Preview

«System analysis and applied information science»

Advanced search

A STRUCTURE APPROACH FOR A PHOTOVOLTAIC STATION CONTROL BASED ON ADAPTIVE FUZZY AGENT

https://doi.org/10.21122/2309-4923-2017-3-40-48

Abstract

The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP) a complicated problem. To overcome this problem, many maximum power point tracking (MPPT) control algorithms have been presented. Fuzzy logic (FL) has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in the FLC will be based on the use of asymmetrical membership functions to compensate for the asymmetrical P-V curve of solar panel.

About the Authors

I. A. Elzein
Belarusian National Technical University
Belarus
Master of Science in Electronics Engineering Technology, Wayne State University, Michigan-USA


Yu. N. Petrenko
Belarusian National Technical University
Belarus
Associate Professor, PhD in Engineering


References

1. Elzein Imad, Petrenko Yury. An Integration of a Predictive Control Model and MPPT for PV Station. IEEE Region 8, International Conference on Smart Systems and Technologies (SST 2016), proc. Of IEEE trans., Croatia, IEEE, region 8, pp. 275–280, ISBN: 978–1-5090–3718–6, IEEE catalog number: CFP16G03-PRT

2. Elzein, I. Predictive Model Control for Photovoltaic Station. / Imad Elzein, Y. N. Petrenko // Наука – образованию, производству, экономике: материалы. 14-й. Междунар. науч.-техн. конф., Минск, июнь, 2016 г. В 4 т. / Белорус, национ. техн. ун-т; редкол.: Б. М. Хрусталев [и др.]. – Минск, 2016. – Т. 1. – С. 238.

3. Elzein I. Imad. An Evaluation of Photovoltaic Systems MPPT Techniques Under the Characteristics of Operational Conditions./ Imad Elzein, Y. N. Petrenko // System Analysis and Applied Information Science. – 2017. – № 2, P. 30–38.

4. Impulse control hybrid electrical system / Imad Elzein [et al.] // System Analysis and Applied Information Science, – 2016. – № 4, – P. 46–52.

5. Elzein, Imad. Аналитические методы определения параметров режима максимальной выходной мощности солнечных батарей / Imad Elzein, Ю. Н. Петренко // Информационные технологии в образовании, науке и производстве: IV Международная научно-техническая интернет-конференция, 18–19 ноября 2016 г. Секция Информационные технологии в производстве и научных исследованиях [Электронный ресурс]. – [Б. и.], 2016. Режим доступа: http://rep. bntu.by/handle/data/27252. Дата доступа: 30.06.2017.

6. Nevzat Onat. Recent Developments in Maximum Power Point Tracking Technologies for Photovoltaic Systems. International Journal of Photo energy, Vol. 2010, Article ID 245316, 11 pp., doi:10.1155/2010/245316.

7. Elzein, I. Maximum Power Point Tracking System for Photovoltaic Station: a Review. System Analysis and Applied Information Science, No. 3, 2015, pp.15–20.

8. D. P. Hohm and M. E. Ropp, «Comparative study of maximum power point tracking algorithms using an exper mental, programmable, maximum power point tracking test bed,» in Proc. Photovoltaic Specialist Conference, pp. 1699–1702, 2000.

9. K. H. Hussein, I. Muta, T. Hoshino, and M. Osakada, «Maximum power point tracking: an algorithm for rapidly changing atmospheric conditions» IEE Proc.-Gen. Transm. Distrib., 1995. Vol. 142, pp. 59–64.

10. Mattavelli, P., Rossetta, L., Spiazzi, G., &Tenti, P. General purpose fuzzy logic controller for DC-DC converters. IEEE Transactions on Power Electronics, 12(1), 1997, pp. 79–85.

11. E. Koutroulis, F. Blaabjerg. «A New Technique for Tracking Global Maximum Power Point of PV Arrays Operating Under Partial-Shading Conditions» IEEE JORNAL OF PHOTOVOLTAICS, vol. 2, no. 2, April 2012.

12. Petrenko, Y. N. Fuzzy logic and genetic algorithm technique for non-liner system of overhead crane / Y. N. Petrenko, S. E. Alavi. Computational Technologies in Electrical and Electronics Engineering (SIBIRCON), 2010 IEEE Region 8 International Conference, 11–15 July 2010. pp. 848–851.


Review

For citations:


Elzein I.A., Petrenko Yu.N. A STRUCTURE APPROACH FOR A PHOTOVOLTAIC STATION CONTROL BASED ON ADAPTIVE FUZZY AGENT. «System analysis and applied information science». 2017;(3):40-48. https://doi.org/10.21122/2309-4923-2017-3-40-48

Views: 866


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2309-4923 (Print)
ISSN 2414-0481 (Online)