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JACIII Vol.25 No.3 pp. 310-316
doi: 10.20965/jaciii.2021.p0310
(2021)

Paper:

Single-Phase Photovoltaic Grid-Connected Inverter Based on Fuzzy Neural Network

Shenping Xiao*,**,†, Zhouquan Ou*,**, Junming Peng*,**, Yang Zhang*,**, and Xiaohu Zhang*,**

*College of Electrical and Information Engineering, Hunan University of Technology
88 Taishan Road, Tianyuan District, Zhuzhou City, Hunan 412007, China

**Key Laboratory for Electric Drive Control and Intelligent Equipment of Hunan Province
88 Taishan Road, Tianyuan District, Zhuzhou City, Hunan 412007, China

Corresponding author

Received:
September 29, 2020
Accepted:
February 16, 2021
Published:
May 20, 2021
Keywords:
single-phase inverter, fuzzy neural network, PID controller
Abstract
Single-Phase Photovoltaic Grid-Connected Inverter Based on Fuzzy Neural Network

Topology diagram of the fuzzy neural network

Based on a single-phase photovoltaic grid-connected inverter, a control strategy combining traditional proportional–integral–derivative (PID) control and a dynamic optimal control algorithm with a fuzzy neural network was proposed to improve the dynamic characteristics of grid-connected inverter systems effectively. A fuzzy inference rule was established after analyzing the proportional, integral, and differential coefficients of the PID controller. A fuzzy neural network was applied to adjust the parameters of the PID controller automatically. Accordingly, the proposed dynamic optimization algorithm was deduced in theory. The simulation and experimental results showed that the method was effective in making the system more robust to external disruption owing to its excellent steady-state adaptivity and self-learning ability.

Cite this article as:
Shenping Xiao, Zhouquan Ou, Junming Peng, Yang Zhang, and Xiaohu Zhang, “Single-Phase Photovoltaic Grid-Connected Inverter Based on Fuzzy Neural Network,” J. Adv. Comput. Intell. Intell. Inform., Vol.25, No.3, pp. 310-316, 2021.
Data files:
References
  1. [1] Y. Wang, “A Research and Design of Inverter Based on Bipolar SPWM Modulation,” J. of Electric Power, 2014 (in Chinese).
  2. [2] C. T. Wu and L. Y. Wang, “Double-loop SVPWM control strategy for multi-level inverter based on LC filter,” 2015 IEEE Int. Conf. on Applied Superconductivity and Electromagnetic Devices (ASEMD), pp. 395-396, 2015.
  3. [3] W. D. P. Vallejos, “Standalone photovoltaic system, using a single stage boost DC/AC power inverter controlled by a double loop control,” 2017 IEEE PES Innovative Smart Gri Technologies Conf. – Latin America (ISGT Latin America), pp. 1-6, 2017.
  4. [4] W. Fang, Z. Yi, and W. Zhen, “Research on a kind of multiple control strategy for parallel connected inverters,” Proc. of IEEE 2011 10th Int. Conf. on Electronic Measurement & Instruments (ICEMI’2011), Vol.4, pp. 267-269, 2011.
  5. [5] M. Jahanbakhshi, B. Asaei, and B. Farhangi, “A novel deadbeat controller for single phase PV grid connected inverters (ICEE),” 2015 23rd Iranian Conf. on Electrical Engineering, pp. 1613-1617, 2015.
  6. [6] P. Mitra, C. Dey, and R. K. Mudi, “An improved fuzzy PID controller with fuzzy rule based set-point weighting technique,” 2016 2nd Int. Conf. on Control, Instrumentation, Energy and Communication (CIEC), pp. 40-44, 2016.
  7. [7] Y.-S. He, “Grid-Connected Fuzzy-PID Control of PV Power Generation System,” Power System and Clean Energy, Vol.29, No.2, pp. 85-89, 2013.
  8. [8] P. Mohammadi, B. Azimian, and A. Shahirinia, “A Novel Double-Loop Control Structure Based on Fuzzy-PI and Fuzzy-PR Strategies for Single-Phase Inverter in Photovoltaic Application,” 2018 North American Power Symp. (NAPS), pp. 1-6, 2018.
  9. [9] H. P. Nguyen and V. Kreinovich, “Towards Making Fuzzy Techniques More Adequate for Combining Knowledge of Several Experts,” J. Adv. Comput. Intell. Intell. Inform., Vol.24, No.5, pp. 583-588, 2020.
  10. [10] Y. Zhang, Z. Lei, S. Li, and H. Zhang, “Research on BP neutral network based grid-connected photovoltaic inverter,” 2016 Chinese Control and Decision Conf. (CCDC), pp. 506-509, 2016.
  11. [11] G. Han, Y. Xia, and W. Min, “A grid-connected current control technique of single-phase voltage source inverter based on BP neural network,” 2012 IEEE Int. Conf. on Computer Science and Automation Engineering (CSAE), Vol.1, pp. 547-551, 2012.
  12. [12] J. Hu, L. Zhou, and Y. Wang, “Comparative Analysis of Risk Assessment for Technical Standards Alliance Based on BP Neural Network and Fuzzy AHP Methods,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.6, pp. 838-845, 2018.
  13. [13] J. Liu, “MATLAB simulation of advanced PID control,” Electronics Industry Press, 2004 (in Chinese).
  14. [14] D. Xu, “Modeling and control of power electronic system,” Machinery Industry Press, 2006 (in Chinese).

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Last updated on Sep. 21, 2021