A NEURO-FUZZY BASED CONTROL OF A SIMULATED SOFC IN A GRID CONNECTED ENVIRONMENT
Resumen
Abstract
In this research paper, a Solid Oxide Fuel Cell (SOFC), rated at 50 kW, is interfaced with grid through Voltage Source Inverter (VSI) and switching technique applied is Hysteresis Current Control. Standard Additive Model (SAM) based Neuro-Fuzzy and PI controllers are separately employed to control the Active and Reactive power demand of grid. The real and reactive powers are controlled by the manipulation of d and q axis currents, respectively. It was found that both Neuro-Fuzzy and PI controllers are capable in controlling the demand Active and Reactive powers of grid but the former supersede the latter. The output voltage and current waveforms of the inverter are simulated for smoothness in order to make it desirable for coupling with the grid. The control strategy decouples the real and reactive power and ensures their independent flow in the grid. The whole setup is simulated in MATLAB/Simulink.
Keywords: Active and Reactive power control, Neuro-Fuzzy Control, solid Oxide Fuel Cell, standard Additive Model.
UN CONTROL BASADO EN NEURO-FUZZY DE UN SOFC SIMULADO EN UN ENTORNO CONECTADO A LA RED
Resumen
En este trabajo de investigación, la celda de combustible de óxido sólido (SOFC), con una potencia nominal de 50 kW, está conectada con el inversor de voltaje (VSI) y la técnica de conmutación aplicada al control de corriente de histéresis. Los controladores Estándar del Modelo Aditivo (SAM) Neuro-Fuzzy y PI se emplean por separado para controlar la demanda de potencia activa y reactiva de la red. La potencia real y la potencia reactiva se controlan mediante la manipulación de las corrientes de los ejes d y q, respectivamente. Se encontró que tanto Neuro-Fuzzy como los controladores PI son capaces de controlar la demanda de potencia activa y reactiva de la red, pero la primera sustituye a la última. La tensión de salida y las formas de onda de corriente del inversor se simulan para suavizarlas y hacerlas deseables para el acoplamiento con la red. La estrategia de control desacopla la potencia real y reactiva y asegura su flujo independiente en la red. Toda la configuración se simula en MATLAB / Simulink.
Palabras Claves: Celda de combustible de óxido sólido, control Neuro-Fuzzy, modelo de aditivo estándar, control de potencia activa y reactiva.
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Bhuyan, K. C., Mahapatra, K. K., An intelligent control of solid oxide fuel cell voltage, 2011 International Conference on Power and Energy Systems (ICPS), pp.1,6, 22-24, December 2011.
Asadi, A., Mahmud, F., Moein, M, Techno-economic considerations on distributed generations (DGs) planning studies in power distribution systems, 2014 19th Conference on Electrical Power Distribution Networks (EPDC), vol., no., pp.82,87, 6-7, May 2014.
Diab, H., El-Helw, H., Talaat, H., Intelligent Maximum Power Tracking and Inverter Hysteresis Current Control of Grid-connected PV Systems, IEEE 2012, International Conference on advances in Power Conversion and Energy Technologies (APCET), pp. 1-5, 2-4, Aug. 2012.
Kang, H., Qingli, S., Zhengqui, W., Discussion on advantages and disadvantages of distribution generation connected to grid, IEEE 2011, International Conference on Electrical and Control Engineering (ICECE), 10.1109/ICECENG, pp. 170-173, 2011.
Khan, Z. W., and Khan, S., Analyzing the impacts of Distributed Generation on power losses and voltage profile, 2015 International Conference on Emerging Technologies (ICET), Peshawar, pp. 1-4, 2015.
Kosko, B., Fuzzy Engineering. Upper saddle River, NJ: Prentice-Hall, 1997.
Mekhilef, S., Saidur, R., & Safari, A, Comparative study of different fuel cell technologies, Renewable and Sustainable Energy Reviews, pp.981-989, 2012.
Nauck, D., Klawon, F., Kruse, R., Foundation of Neuro-Fuzzy Systems, J. Wiley and sons, 1997.
Vaishampayan, V., Vangari, A., Shah, J., Challenges and opportunities of affordable Fuel Cell for distributed generation, 1st International Conference on Non Conventional Energy (ICONCE), 10.1109/ICONCE, 6808734, pp. 319-323, 2014.
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