PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions

Al-Wesabi, Ibrahim; Shafik, M.B.; Deng, Min; Sarhan, Mohammad Abu; Fang, Zhijian; Alareqi, Ahmed. G.; Almoqri, Tariq; Al-Rassas, Ayman. M.

doi:10.23919/cjee.2020.000035

Cited by 90 publications

(33 citation statements)

References 28 publications

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“…According to Thevenin's theory, when the value of the power supply's output impedance equals the load, the output will reach the maximum value. Therefore, it is necessary to add an https://www.indjst.org/ Boost converter circuit (13,54) . impedance transformation circuit in the MPPT control system, making the power supply and load reach the state of impedance matching and adjust the output power (55) .…”

Section: Maximum Power Point Tracking Control Algorithmsmentioning

confidence: 99%

“…Each particle adjusts its position X i j in the limited search area according to its best position X Pbest.i j , All the particles are in the best position X Gbest.i j as seen in Figure 13 . The following formula can be used through the optimal search process to explain in detail (54) . The first modification is the velocity step function V t i j Adopted by the classical particle swarm optimization algorithm.…”

Section: Modified Particle Swarm Optimization (Mpso)mentioning

confidence: 99%

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Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Al-Wesabi¹,

Fang²,

Ameur³

et al. 2021

IJST

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Objectives: To improve the reduction of photovoltaic system's power output under various resistance load. Additionally, partial shaded conditions (PSCs) lead to several peaks on photovoltaic (PV) curves, which decrease conventional techniques' efficiency and in these (PSCs), standard equations might not be implemented entirely, therefore, the mathematical model of PV array is compulsory to modify and re-establish as well as it is compulsory to apply some methods based on artificial intelligence to develop the performance of traditional techniques. Methods: This work has modified and re-established the mathematical model of PV array under (PSCs) which are recognized and verified using MATLAB/Simulink environment. Also, heuristic algorithms (Cuckoo Search Algorithm (CSA) and Modified Particle Swarm Optimization (MPSO)) have been suggested and applied with PV system to promote output power under various resistance load, varying weather conditions and (PSCs). Moreover, these suggested algorithms can improve the dynamic response and steady-state PV systems' performance simultaneously and effectively comparing to the Modified Perturb and Observe (MP&O) and Artificial Neural Network (ANN) methods. Findings: The proposed methods are examined under various resistance load, several scenarios for (PSCs) and non-uniform irradiation levels to investigate its effectiveness. The results ensure that proposed tracker based on Cuckoo Search Algorithm (CSA) can distinguish between the global and local maximum peaks of PV system effectively with efficiency of 99% comparing to other MPPT approaches. So, all approaches mentioned above are implemented to improve the output power of PV system in Yemen. Novelty: Modified and re-established the mathematical model of PV array under (PSCs) and also, proposed a heuristic algorithms (CSA) and (MPSO)

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Section: Maximum Power Point Tracking Control Algorithmsmentioning

confidence: 99%

Section: Modified Particle Swarm Optimization (Mpso)mentioning

confidence: 99%

Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Al-Wesabi¹,

Fang²,

Ameur³

et al. 2021

IJST

Self Cite

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“…The algorithms differ in control structure, accuracy, required sensors, response time, cost, simplicity and dynamic behaviour during environmental changes [3]. Based on the control structure, these techniques have been classified into two main groups, namely: direct and indirect techniques [4].…”

Section: Introductionmentioning

confidence: 99%

Modified Variable Step-Size Incremental Conductance MPPT Technique for Photovoltaic Systems

et al. 2021

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A highly efficient photovoltaic (PV) system requires a maximum power point tracker to extract peak power from PV modules. The conventional variable step-size incremental conductance (INC) maximum power point tracking (MPPT) technique has two main drawbacks. First, it uses a pre-set scaling factor, which requires manual tuning under different irradiance levels. Second, it adapts the slope of the PV characteristics curve to vary the step-size, which means any small changes in PV module voltage will significantly increase the overall step-size. Subsequently, it deviates the operating point away from the actual reference. In this paper, a new modified variable step-size INC algorithm is proposed to address the aforementioned problems. The proposed algorithm consists of two parts, namely autonomous scaling factor and slope angle variation algorithm. The autonomous scaling factor continuously adjusts the step-size without using a pre-set constant to control the trade-off between convergence speed and tracking precision. The slope angle variation algorithm mitigates the impact of PV voltage change, especially during variable irradiance conditions to improve the MPPT efficiency. The theoretical investigations of the new technique are carried out while its practicability is confirmed by simulation and experimental results.

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“…The current solution for controlling the solar power system is to inject the maximum power into the power grid [15] ; however, this method is only suitable when solar power contributes insignificantly to the grid power capacity. Maximum power point tracking (MPPT) [16] can be performed to extract the maximum power from a solar array [17] ; however, it does not contribute to the system inertia [18] . Such a problem can be mitigated using large-scale grid power.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic controller-based synchronverter in grid-connected solar power system with adaptive damping factor

Yap

Beh

Sarimuthu

2021

Chin. J. Electr. Eng.

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In recent years, renewable energy sources, specifically solar power systems, have developed rapidly owing to their technological maturity and cost effectiveness. However, its grid integration deteriorates frequency stability because of insufficient rotating masses and inertial response. Hence, a synchronverter, which is an inverter that mimics the operation of a synchronous generator, is crucial to interface solar power in a power grid. It stabilizes the power grid by emulating a virtual inertia. However, a conventional proportional-integral (PI)-based synchronverter is not equipped with an adaptive damping factor (D p ) or a digitalized smart controller to manage fast-responding solar inputs. Hence, a novel fuzzy logic controller (FLC) framework is proposed such that the synchronverter can operate in a grid-connected solar power system. In this study, D p is controlled in real time using an FLC to achieve balance between speed and stability for frequency error correction based on frequency difference. Results of four case studies performed in Matlab/Simulink show that the proposed FLC-based synchronverter can stabilize the grid frequency by reducing the frequency deviation by at least 0.2 Hz (0.4%), as compared with the conventional PI-based synchronverter.

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PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions

Cited by 90 publications

References 28 publications

Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Modified Variable Step-Size Incremental Conductance MPPT Technique for Photovoltaic Systems

Fuzzy logic controller-based synchronverter in grid-connected solar power system with adaptive damping factor

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