A Comprehensive Review on a PV Based System to Harvest Maximum Power

Javed, Muhammad Yaqoob; Mirza, Adeel Feroz; Hasan, Ali N.; Rizvi, Syed Tahir Hussain; Ling, Qiang; Gulzar, Muhammad Majid; Safder, Muhammad Umair; Mansoor, Majad

doi:10.3390/electronics8121480

Cited by 48 publications

(29 citation statements)

References 127 publications

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“…Due to weak knowledge accepting ability, based on the second rule, the teacher provides more attention to the average group. An average group of students can gain knowledge by Equation (9).…”

Section: Teacher Phase IImentioning

confidence: 99%

“…The modern intelligent controllers are based upon the three main techniques namely fuzzy logic controllers (FLC) [6], neural networks (NN) [7,8], and swarm intelligence (SI) [8]. The most common benefits one achieves by using these intelligent controllers are high efficiency, robustness, and ability to tackle the MPPT problem with the least accurate mathematical modeling of the system, meanwhile, classical techniques pose major drawbacks, discussed later [9]. In the literature many MPPT techniques have been proposed, and depending upon the accuracy, techniques vary significantly by the type of control strategies.…”

Section: Introductionmentioning

confidence: 99%

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Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

et al. 2020

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The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique.

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Section: Teacher Phase IImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

et al. 2020

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“…For maximum power transfer, the DC-DC converter changes its impedance by varying its duty cycle. 23,24 The ideal model contains only the source and a diode, no resistance is taken into account, whereas the practical Equation 1…”

Section: Pv System Cell Modelingmentioning

confidence: 99%

“…Under changing weather conditions or partial shading conditions, the impedance of PV system changes. For maximum power transfer, the DC‐DC converter changes its impedance by varying its duty cycle 23,24 …”

Section: Pv System Cell Modelingmentioning

confidence: 99%

Variable step size fractional incremental conductance for MPPT under changing atmospheric conditions

Khan

Gulzar

Sibtain

et al. 2020

Int J Numerical Modelling

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This paper presents a new modified variable step size Fractional Order Incremental Conductance (FOIC) with maximum power point tracking using Fractional Order PID controller tuned by bio-inspired Particle Swarm Optimization (PSO) to find optimal gain values of fractional integrator order (λ) and fractional derivative order (μ). The classical incremental conductance and FOIC show drawbacks under changing irradiance, oscillation around maximum power point (MPP) which decreases its convergence speed. To resolve these prone a variable step size FOIC is proposed to achieve an adaptive duty cycle via tuning of FOPID through PSO. The robustness of the proposed technique is judged by its steady-state and dynamic response with fast converges, less response time, overshoot, and ripples under changing environmental conditions. Furthermore, the performance of the proposed technique is evaluated by comparing it with a fixed step size conventional incremental conductance algorithm and FOIC.

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“…However, the fuzzy control method also have apparent shortcomings, which relies too much on selecting fuzzy rules and rich experience. In (Javed et al, 2019), the article gives a detailed introduction to the single diode, double diode, and PV components system. Then tests the output characteristics of PV cells under the uniform irradiance condition (UIC) and partial shading condition (PSC) conditions.…”

Section: Introductionmentioning

confidence: 99%

A Novel Maximum Power Point Tracking Strategy Based on Enhanced Real-Time Adaptive Step-Size Modified Control for Photovoltaic Systems

Zhou

Zhang

et al. 2021

Front. Energy Res.

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With the development of society, the demand for energy keeps increasing. Solar energy has received widespread concern for its renewable and environmentally friendly advantages. As one of the most efficient solar energy devices, the output power of photovoltaic (PV) cells is easily affected by the external environment. In order to solve the problem of the maximum power output of PV cells, this paper proposed a maximum power point tracking (MPPT) method. Based on the online particle swarm optimization (PSO) variable step length algorithm, the pulse width modulation (PWM) control module parameters are set according to the parameters of the PV cells’ output voltage. By dynamically adjusting the output voltage step of the PV cells online, the output of the PV cells is stabilized near the maximum power point (MPP). The simulation results concluded that the method and model could accurately adjust the output voltage according to the external environment changes in real time and reduce the voltage fluctuation at the MPP, providing a new idea to solve the problem of MPPT of PV cells.

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A Comprehensive Review on a PV Based System to Harvest Maximum Power

Cited by 48 publications

References 127 publications

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

Variable step size fractional incremental conductance for MPPT under changing atmospheric conditions

A Novel Maximum Power Point Tracking Strategy Based on Enhanced Real-Time Adaptive Step-Size Modified Control for Photovoltaic Systems

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