Abstract
The main objective of proposed paper is to implement an off-grid fuel cell array in combination with DC-to-DC boost chopper and MPPT. To extract the maximum power from the fuel cell array under different conditions, tuned PID-based MPPT technique is adopted. The design parameters of PID controller have critical role to improve the performance of the system. Ant lion optimizer (ALO) algorithm is taken up to get the optimum values of PID parameters to supply suitable duty ratio for DC-to-DC boost chopper to optimize the output power and voltage of the proposed system. P&O-based MPPT technique is carried out to validate the supremacy of PID-based MPPT to upgrade the response of the system. In this paper, the proposed ALO optimized PID controller-based MPPT technique is performed better over conventional P&O technique in terms of the output voltage, current, and power of the fuel cell array.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Esram, T., Chapman, P.L.: Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans. Energy Convers. 22(2), 439–449 (2007)
Al-Diab, A., Sourkounis, C.: Variable step size P&O MPPT algorithm for PV systems. In: Proceedings of International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), pp. 1097–1102 (2010)
Ishaque, K., Salam, Z.: A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition. Renew. Sustain. Energy Rev. 19, 475–488 (2013)
Ahmed, J., Salam, Z.: A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability. Appl. Energy 119, 118–130 (2014)
Giustiniani, A., Petrone, G., Spagnuolo, G.: Low-frequency current oscillations and maximum power point tracking in grid-connected fuel-cell-based systems. IEEE Trans. Ind. Electron. 57(6), 2010
Yang, Y.R.: A fuzzy logic controller for maximum power point tracking with 8-Bit Microcontroller, vol. 5, pp. 1078–1086 (2011)
Liu, Y.H., Liu, C.L., Huang, J.W., Chen, J.H.: Neural-network-based maximum power point tracking methods for photovoltaic systems operating under fast changing environments. Sol. Energy 89, 42–53 (2013)
Kamarzaman, N.A., Tan, C.W.: A comprehensive review of maximum power point tracking algorithms for photovoltaic systems. Renew. Sustain. Energy Rev. 37, 585–598 (2014)
Reza, A., Hassan, M., Jamasb, S.: Classification and comparison of maximum power point tracking techniques for photovoltaic system: a review. Renew. Sustain. Energy Rev. 19, 433–443 (2013)
Femia, N., Petrone, G., Spagnuolo, G., Vitelli, M.: Optimization of Perturb and Observe Maximum Power Point Tracking Method, vol. 20, no. 4, pp. 963–973 (2005)
Hoffmann, S., Koehl, M.: Investigation on the Impact of Macro- and Micro-Climate on the Potential Induced Degradation, pp. 1822–1825 (2013)
Ali, E.S., AbdElazim, S.M., Abdelaziz, A.Y.: Ant Lion Optimization algorithm for renewable distributed generations. Energy 116, 445–458 (2016)
Todorovic, M.H., Palma, L., Enjeti, P.N.: Design of a wide input range DC–DC converter with a robust power control scheme suitable for fuel cell power conversion. IEEE Trans. Ind. Electron. 55(3), 1247–1255 (2008)
Derbeli, M., Farhat, M., Barambones, O., Sbita, L.: Control of Proton Exchange Membrane Fuel Cell (PEMFC) Power System Using PI Controller. IEEE (2017)
Derbeli, M., Farhat, M., Barambones, O., Sbita, L.: PEM Fuel Cell Green Energy Generation—SMC Efficiency Optimization. IEEE (2017)
Tourkia, L.: Interaction Between Fuel Cell and DC/DC converter for Renewable Energy Management. IEEE (2017)
Lajnef, T., Adid, S., Ammous, A.: Modeling, Control, and Simulation of a Solar Hydrogen/Fuel Cell Hybrid Energy System for Grid-Connected Applications, Hindawi Publishing Corporation: Advances in Power Electronic, vol. 2013 (2013)
Mirjalili, S.: The Ant Lion Optimizer. Adv. Eng. Softw. 83, 80–98 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Kumar, S., Shaw, B. (2019). Design of Off-grid Fuel Cell by Implementing ALO Optimized PID-Based MPPT Controller. In: Nayak, J., Abraham, A., Krishna, B., Chandra Sekhar, G., Das, A. (eds) Soft Computing in Data Analytics . Advances in Intelligent Systems and Computing, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-13-0514-6_9
Download citation
DOI: https://doi.org/10.1007/978-981-13-0514-6_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-0513-9
Online ISBN: 978-981-13-0514-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)