Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition

Verma, Pallavi; Garg, Rachana; Mahajan, Priya

doi:10.1016/j.isatra.2020.01.009

Cited by 89 publications

(36 citation statements)

References 41 publications

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“…There are also Mamdani and Takagi-Sukeno (T-S) design approaches for FLC, where a Mamdanibased FLC is relatively popular [28]. Typically, FLC consists of three steps, fuzzification, fuzzy rules and defuzzification [29]. In the first step, the input variables are converted into linguistic variables by using various defined membership functions [30].…”

Section: A Flcmentioning

confidence: 99%

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

Yap

Sarimuthu

Lim

2020

Journal of Modern Power Systems and Clean Energy

197

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In the last decade, artificial intelligence (AI) techniques have been extensively used for maximum power point tracking (MPPT) in the solar power system. This is because conventional MPPT techniques are incapable of tracking the global maximum power point (GMPP) under partial shading condition (PSC). The output curve of the power versus voltage for a solar panel has only one GMPP and multiple local maximum power points (MPPs). The integration of AI in MPPT is crucial to guarantee the tracking of GMPP while increasing the overall efficiency and performance of MPPT. The selection of AI-based MPPT techniques is complicated because each technique has its own merits and demerits. In general, all of the AI-based MPPT techniques exhibit fast convergence speed, less steady-state oscillation and high efficiency, compared with the conventional MPPT techniques. However, the AI-based MPPT techniques are computationally intensive and costly to realize. Overall, the hybrid MPPT is favorable in terms of the balance between performance and complexity, and it combines the advantages of conventional and AI-based MPPT techniques. In this paper, a detailed comparison of classification and performance between 6 major AI-based MPPT techniques have been made based on the review and MATLAB/Simulink simulation results. The merits, open issues and technical implementations of AI-based MPPT techniques are evaluated. We intend to provide new insights into the choice of optimal AI-based MPPT techniques. Index Terms-Maximum power point tracking (MPPT), artificial intelligence (AI), fuzzy logic control (FLC), artificial neural network (ANN), genetic algorithm (GA), swarm intelligence (SI), machine learning (ML).

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Section: A Flcmentioning

confidence: 99%

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

Yap

Sarimuthu

Lim

2020

Journal of Modern Power Systems and Clean Energy

197

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“…By considering the states of switchers SW 1 , SW 2 , and SW 3 , four modes, as shown in Figure 4, can be derived [35]. If SW 1 Figure 4d. For each switching mode, one state space formulation can be written.…”

Section: General Viewmentioning

confidence: 99%

“…Today, photovoltaic (PV) panels are extensively used for energy production, due to their renewability, availability, and clarity [1,2]. However, the main problem in the use of PV panels, is their natural dependance to the weather conditions.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature

et al. 2020

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For this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated.

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“…In contrast to binary logic, fuzzy variables can ensure a value between 0 and 1. This command has the advantage of being a robust and relatively simple to build [20]. The general structure of FLC is shown in Figure 10 and consists of three steps: fuzzification, inference and defuzzification.…”

Section: Mppt Control Via Fuzzy Logicmentioning

confidence: 99%

Reliability of the MPPT Control on the Energy Parameters of a Photovoltaic Generator

Jeannot¹,

Jacques²,

Jeannot³

2020

WJET

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This article describes a technique that allows a photovoltaic (PV) production unit to obtain the maximum power at all times. Here, we use the MPPT control via fuzzy logic on a DC/DC boost-type converter. In order to achieve our goals, we first proceeded to model a PV panel. The resulting model offers the possibility to better account for the influence of different physical quantities such as temperature, irradiation, series resistance, shunt resistance and diode saturation current. Thus, the maximum power to be provided by the PV system is acquired by fuzzification and defuzzification of the input and output variables of the converter. Subsequently, a virtual model of an 800 Watt PV prototype is implemented in the Matlab environment. The simulation results obtained and presented, show the feasibility and efficiency of the proposed technology. Indeed, for a disturbance caused by a variation in brightness, our system guarantees the maximum stable power after 1.4 s. While for a load variation, the maximum power is continuous.

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Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition

Cited by 89 publications

References 41 publications

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

Artificial Intelligence Based MPPT Techniques for Solar Power System: A review

Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature

Reliability of the MPPT Control on the Energy Parameters of a Photovoltaic Generator

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