinosa, “An economic MPC approach for a micro grid energy management system,” in Transmission & Distribution Conference and Exposition - Latin America (PES T&D-LA), 2014 IEEE PES, 2014.
[22] R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Trans. Smart Grid, vol. 7, no. 3, pp. 1675 – 1682, 2016.
[23] W. Analytics, “atehnium analytics,” 2013. [Online]. Available at: http://www.weatheranalytics.com/.
[24] V. Chandan and A. G. Alleyne, “Decentralized predictive thermal control for buildings,” J. Process Control, vol. 24, no. 6, pp. 820–835, 2014.
[25] L. Lao, M. Ellis, and P. D. Christofides, “Economic model predictive control of parabolic PDE systems: Addressing state estimation and computational efficiency,” J. Process Control, vol. 24, no. 4, pp. 448–462, 2014.
[26] A. Ferramosca, D. Limon, and E. F. Camacho, “Economic MPC for a changing economic criterion for linear systems,” IEEE Trans. Automat. Contr., vol. 59, no. 10, pp. 2657–2667, 2014.
[27] M. Heidarinejad, J. Liu, and P. D. Christofides, “Economic Model Predictive Control ofNonlinear Process Systems Using LyapunovTechniques,” AIChE J., vol. 58, no. 3, pp. 855–870, 2012.
[28] J. Piccardo and A. Prieto, “Vehículo Eléctrico de Producción Nacional,” Universidad de Buenos Aires, 2012.
[29] J. Arango, F. Sierra, and V. Silva, “Análisis exploratorio de investigaciones sobre los motores de combustión interna que trabajan con biogás,” Tecnura, vol. 18, no. 39, pp. 152–164, 2014.
[30] C. Clastres, “Smart grids: Another step towards competition, energy security and climate change objectives,” Energy Policy, vol. 39, no. 9, pp. 5399–5408, 2011.
[31] J. Gao, Y. Xiao, J. Liu, W. Liang, and C. L. P. Chen, “A survey of communication/networking in Smart Grids,” Futur. Gener. Comput. Syst., vol. 28, no. 2, pp. 391–404, 2012.
[32] H. Lund, A. N. Andersen, P. A. Østergaard, B. V. Mathiesen, and D. Connolly, “From electricity smart grids to smart energy systems - A market operation based approach and understanding,” Energy, vol. 42, no. 1, pp. 96–102, 2012.
[33] J. Ma, S. J. Qin, and T. Salsbury, “Application of economic MPC to the energy and demand minimization of a commercial building,” J. Process Control, vol. 24, no. 8, pp. 1282–1291, 2014.
[34] R. Amrit, J. B. Rawlings, and D. Angeli, “Economic optimization using model predictive control with a terminal cost,” Annu. Rev. Control, vol. 35, no. 2, pp. 178–186, 2011.
[35] S. Lucia, J. A. E. Andersson, H. Brandt, M. Diehl, and S. Engell, “Handling uncertainty in economic nonlinear model predictive control: A comparative case study,” J. Process Control, vol. 24, no. 8, pp. 1247–1259, 2014.
[36] C. N. Papadimitriou, E. I. Zountouridou, and N. D. Hatziargyriou, “Review of hierarchical control in DC microgrids,” Electr. Power Syst. Res., vol. 122, pp. 159–167, 2015.
[37] N. Jain, J. P. Koeln, S. Sundaram, and A. G. Alleyne, “Partially decentralized control of large-scale variable-refrigerant-flow systems in buildings,” J. Process Control, vol. 24, no. 6, pp. 798–819, 2014.
[38] Y. Huang, J. Lu, C. Liu, X. Xu, W. Wang, and X. Zhou, “Comparative study of power forecasting methods for PV stations,” 2010 Int. Conf. Power Syst. Technol., pp. 1–6, 2010.
[39] Z. Váňa, J. Cigler, J. Široký, E. Žáčeková, and L. Ferkl, “Model-based energy efficient control applied to an office building,” J. Process Control, vol. 24, no. 6, pp. 790–797, 2014.
[40] Y. Zong, L. Mihet-Popa, D. Kullmann, A. Thavlov, O. Gehrke, and H. W. Bindner, “Model predictive controller for active demand side management with PV self-consumption in an intelligent building,” IEEE PES Innov. Smart Grid Technol. Conf. Eur., pp. 1–8, 2012.
[41] C. R. Touretzky and M. Baldea, “Nonlinear model reduction and model predictive control of residential buildings with energy recovery,” J. Process Control, vol. 24, no. 6, pp. 723–739, 2014.
[42] W. J. Cole, D. P. Morton, and T. F. Edgar, “Optimal electricity rate structures for peak demand reduction using economic model predictive control,” J. Process Control, vol. 24, no. 8, pp. 1311–1317, 2014.
[43] D. I. Mendoza-Serrano and D. J. Chmielewski, “Smart grid coordination in building HVAC systems: EMPC and the impact of forecasting,” J. Process Control, vol. 24, no. 8, pp. 1301–1310, 2014.