_{1}

One of the challenges in accurately estimating Photovoltaic (PV) cell electric performance is the uncertainty of the model equivalent circuit parameters. The parameters considered in the study are the series resistance, shunt resistance, photo current, saturation current, and diode ideality factor. Parameter estimation for the PV cell equivalent circuit model is challenging due to the implicit transcendental relationship of the I-V characteristics of the cell. This paper presents a fuzzy logic based study for estimating the uncertainty of the cell parameters. The model parameters change with temperature and irradiance, are the source of uncertainties. Mathematical programming is used to estimate the fuzzy parameters. The approach is performed on practical data and the results of the analysis provide the estimation of the PV cell parameters. Results of this research yielding better estimated parameters compared with other methods using the Absolute Mean Error (AME).

Renewable energy sources are gaining more interest in recent years and will be an increasingly important part of power generation in the coming years [

Several methods are proposed in the literature to estimate model PV parameters. In [

In [

The present paper introduces a fuzzy-based methodology for the parameters estimation of PV cell. Using the of the PV equivalent circuit,

Accurate estimation of the equivalent circuit parameters is important for control and performance evaluation of the PV cell. Manufacturer datasheet parameters are nominal values that are measured in factory under specific temperature, illumination, and weather conditions. The parameters values changes with time due to aging and the nonlinear transcendental nature of the PV cell. Therefore, for PC cells in different weather and degradation

conditions the parameters must be estimated to obtain more accurate values than that given in the nominal manufacturing datasheet.

Solar photovoltaic power generation employs solar panels also called modules that composed of a number of solar cells containing semi-conductor photovoltaic diode(s) which converts solar radiation into electric current. Mathematically, the solar photovoltaic cell is modeled by current voltage relationship (I-V) which exhibits a non-linear relationship due to the semi-conductor behavior of the cell. This (I-V) characteristic of the solar cell can be presented by a single diode model [

where ^{−}^{23} J/K); q is the electronic charge (1.602176565 × 10^{−}^{19} C) and T is the cell absolute temperature in Kelvin.

The research idea is based on the fact that system parameters could be deduced if their values are bounded by using a fuzzy logic algorithm. Using measured data together with fuzzy logic a set of equations are formed with fuzzy input fuzzy parameters. Then Least squares are used to obtain the optimal estimated parameters based on the formulation in [

The equation of error and signal is given below as follows:

where,

A triangular shaped membership function is used for the input parameters. The range of the signal has been selected appropriate to each variable. _{s}.

Estimation of the five parameters of the PV module is illustrated in this section. Real photovoltaic solar module terminal data

The paper presents a fuzzy-logic based technique to estimate the equivalent circuit parameters of PV cell. The PV cell five equivalent circuit parameters are modeled to be fuzzy parameters. Measurement I-V data of the PV

Ref. [ | Ref. [ | Ref. [ | This work | |
---|---|---|---|---|

I_{ph}(A) | 1.0313 | 1.0339 | 1.0331 | 1.0341 |

I_{sd} (μA) | 3.1756 | 3.076 | 3.6642 | 3.6391 |

R_{s} (Ω) | 1.2053 | 1.203 | 1.1989 | 1.2019 |

G_{sh} (Ω^{−}^{1}) | 0.0014 | 0.0018 | 0.0012 | 0.0015 |

n | 48.2889 | 48.1862 | 48.8211 | 48.1849 |

Error(MAE) | 0.175367 | 0.183851 | 0.026887 | 0.016638 |

cell are used to form a set of equations with fuzzy parameters. Least square methods are used to obtain the optimum parameters. The proposed technique could be applied to estimate the parameters of PV modules in order to account for ageing, performance degradation, and changes of operating conditions. The results obtained are compared with other techniques in the literature yielding better estimated parameters compared with other methods using the Absolute Mean Error (AME).

The research is commissioned and financially supported by Kuwait University Research Sector under grant WI01/13.

Helal Al-Hamadi, (2015) Fuzzy Estimation Analysis of Photovoltaic Model Parameters. Journal of Power and Energy Engineering,03,39-43. doi: 10.4236/jpee.2015.37007