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Malik Sameeullah1, Dr. Akhilesh Swarup2
World Energy and Environment Technology Coventry, CV3 1PG, UK; Email: [email protected]
Fuzzy Logic Based Adaptive Perturbation & Observation MPPT for Photovoltaic System
6. Conclusions
1. Objectives
2. Solar Photovoltaic Model
3. Concept of MPPT and P&O
International Seminar on Renewable Energy and Sustainable Development Royal University of Bhutan, Thimphu, Bhutan 15-17th June, 2015 Bhutan
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School of Renewable Energy and Efficiency National Institute of Technology Kurukshetra Kurukshetra, India-136119
To study the mathematical model of solar PV module Explain the concept of Maximum Power Point Tracking Study the working methodology of Perturbation and Observation (P&O) MPPT Design of FLC based adaptive P&O MPPT Results comparison of P&O and FLC MPPT controller
The basic unit of the PV system is PV cell. The photovoltaic cell works on the principle of photo effect and converts part of
sun energy into electricity. For commercial application, the PV cells are connected in series and parallel
manner and known as PV module. A PV module is an Irradiance Control current source with lossy diode and series-
shunt resistance in parallel.
𝐼 = 𝐼𝑃𝑉 − 𝐼𝑜 exp( 𝑉+𝑅𝑠𝐼𝑎𝑉𝑡
) − 1 − 𝑉+𝑅𝑠𝐼𝑅𝑝ℎ
𝐼𝑜 = (𝐼𝑠𝑠𝑠 + 𝐾𝐼∆𝑇)/ {exp 𝑉𝑜𝑜𝑜+𝐾𝑉∆𝑇𝑉𝑡
− 1}
where IPV :Photo current, Io :Diode saturation current, a :Ideality factor, k : Boltzman constant, Rs :Series Resistance, Rph :Shunt Resistance, KI and KV : Temperature coefficient, Iscn :Short circuit current, Vocn :Open circuit voltage, Ns : No. of cells in series
Three unknowns in PV equation are Rph, Rs and a For Si-PV module, the approximate value of a=1.22 Sometimes, Rph=Inf and Rs =0 is considered Iterative methods are used for Rph and Rs calculation
Pseudo code for the calculation of Rs and Rph 1. Initialize with datasheet values, nimax=10000 2. Set Rs=0 3. Calculate Rph=Rph,min 4. Loop iteration
A. Calculate Rph B. Solve I=f(V) for (0<V<Voc) C. Calculate P for (0<V<Voc) D. Choose the maximum power (Pmth) E. Find Perror = Pm,e – Pmth F. If Perror < tol, than go to step 5 G. If n > nimax, than go to step 6
5. Print Rs and Rph and exit 6. Print Rs = 0 and Rph = Rph,min and exit (Pm,e is the maximum output power at STC)
𝑅𝑝 = 𝑉𝑚𝑝 𝑉𝑚𝑝 + 𝐼𝑚𝑝𝑅𝑠 /(𝑉𝑚𝑝𝐼𝑚𝑝 − 𝑉𝑚𝑝𝐼𝑜 exp𝑉𝑚𝑝 + 𝐼𝑚𝑝𝑅𝑠
𝑉𝑡+ 𝑉𝑚𝑝𝐼𝑜 − 𝑃𝑚,𝑒)
It is a procedure to track Maximum Power Point (MPP) under variable atmospheric condition.
For MPPT, it is essential that load line must intersect MPP. Generally, load line and MPP line are far apart. DC-DC convert is used to adjust the apparent load across
the PV array. Perturbation and Observation (P&O) MPPT
It is the most commonly used MPPT algorithm. It perturbs the output voltage and observe the corresponding change in power. The algorithm and working procedure of P&O are explained in Figure 3 and
Figure 4. It has some major drawbacks as follows:
(a) Power tracking speed during rapid change in irradiance (b) Higher oscillation near MPP (c) Duty step selection is an issue, which causes slow time response and higher
oscillation loss.
A fuzzy logic based MPPT is proposed and implemented. It is concluded that: FLC MPPT reduces the oscillation near MPP. Overall tracking time of MPPT has been improved by using FLC. For accurate result, a proper selection of fuzzy rule and Membership Functions is essential. More experience can be gained through experimental work.
4. Proposed Fuzzy Logic MPPT Controller Fuzzy logic is a most widely used Artificial Intelligence control scheme. The fuzzification, fuzzy logic inference system and defuzzification are the three
major stages of FLC. A FLC with buck converter used for the MPPT, is shown in Figure 5.
The IF-THAN based rules are used for the automatic control of output linguistic variable.
The change in current (ΔI) and change in power (ΔP) are the two input of FLC . A fuzzy logic works on the principle of human behavior and performance can be
improved by observing the result of past experience. Two different sets of Membership Functions (MFs) and set of rules are shown in
Figure 6.
Rule for Fuzzy Logic Controller If ΔP>0 II ΔV>0, than ΔD is either PS, PM or PB If ΔP>0 II ΔV<0, than ΔD is either NS, NM or NB If ΔP<0 II ΔV>0, than ΔD is either NS, NM or NB If ΔP<0 II ΔV>0, than ΔD is either PS, PM or PB
Fig. 5 Matlab Simulink model of Solar PV System with Fuzzy Logic MPPT controller
[Notation: N: Negative, P: Positive, ZE: Zero, PS: Positive Small, PM: Positive Medium, PB: Positive Big, S: Small, NS: Negative Small, NM Negative Medium, NB: Negative Big]
Set 1 Set2 Fig. 6 Fuzzy membership function (MF) and Fuzzy rules
5. Simulation Results and Analysis Responses of simulation are shown in Figure 7.
From the responses, it is observed that:
1. Output power for P&O MPPT is oscillating near MPP.
2. The FLC MPPT (set 1) is able to reduce oscillation.
3. For low Irradiation, the FLC (set 1) is inefficient
4. The modified FLC MPPT (set 2) has a better response.
5. Speed of FLC MPPT tracking is higher than P&O MPPT
Fig 7 Analysis of the MPPT controller response
Fig. 2 P-V curve of PV module
Fig. 1 Diode model of PV module
Fig. 3 Algorithm of Perturbation and Observation MPPT Fig. 4 Demonstration of P&O MPPT
1: PG Student, School of Renewable Energy and Efficiency, 2: Professor, Department of Electrical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India-136119 Email: [email protected], [email protected]
WEENTECH Financial Support for this work:
Acknowledgement The first Author is thankful for receiving the financial support regarding the presentation of this paper, by Advancetech India Pvt. Ltd., Chandigarh.
