Abstract
Due to the nonlinear property of the PV panels, there are a few significant restrictions and limitations in the PV solar system. The PV panels always have to depend on environmental conditions such as temperature and solar radiation to generate efficient power. This paper proposed an optimum control system that can handle the uncertainties and nonlinearities of any system by using the Fuzzy Logic Control system (FLC). The proposed system utilized an FLC system for a DC-DC boost converter, tracking the PV panel’s maximum power point (MPPT). A PI control system is also used to maintain the continuous power supply for an optimum battery charging system for the DC-DC Buck converter. The goal is to provide constant voltage and appropriate current for charging the battery. It will increase the system efficiency and reduce the losses. It would also increase the battery life cycle and help the battery to charge fast. There are several MPPT methods found in the literature. The FLC can make a precise decision by considering the environmental state of the system. It can get a response to nonlinear environmental conditions instantly. The proposed system yielded an expected accuracy of 92% to 96%, with a system efficiency of 76% to 83%. Besides, it does not require any knowledge about the system since it is a rule-based system. The entire system has been designed in MATLAB/Simulink. The simulation results have been analyzed under 9 environmental states in a 1.0 s period.
ABSTRAK: Berdasarkan struktur tak linear panel PV, terdapat beberapa faktor kekangan yang jelas dan had tertentu dalam sistem solar PV. Panel PV selalunya sering bergantung kepada kondisi persekitaran seperti suhu dan radiasi solar bagi menghasilkan tenaga optimum. Kajian ini mencadangkan sistem kawalan optimum yang dapat mengawal ketidaktentuan dan ketidak linearan apa-apa sistem menggunakan sistem Kawalan Logik Fuzi (FLC). Sistem yang dicadangkan ini menggunakan sistem FLC bagi penukaran penggalak DC-DC, mengesan titik tenaga maksimum panel PV (MPPT). Sistem Kawalan PI turut digunakan bagi menyediakan bekalan tenaga berterusan untuk sistem pengecas bateri optimum melalui penukaran Balik DC-DC. Matlamat adalah bagi menghasilkan voltan berterusan & arus mencukupi bagi mengecas bateri. Ia dapat meningkatkan kecekapan sistem dan mengurangkan pembaziran tenaga. Ia juga dapat meningkatkan kitaran hayat bateri dan membantu bateri mengecas dengan cepat. Terdapat beberapa kaedah MPPT dijumpai dalam kajian terdahulu. FLC dapat menghasilkan keputusan tepat dengan mengambil kira keadaan persekitaran pada sistem tersebut. Ia dapat memberi respon kepada keadaan persekitaran tak linear dengan serta merta. Sistem yang dicadangkan menghasilkan ketepatan yang dijangkakan sebanyak 92% hingga 96%, dengan kecekapan sistem sebanyak 76% hingga 83%. Selain itu, ia tidak memerlukan apa-apa pengetahuan tentang sistem tersebut kerana sistem ini berdasarkan aturan. Keseluruhan sistem dibangunkan menggunakan MATLAB/Simulink. Dapatan simulasi dikaji menggunakan 9 tahap persekitaran dalam tempoh 1.0 s.
Subject
Applied Mathematics,General Engineering,General Chemical Engineering,General Computer Science
Reference14 articles.
1. Aranya SDS, Sathyamoorthi S, Gandhiraj R. (2015) A fuzzy logic-based energy management system for a microgrid. ARPN Journal of Engineering and Applied Sciences, 10(6): 2663-2669.
2. Rai N, Rai B. (2018) Control of fuzzy logic-based PV-battery hybrid system for stand-alone DC applications. Journal of Electrical Systems and Information Technology, 5(2): 135-143. https://doi.org/10.1016/j.jesit.2018.02.007
3. Greeshma VJ, Sasidharan R. (2016) Battery charging control using fuzzy based controller in a photovoltaic system, International Advanced Research Journal in Science, Engineering and Technology, Sp. Issue of National Conference on Emerging Trends in Engineering and Technology (NCETET’16), 3(3): 114-117. http://iarjset.com/upload/2016/si/NCETET-16/IARJSET-NCETET%2021.pdf
4. Yilmaz U, Kircay A, Borekci S. (2018) PV system fuzzy logic MPPT method and PI control as a charge controller. Renewable and Sustainable Energy Reviews, 81: 994-1001. https://doi.org/10.1016/j.rser.2017.08.048
5. Abdelhak B, Abdelhalim B, Layachi Z, Sief EB, Amor F. (2018) Fuzzy logic controller to improve photovoltaic water pumping system performance. 6th International Renewable and Sustainable Energy Conference (IRSEC), pp 1-5. DOI: 10.1109/IRSEC.2018.8702841
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Performance Analysis and Comparison Between Fuzzy Logic Algorithm and PI-Controller in Photovoltaic System;2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI);2023-12-27
2. A Comparative Study of Energy Control Strategies for Photovoltaic-Battery Systems;2023 IEEE Third International Conference on Signal, Control and Communication (SCC);2023-12-01