Optimal Control of Bi-directional Converter to Enhance the Performance of an off-Grid Hybrid System

Authors

  • Abdelhak Kechida Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, 17000 Djelfa, Algeria
  • Djamal Gozim Laboratory of Applied Automation and Industrial Diagnostics (LAADI), Faculty of Science and Technology, Ziane Achour University, 17000 Djelfa, Algeria
  • Belgacem Toual Electrical Engineering Department Renewable Energy Systems Applications Laboratory (LASER), Ziane Achour University, 17000 Djelfa, Algeria
  • Bakria Derradji Renewable Energy Systems Applications Laboratory (LASER), Ziane Achour University, Djelfa, Algeria, Algeria
Volume: 15 | Issue: 3 | Pages: 23988-23994 | June 2025 | https://doi.org/10.48084/etasr.10787

Abstract

This paper presents a new method based on Artificial Intelligence (AI), for the optimal control of a bidirectional converter. The goal is to improve the DC bus voltage efficiency of a grid-independent hybrid system. The proposed design consists of a Photovoltaic System (PVS), a Wind Energy Conversion System (WECS), a Battery Storage System (BSS), and a variety of electronic power devices to extract the maximum energy from the generation sources. A bidirectional converter is featured in the use of an Adaptive Network-based Fuzzy Inference System (ANFIS) based controller, to improve the energy quality of the DC bus. The proposed approach provided good results compared to the Proportional Integral (PI) controller and the Fuzzy Logic controller (FLC). The use of this approach reduced the value of oscillations, improved the response time of the system, and contributed to the elimination of the problem of overshoot. This experiment was conducted using Matlab and Simulink.

Keywords:

bi-directional converter, PI-controller, ANFIS, hybrid system, renewable energy

Downloads

Download data is not yet available.

References

A. Al-Quraan and M. Al-Qaisi, "Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System," Energies, vol. 14, no. 16, p. 4849, Jan. 2021. DOI: https://doi.org/10.3390/en14164849

Alanazi A., Touti E., Nichita C. and Mohamed A., "Emulation Structures and Control of Wind-Tidal Turbine Hybrid Systems for Saudi Arabia Off-shore Development," Engineering, Technology & Applied Science Research, vol. 14, no. 4, pp. 15251–15256, Aug. 2024. DOI: https://doi.org/10.48084/etasr.7800

H. T. Dinh, J. Yun, D. M. Kim, K. H. Lee, and D. Kim, "A Home Energy Management System With Renewable Energy and Energy Storage Utilizing Main Grid and Electricity Selling," IEEE Access, vol. 8, pp. 49436–49450, Mar. 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2979189

M. A .J. Al-Ani, M. A. Zdiri, F. B. Salem, and N. Derbel, "Optimized Grid-Connected Hybrid Renewable Energy Power Generation: A Comprehensive Analysis of Photovoltaic, Wind, and Fuel Cell Systems," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 13929–13936, Jun. 2024. DOI: https://doi.org/10.48084/etasr.6936

Q. Hassan, S. Algburi, A. Z. Sameen, H. M. Salman, and M. Jaszczur, "A review of hybrid renewable energy systems: Solar and wind-powered solutions: Challenges, opportunities, and policy implications," Results in Engineering, vol. 20, no. 101621, Dec. 2023. DOI: https://doi.org/10.1016/j.rineng.2023.101621

X. Wu, X. Hu, S. Moura, X. Yin, and V. Pickert, "Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array," Journal of Power Sources, vol. 333, pp. 203–212, Nov. 2016. DOI: https://doi.org/10.1016/j.jpowsour.2016.09.157

A. Shaqour, H. Farzaneh, Y. Yoshida, and T. Hinokuma, "Power control and simulation of a building integrated stand-alone hybrid PV-wind-battery system in Kasuga City, Japan," Energy Reports, vol. 6, pp. 1528–1544, Nov. 2020. DOI: https://doi.org/10.1016/j.egyr.2020.06.003

A. M. Yasin and M. F. Alsayed, "Fuzzy logic power management for a PV/Wind microgrid with backup and storage systems," International Journal of Electrical and Computer Engineering (IJECE), vol. 11, no. 4, pp. 2876–2888, Aug. 2021. DOI: https://doi.org/10.11591/ijece.v11i4.pp2876-2888

B. Benlahbib et al., "Experimental investigation of power management and control of a PV/wind/fuel cell/battery hybrid energy system microgrid," International Journal of Hydrogen Energy, vol. 45, no. 53, pp. 29110–29122, Oct. 2020. DOI: https://doi.org/10.1016/j.ijhydene.2020.07.251

H. M. Mohan and S. K. Dash, "Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System," Systems, vol. 11, no. 6, May 2023. DOI: https://doi.org/10.3390/systems11060273

S. Arrar and L. Xioaning, "Energy Management in Hybrid Microgrid using Artificial Neural Network, PID, and Fuzzy Logic Controllers," European Journal of Electrical Engineering and Computer Science, vol. 6, no. 2, pp. 38–47, Apr. 2022. DOI: https://doi.org/10.24018/ejece.2022.6.2.414

A. Kechida et al., "Smart control and management for a renewable energy based stand-alone hybrid system," Scientific Reports, vol. 14, no. 32039, Dec. 2024. DOI: https://doi.org/10.1038/s41598-024-83826-1

A. Sakouchi et al., "Enhanced control of grid-connected multi-machine wind power generation systems using fuzzy backstepping approaches," Energy Reports, vol. 12, pp. 4208–4231, Dec. 2024. DOI: https://doi.org/10.1016/j.egyr.2024.09.077

A. Kechida, D. Gozim, and B. Toual, "Improving the Performance of Hybrid System-Based Renewable Energy by Artificial Intelligence," Power Electronics and Drives, vol. 9, no. 44, Feb. 2025. DOI: https://doi.org/10.2478/pead-2024-0025

S. R. Revathy et al., "Design and Analysis of ANFIS – Based MPPT Method for Solar Photovoltaic Applications," International Journal of Photoenergy, vol. 2022, no. 9625564, May 2022. DOI: https://doi.org/10.1155/2022/9625564

B. T. Gul, I. Ahmad, H. Rehman, and A. Hasan, "Optimized ANFIS-Based Robust Nonlinear Control of a Solar Off-Grid Charging Station for Electric Vehicles," IEEE Access, vol. 13, pp. 20361–20373, Jan. 2025. DOI: https://doi.org/10.1109/ACCESS.2025.3535571

S. Acharya, D. V. Kumar, R. Venu, B. Rajasekhar, G. Rohini, and R. Sathvika, "Enhanced grid integration in hybrid power systems using ANFIS-based distributed controllers," International Journal of Information Technology, Jan. 2025. DOI: https://doi.org/10.1007/s41870-024-02358-z

Downloads

How to Cite

[1]
A. Kechida, D. Gozim, B. Toual, and B. Derradji, “Optimal Control of Bi-directional Converter to Enhance the Performance of an off-Grid Hybrid System”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 3, pp. 23988–23994, Jun. 2025.

Metrics

Abstract Views: 198
PDF Downloads: 298

Metrics Information