El Modelado paramétrico y gestión energética de un volante de inercia industrial regenerativo para suavizado de potencia eólica

Autores/as

  • Juan Carlos Torres Bordón Universidad de Las Palmas de Gran Canaria
  • Pedro Jesús Cabrera Santana Universidad de Las Palmas de Gran Canaria

DOI:

https://doi.org/10.64117/simposioscea.v2i3.255

Palabras clave:

Volante de Inercia, almacenamiento energético, suavizado eólico, gestión energética., motor asíncrono, accionamiento regenerativo

Resumen

Este trabajo presenta una metodología para transformar un banco experimental de volante de inercia, que hasta ahora ha sido caracterizado mediante consignas de velocidad y rampa, en un sistema orientado al control energético por potencia activa. Se propone un modelo parametrizado en Simulink de un sistema regenerativo industrial formado por un accionamiento regenerativo de cuatro cuadrantes, motor asíncrono y volante de inercia, acoplado a un modelo de generación eólica y a un sistema de gestión energética.

Se propone un EMS (Energy Manage System) capaz de calcular la potencia de compensación necesaria a partir de la diferencia entre la potencia eólica instantánea y una referencia suavizada, incorporando corrección de estado de carga, pérdidas y límites físicos de par, corriente, potencia y velocidad. Este enfoque permite superar las limitaciones del control por velocidad/rampa, donde la potencia intercambiada queda desfasada respecto a la variable de consigna.

El modelo permite evaluar la capacidad del FESS (Flywheel Energy System Storage) para suavizar fluctuaciones eólicas en distintas bandas temporales y construir fronteras de dimensionado entre potencia eólica nominal, frecuencia de corte y potencia útil del volante. Aunque la validación experimental está todavía en curso, el trabajo proporciona una herramienta para diseñar ensayos, seleccionar configuraciones de accionamiento y estudiar la viabilidad técnica de volantes de inercia en aplicaciones renovables, así como desarrollar tecnicas de EMS sobre estos mismo.

Citas

[1] Lund, H., Thellufsen, J.Z., Østergaard, P.A., Sorknæs, P., Skov, I.R., Mathiesen, B.V., 2021. EnergyPLAN: Advanced analysis of smart energy systems. Smart Energy 1, 100007. DOI: https://doi.org/10.1016/j.segy.2021.100007

[2] Cabrera, P., Lund, H., Carta, J.A., 2018. Smart renewable energy penetration strategies on islands: The case of Gran Canaria. Energy 162, 421-443. DOI: https://doi.org/10.1016/j.energy.2018.08.020

[3] Cabrera, P., Carta, J.A., Lund, H., Thellufsen, J.Z., 2021. Large-scale optimal integration of wind and solar photovoltaic power in water-energy systems on islands. Energy Conversion and Management 235, 113982. DOI: https://doi.org/10.1016/j.enconman.2021.113982

[4] Luo, X., Wang, J., Dooner, M., Clarke, J., 2015. Overview of current development in electrical energy storage technologies and the application potential in power system operation. Applied Energy 137, 511-536. DOI: https://doi.org/10.1016/j.apenergy.2014.09.081

[5] Bolund, B., Bernhoff, H., Leijon, M., 2007. Flywheel energy and power storage systems. Renewable and Sustainable Energy Reviews 11, 235-258. DOI: https://doi.org/10.1016/j.rser.2005.01.004

[6] Sebastián, R., Peña Alzola, R., 2012. Flywheel energy storage systems: Review and simulation for an isolated wind power system. Renewable and Sustainable Energy Reviews 16, 6803-6813. DOI: https://doi.org/10.1016/j.rser.2012.08.008

[7] Mousavi G., S.M., Faraji, F., Majazi, A., Al-Haddad, K., 2017. A comprehensive review of Flywheel Energy Storage System technology. Renewable and Sustainable Energy Reviews 67, 477-490. DOI: https://doi.org/10.1016/j.rser.2016.09.060

[8] Amiryar, M.E., Pullen, K.R., 2017. A review of flywheel energy storage system technologies and their applications. Applied Sciences 7, 286. DOI: https://doi.org/10.3390/app7030286

[9] Khodadoost Arani, A.A., Karami, H., Gharehpetian, G.B., Hejazi, M.S.A., 2017. Review of Flywheel Energy Storage Systems structures and applications in power systems and microgrids. Renewable and Sustainable Energy Reviews 69, 9-18. DOI: https://doi.org/10.1016/j.rser.2016.11.166

[10] Barra, P.H.A., de Carvalho, W.C., Menezes, T.S., Fernandes, R.A.S., Coury, D.V., 2021. A review on wind power smoothing using high-power energy storage systems. Renewable and Sustainable Energy Reviews 137, 110455. DOI: https://doi.org/10.1016/j.rser.2020.110455

[11] Zhang, J., Wang, Y.H., Liu, G., Tian, G.Z., 2022. A review of control strategies for flywheel energy storage system and a case study with matrix converter. Energy Reports 8, 3948-3963. DOI: https://doi.org/10.1016/j.egyr.2022.03.009

[12] Cabrera Santana, P., Carta, J.A., González, J., Melián, G., 2017. Artificial neural networks applied to manage the variable operation of a simple seawater reverse osmosis plant. Desalination 416, 140-156. DOI: https://doi.org/10.1016/j.desal.2017.04.032

