Author
Listed:
- Dikio C. Idoniboyeobu
(Department of Electrical Engineering, Rivers State University, Port Harcourt,)
- Sunny Orike
(Department of Electrical Engineering, Rivers State University, Port Harcourt,)
- Peace B. Biragbara
(Department of Electrical Engineering, Rivers State University, Port Harcourt)
Abstract
Solar Photovoltaic energy generating system is one of the auspicious renewable energy resources that use the ample energy from the sun with clean, inexhaustible and environment friendly cyclic operations. However, the intermittent nature of the output power of PV systems reduces their reliability in delivering continuous power to customers. In this work, we propose an efficient and precise technique using a fuzzy controller and simulated in MATLAB environment, for tracking maximum power point in PV system. The fuzzy Logic model results were compared with other methods such as Perturb and Observe (P&O) and Proportional Integral Differential (PID) for validation. The results show that the Fuzzy Logic Controller, an Artificial Intelligence technique under various conditions was able to track the peak power point under lesser time - it took the fuzzy model less than 0.4 secs to attain maximum power while the other controllers took more than 0.7 and 0.8 seconds respectively. It was also observed that the fuzzy logic controller showed greater stability when the maximum power point was attained than the other controller. Hence the fuzzy logic controller gave a better overall performance than other conventional controllers.
Suggested Citation
Dikio C. Idoniboyeobu & Sunny Orike & Peace B. Biragbara, 2017.
"Optimization of a Grid Connected Photovoltaic System using Fuzzy Logic Control,"
European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 1(2), November.
Handle:
RePEc:epw:ejece0:v:1:y:2017:i:2:id:19007
DOI: 10.24018/ejece.2017.1.2.7
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejece0:v:1:y:2017:i:2:id:19007. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.