243
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A novel combined Fuzzy-M5P model tree control applied to grid-tied PV system with power quality consideration

, &
Pages 3125-3147 | Received 09 Nov 2021, Accepted 24 Mar 2022, Published online: 17 Apr 2022
 

ABSTRACT

A novel control strategy based on an effective combination of the fuzzy logic controller and the M5P decision tree algorithm (Fuzzy-M5P) for a grid-interfaced solar energy system is proposed in this paper. The aim is to benefit from fuzzy logic advantages using its resulting datasets along with the fast model tree functionality. This mixed control has the ability to cope effectively with the large computation time and complexity of fuzzy logic controllers especially when embedded systems or real-time implementation are considered. Using a photovoltaic (PV) inverter with active filtering capability, the primary objective is to provide a grid-solar topology with a maximum PV energy extraction and power quality enhancement. For the inverter control, the M5P model was tested in the indirect current technique. This harmonic generation method is very efficient and its performances are entirely dependent on the chosen dc-link controller. Moreover, a novel maximum power point tracking technique (MPPT) based on the M5P model tree is performed in which data inputs are collected from fuzzy logic-based MPPT. WEKA and MATLAB software are used to translate the model by formulating a simple hierarchical program structure. To validate the effectiveness of the proposed control, simulation, and experimental tests are done under steady and dynamic conditions. The final developed algorithm based on simple IF-ELSE rules shows promising results, it can reduce harmonic distortions to 2.77%, perfectly compensates reactive power with almost unity power factor, and enhances dynamic performances with fast transient response.

List of symbols and abbreviations

Ts=

Sampling-time

PV=

Photovoltaic system

M5P=

Pruned M5 model tree

MPPT=

Maximum power point tracking

FLC=

Fuzzy logic control

ANN=

Artificial neural network

APF=

Active power filter

ICC=

Indirect current control

THD=

Total harmonic distortion

PLL=

Phase locked-loop

VSI=

Voltage source inverter

idc-link=

Output dc current from the regulator

iS=

Source current

iF=

Filter current

iL=

Load current

Vs=

Source voltage

Vdc=

DC-Link voltage

P=

Active power

Q=

Reactive power

D=

Harmonic power

C=

DC bus capacitor

NL=

Nonlinear load

PI=

Proportional-Integral

Linv=

Filter inductance

Lg=

Source inductance

Rd=

Resistance of NL

Ld=

Inductance of NL

LMT=

Logistic model tree

DT=

Decision tree

LUT=

lookup table

PO=

Perturb & observe technique

INC=

Incremental conductance technique

MAE=

The mean absolute error

RMSE=

The root mean square error

R=

The correlation coefficient

Disclosure statement

No potential conflict of interest was reported by the author(s).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.