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Maximum power point tracking of a standalone photovoltaic system using electromagnetic field optimization algorithm

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Abstract

There are non-stop efforts being put into enhancing the performance of the available maximum power point tracking methods and proposing new tracking methods. In this paper, a novel maximum power point tracking method based on a physics-inspired metaheuristic algorithm called Electromagnetic Field Optimization algorithm is proposed. The methodology of applying the Electromagnetic Field Optimization method on the maximum power point tracking problem is explained. The proposed method is applied to control the duty cycle of a DC–DC converter in a standalone photovoltaic system. The performance of the proposed method is evaluated against the Cuckoo Search Algorithm method, the Particle Swarm Optimization method, the Perturb and Observe method, and the Incremental Conductance method. A simulation test using MATLAB/Simulink software was conducted for varied sun irradiance levels under fixed temperature and load conditions. An experimental test was also conducted under fixed load and fixed weather conditions. The proposed method achieved tracking efficiencies of 100% and 80.14% in the simulation and experimental tests, accordingly. The superiority of the proposed method over the other applied metaheuristic-based methods is highlighted as the proposed method achieved short tracking times, no steady-state oscillations, and no duty cycle oscillations in both tests. The easiness of tuning the proposed method’s parameters is also an advantage of it.

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Abbreviations

CO2 :

Carbon dioxide

\({R}_{\mathrm{i}}\) :

Input resistance of the DC–DC converter (Ω)

\({R}_{\mathrm{opt}}\) :

Optimal internal resistance of PV module (Ω)

\(D\) :

Duty cycle

\({D}_{i}\) :

Duty cycle at index \(i\)

\(K\) :

Random index from the neutral field

\(P\) :

Random index from the positive field

\(N\) :

Random index from the negative field

\({D}_{K}\), \({D}_{P}\), and \({D}_{N}\) :

Duty cycles at \(K\), \(P\), and \(N\)

\({L}_{1}, {L}_{2}\) :

Inductors of the DC–DC converter (H)

\(S\) :

MOSFET of the DC–DC converter

\(D\) :

Diode of the DC–DC converter

\({C}_{1}\) :

Series capacitor of the DC–DC converter (F)

\({C}_{2}\) :

Output capacitor of the DC–DC converter (F)

\({C}_{\mathrm{in}}\) :

Input capacitor of the DC–DC converter (F)

\(N\_\mathrm{emp}\) :

Number of electromagnetic particles

\(P\_\mathrm{field}\) :

A portion of the population assigned to the positive field (ranges between 0.05 and 0.1)

\(N\_\mathrm{field}\) :

A portion of the population assigned to the negative field (ranges between 0.4 and 0.5)

\(Ps\_\mathrm{rate}\) :

Probability of selecting an electromagnetic particle from the positive field (ranges between 0.1 and 0.4)

\(R\_\mathrm{rate}\) :

Probability of changing one electromagnet with a randomly generated electromagnet

\(r\) :

A random number between [0, 1]

\(K\) :

Lévy multiplying coefficient

\({P}_{a}\) :

Probability of discovering and replacing the worst nest by a new nest

\(w\) :

Inertia weight

\({c}_{1}\), \({c}_{2}\) :

Acceleration coefficients

PV:

Photovoltaic

MPPT:

Maximum power point tracking

MPP :

Maximum power point

EFO:

Electromagnetic field optimization

CSA:

Cuckoo search algorithm

PSO:

Particle swarm optimization

P&O:

Perturb and observe

INC:

Incremental conductance

SEPIC:

Single ended primary inductor converter

T.E.:

Tracking efficiency (%)

T.T.:

Tracking time (s)

S.S.O.:

Steady-state oscillations

Ave.:

Average

\(\varphi\) :

The golden ratio (1.618)

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Authors and Affiliations

  1. College of Engineering and Applied Sciences, American University of Kuwait, Salmiya, Kuwait

    Abeer Imdoukh

  2. Department of Electrical Engineering, College of Engineering and Petroleum, Kuwait University, Al-Shadadiya, Kuwait

    Mohamed Zribi

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  1. Abeer Imdoukh
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  2. Mohamed Zribi
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Contributions

AI proposed the methodology, investigated the project resources, performed the simulation and the experimental tests, analyzed the results, and drafted, reviewed, and submitted the final manuscript. MZ supervised the work.

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Correspondence to Abeer Imdoukh.

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Imdoukh, A., Zribi, M. Maximum power point tracking of a standalone photovoltaic system using electromagnetic field optimization algorithm. Int J Energy Environ Eng 14, 961–971 (2023). https://doi.org/10.1007/s40095-023-00559-z

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