[13] Cabrera, P., Carta, J.A., González, J., Melián, G., 2018. Wind-driven SWRO desalination prototype with and without batteries: A performance simulation using machine learning models. Desalination 435, 77-96. DOI: https://doi.org/10.1016/j.desal.2017.11.044

[14] Cabrera, P., Carta, J.A., Matos, C., Lund, H., 2024. Lessons learned in wind-driven desalination systems in the Canary Islands. Desalination 583, 117697. DOI: https://doi.org/10.1016/j.desal.2024.117697

[15] Zhao, H., Wu, Q., Hu, S., Xu, H., Rasmussen, C.N., 2015. Review of energy storage system for wind power integration support. Applied Energy 137, 545-553. DOI: https://doi.org/10.1016/j.apenergy.2014.04.103

[16] Slootweg, J.G., de Haan, S.W.H., Polinder, H., Kling, W.L., 2003. General model for representing variable speed wind turbines in power system dynamics simulations. IEEE Transactions on Power Systems 18, 144-151. DOI: https://doi.org/10.1109/TPWRS.2002.807113

[17] Bianchi, F.D., De Battista, H., Mantz, R.J., 2007. Wind Turbine Control Systems: Principles, Modelling and Gain Scheduling Design. Springer, London.

[18] Muljadi, E., Butterfield, C.P., Chacon, J., Romanowitz, H., 2006. Power quality aspects in a wind power plant. IEEE Power Engineering Society General Meeting, pp. 1-10.

[19] Carrasco, J.M., Franquelo, L.G., Bialasiewicz, J.T., Galván, E., Portillo Guisado, R.C., Prats, M.A.M., León, J.I., Moreno-Alfonso, N., 2006. Power-electronic systems for the grid integration of renewable energy sources: A survey. IEEE Transactions on Industrial Electronics 53, 1002-1016. DOI: https://doi.org/10.1109/TIE.2006.878356

[20] Lamsal, D., Sreeram, V., Mishra, Y., Kumar, D., 2019. Output power smoothing control approaches for wind and photovoltaic generation systems: A review. Renewable and Sustainable Energy Reviews 113, 109245. DOI: https://doi.org/10.1016/j.rser.2019.109245

[21] Jabir, M., Illias, H.A., Raza, S., Mokhlis, H., 2017. Intermittent smoothing approaches for wind power output: A review. Energies 10, 1572. DOI: https://doi.org/10.3390/en10101572

[22] de Siqueira, L.M.S., Peng, W., 2021. Control strategy to smooth wind power output using battery energy storage system: A review. Journal of Energy Storage 35, 102252. DOI: https://doi.org/10.1016/j.est.2021.102252

[23] Krause, P.C., Wasynczuk, O., Sudhoff, S.D., Pekarek, S., 2013. Analysis of Electric Machinery and Drive Systems, 3rd ed. Wiley-IEEE Press, Hoboken.

[24] Bose, B.K., 2002. Modern Power Electronics and AC Drives. Prentice Hall, Upper Saddle River.

[25] Díaz-González, F., Sumper, A., Gomis-Bellmunt, O., Bianchi, F.D., 2013. Energy management of flywheel-based energy storage device for wind power smoothing. Applied Energy 110, 207-219. DOI: https://doi.org/10.1016/j.apenergy.2013.04.029

[26] Díaz-González, F., Sumper, A., Gomis-Bellmunt, O., Villafáfila-Robles, R., 2013. Modeling, control and experimental validation of a flywheel-based energy storage device. EPE Journal 23, 41-51. DOI: https://doi.org/10.1080/09398368.2013.11463852

[27] Díaz-González, F., Bianchi, F.D., Sumper, A., Gomis-Bellmunt, O., 2014. Control of a flywheel energy storage system for power smoothing in wind power plants. IEEE Transactions on Energy Conversion 29, 204-214. DOI: https://doi.org/10.1109/TEC.2013.2292495

[28] Cardenas, R., Peña, R., Asher, G., Clare, J., 2001. Control strategies for enhanced power smoothing in wind energy systems using a flywheel driven by a vector-controlled induction machine. IEEE Transactions on Industrial Electronics 48, 625-635. DOI: https://doi.org/10.1109/41.925590

[29] Cardenas, R., Peña, R., Asher, G., Clare, J., Blasco-Gimenez, R., 2004. Control strategies for power smoothing using a flywheel driven by a sensorless vector-controlled induction machine operating in a wide speed range. IEEE Transactions on Industrial Electronics 51, 603-614. DOI: https://doi.org/10.1109/TIE.2004.825345

[30] Cimuca, G.O., Saudemont, C., Robyns, B., Radulescu, M.M., 2006. Control and performance evaluation of a flywheel energy-storage system associated to a variable-speed wind generator. IEEE Transactions on Industrial Electronics 53, 1074-1085. DOI: https://doi.org/10.1109/TIE.2006.878326

[31] Jia, Y., Wu, Z., Bao, M., Zhang, J., Yang, P., Zhang, Z., 2022. Control strategy of MW flywheel energy storage system based on a six-phase permanent magnet synchronous motor. Energy Reports 8, 11927-11937. DOI: https://doi.org/10.1016/j.egyr.2022.09.048

[32] Zhou, J., Jia, Y., Sun, C., 2025. Flywheel energy storage system controlled using tube-based deep Koopman model predictive control for wind power smoothing. Applied Energy 381, 125117. DOI: https://doi.org/10.1016/j.apenergy.2024.125117

Publicado

2026-10-08