Optimization and control of a photovoltaic powered water pumping system

Chikh, A.; Chandra, Ambrish

doi:10.1109/epec.2009.5420374

Cited by 14 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Combining the previous equations, we obtain

I = I_{ph} - I_{o} ()(, \exp ()(, \frac{q ()(, V + R_{s} I)}{k A T}) - 1) - ()(, \frac{V + R_{s} I}{R_{sh}})

As discussed previously, the reference I − V curve of the solar cell can be expressed by (4) for a solar irradiance G of 1000 W/m 2 and a cell temperature T c of 25°C at AM 1.5 radiation spectrum, which are known as the standard test conditions (STC). Using other conditions ( G , T c ), the I − V curve can be computed using the following set of equations [2, 5, 9, 20–22] in accordance to the international standard IEC 60891 [23]

T_{c} = T_{a} + \frac{G}{G_{r}} (NOCT - T_{normala, normalr})

normalΔ I = α ()(, \frac{G}{G_{ref}}) ()(, T_{c} - T_{normalc, ref}) + ()(, \frac{G}{G_{ref}} - 1) I_{sc, ref}

normalΔ V = - β ()(, T_{c} - T_{normalc ref}) - R_{s} normalΔ I

where Δ I and Δ V are the changes in cell current and voltage due to variation in climatic conditions, T a is the ambient temperature, T a,r = 20°C is the nominal ambient temperature, NOCT is the nominal operating cell temperature, G r = 800 W/m 2 is the nominal solar irradiance, α is the cell's short‐circuit current temperature coefficient, β is the cell's open‐circuit voltage temperature coefficient, G ref = 1000 W/m 2 is the solar irradiance at STC, T c,ref = 25°C is the cell temper...…”

Section: Pv Cell Modellingmentioning

confidence: 99%

“…Finally, owing to a change in climatic conditions ( G , T c ), a translation of the STC curve will take place and the new values of current and voltage will be [15, 20]

I_{n} = I_{ref} + normalΔ I

V_{n} = V_{ref} + normalΔ V

where I ref and V ref are, respectively, the cell current and voltage at STC given by manufacturers of PV modules, I n and V n are the new values of the cell current and voltage computed due to a change in climatic conditions; they are computed related to the reference current and voltage I ref and V ref .…”

Section: Pv Cell Modellingmentioning

confidence: 99%

“…It can be seen that the diode current is a non‐linear function of the cell voltage and temperature. By simplification, it can be rewritten as follows [5, 20, 26]

\begin{matrix} right leftthickmathspace.5em \\ I_{d} & = I_{rr} {(][, \frac{T_{c}}{T_{normalc, ref}})}^{3} \exp (\frac{q E_{normalG}}{k A} (][, \frac{1}{T_{normalc, ref}} - \frac{1}{T_{normalc}})) \\ \times (\exp (\frac{q (V + R_{normals} I)}{k A T_{normalc}}) - 1) = h (V, T_{normalc}) \end{matrix}

Using expressions (10) and (11), it is easy to verify that the solar cell current is composed of a linear combination of two currents, I ph and I d , where the first one is linearly dependent on the solar irradiance and temperature and the second is non‐linearly dependent on the cell voltage and temperature as

I ()(, V, G, T_{c}) = I_{ph} ()(, G, T_{c}) - I_{d} ()(, V, T_{c})

or f false(V, G, T false) = g ()(, G, T_{c}) - h ()(, V, T_{c})

It can be seen clearly from expressions (14), (15a) and (15b) that the diode current I d = f ( V , T c ) does not depend on solar irradiance, but depends only on the cell voltage and temperature; therefore solar irradiance G can be eliminated from the input of the junction current diag...…”

Section: Pv Cell Modellingmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive neuro‐fuzzy based solar cell model

Chikh

Chandra

2014

IET Renewable Power Generation

View full text Add to dashboard Cite

The modelling of photovoltaic (PV) solar cells using a hybrid adaptive neuro-fuzzy inference system (ANFIS) algorithm is presented. It is based on the decomposition of the cell output current into photocurrent and junction current. The photocurrent is linearly dependent on solar irradiance and cell temperature; consequently, its analytical computation is done easily. However, the junction current is highly non-linear and depends on cell voltage and temperature. Therefore, its analytical computation is complicated and the manufacturers do not supply any information about this parameter. Moreover, there is no way to measure it physically. Therefore, it is proposed to use the ANFIS algorithm as a powerful technique in order to estimate this current and reconstruct the output PV cell current using the photocurrent. The model validation is based on the gradient descent and chain rule applied to a set of data different than the one used for training process. The advantage of the proposed model is that only one climatic parameter is used as the input to the ANFIS algorithm, which makes it less sensitive to climatic variations.

show abstract

“…Combining the previous equations, we obtain

I = I_{ph} - I_{o} ()(, \exp ()(, \frac{q ()(, V + R_{s} I)}{k A T}) - 1) - ()(, \frac{V + R_{s} I}{R_{sh}})

T_{c} = T_{a} + \frac{G}{G_{r}} (NOCT - T_{normala, normalr})

normalΔ I = α ()(, \frac{G}{G_{ref}}) ()(, T_{c} - T_{normalc, ref}) + ()(, \frac{G}{G_{ref}} - 1) I_{sc, ref}

normalΔ V = - β ()(, T_{c} - T_{normalc ref}) - R_{s} normalΔ I

Section: Pv Cell Modellingmentioning

confidence: 99%

“…Finally, owing to a change in climatic conditions ( G , T c ), a translation of the STC curve will take place and the new values of current and voltage will be [15, 20]

I_{n} = I_{ref} + normalΔ I

V_{n} = V_{ref} + normalΔ V

Section: Pv Cell Modellingmentioning

confidence: 99%

“…It can be seen that the diode current is a non‐linear function of the cell voltage and temperature. By simplification, it can be rewritten as follows [5, 20, 26]