A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller

Mohammadinodoushan, Mohammad; Abbassi, Rabeh; Jerbi, Houssem; Ahmed, Faraedoon Waly; ahmed, Halkawt Abdalqadir kh; Rezvani, Alireza

doi:10.1016/j.seta.2021.101056

Cited by 49 publications

(32 citation statements)

References 25 publications

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“…Typical classical online techniques include hill climbing (HC), incremental conductance (InC), and perturb and observe (P&O) algorithm. [12] They are also called gradient-based techniques because the decision to retain the power tracking direction is controlled by the gradient values of consecutive power samples. Voltage, current, and the duty cycle are updated by a fixed constant value.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The influence weights are adjusted according to sensitivity analysis. Unlike PSO, the swarming behavior of TSA is modeled by Equation (12),…”

Section: Swarm Behavior Of Tsamentioning

confidence: 99%

“…2 + c 1 (12) where ⃖⃖⃖ ⃗ P p (x) is the current position of the searching agent and the swarm updates the position randomly within a cone-shaped or cylindrical random search space shape.…”

Section: Swarm Behavior Of Tsamentioning

confidence: 99%

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An Intelligent Tunicate Swarm Algorithm Based MPPT Control Strategy for Multiple Configurations of PV Systems Under Partial Shading Conditions

Mansoor

Mirza

Feng³

et al. 2021

Advcd Theory and Sims

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Solar energy is the most techno-economically viable renewable source of energy and can be effectively converted into electrical power by Photovoltaic (PV) systems. As partial shading (PS) may reduce the harvested energy of PV systems, this paper proposes a novel tunicate swarm algorithm (TSA) based MPPT (maximum power point tracking) strategy to tackle the PS issue. More specifically, the simple and effective modeling of TSA with a search and skipping (SAS) scheme is utilized to minimize the tracking time and search area. The SAS scheme can discard the voltage range lacking global maximum power point (GMPP) and significantly reduce computation time. Consequently, power tracking, tracking time, and robustness can be greatly enhanced. The performance of the proposed TSA strategy is comprehensively analyzed against state-of-the-art techniques, including incremental conductance (InC), improved particle swarm optimization (IPSO), grey wolf optimization (GWO), and cuckoo search algorithm (CSA), through detailed case studies, which include standard array configurations, PS conditions, varying irradiance patterns, fast-changing temperature, and the field atmospheric data. TSA is further validated on a low-cost hardware setup, confirming its superior performance. The results provide insightful validation of the practicality of the proposed TSA strategy in the real-world applications.

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Section: Literature Reviewmentioning

confidence: 99%

“…The influence weights are adjusted according to sensitivity analysis. Unlike PSO, the swarming behavior of TSA is modeled by Equation (12),…”

Section: Swarm Behavior Of Tsamentioning

confidence: 99%

See 1 more Smart Citation

An Intelligent Tunicate Swarm Algorithm Based MPPT Control Strategy for Multiple Configurations of PV Systems Under Partial Shading Conditions

Mansoor

Mirza

Feng³

et al. 2021

Advcd Theory and Sims

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show abstract

“…The algorithm can be summarized as follows. Through the controller's structural improvement, such as PID control [18], fuzzy logic control (FLC) [19,20], sliding mode control (SMC) [21], etc., a feedback-based closed-loop control process can be achieved. However, the output of the parameters may be poor.…”

Section: Introductionmentioning

confidence: 99%

Research and Application of MPPT Control Strategy Based on Improved Slime Mold Algorithm in Shaded Conditions

Zhang

Dong

2022

Electronics

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A PV maximum power tracking strategy for shaded conditions, based on an improved slime mold algorithm, is proposed in this research. To verify the superiority of the proposed algorithm, four bionomics algorithms—particle swarm optimization (PSO), tuna swarm optimization (TSO), squirrel search algorithm (SSA), and black widow spider algorithm (BWO)—were compared. The output parameter of the five control algorithms was summarized and analyzed. The adaptability of the algorithms was proven by setting different shading conditions. The simulation results demonstrated that the proposed algorithm possessed short response time, good tracking effect and fewer fluctuations. Eventually, the different algorithms were verified in the HIL+RCP physical platform. The experimental outcomes showed that the improved slime mold algorithm possessed the best tracking effect, with fewer power fluctuations.

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“…Many methods have been developed to determine the maximum power point (MPP) under all conditions [2][3][4][5][6][7][8]. There are numerous approaches, some of which are based on the well-known perturb and observe (P&O) concept [2,3], others on the sliding mode control method [4,5], artificial neural networks or fuzzy based algorithms [6,7], and synergetic control [1,7,8].…”

Section: Introductionmentioning

confidence: 99%

MPPT for Photovoltaic System Using Adaptive Fuzzy Backstepping Sliding Mode Control

Hadjira¹,

Behih²,

Bouchama³

et al. 2021

EJEE

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This paper presents an intelligent monitoring control strategy for a maximum power point tracking (MPPT) in photovoltaic (PV) system applications. The design of the proposed nonlinear adaptive control law (AFBSMC) is formulated based on adaptive fuzzy systems, backstepping approach and sliding mode technique to maximize the power output of a PV system under various sets of conditions and parameters variation. Unlike many conventional controllers, the main contribution of the present paper provides a soften control law which useful to handle parameters variations due to the different operating conditions occurring on the PV system and makes the controller easy to implement. This aim is achieved using fuzzy systems in an adaptive scheme to approximate the switching control function of the global control law while backstepping sliding mode control compensates uncertainties and external disturbances. The analytical stability proof of the closed-loop system is corroborated via Lyapunov synthesis while numerical simulations of different operating conditions of a PV system is conducted to validate the effectiveness of the proposed approach.

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A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller

Cited by 49 publications

References 25 publications

An Intelligent Tunicate Swarm Algorithm Based MPPT Control Strategy for Multiple Configurations of PV Systems Under Partial Shading Conditions

An Intelligent Tunicate Swarm Algorithm Based MPPT Control Strategy for Multiple Configurations of PV Systems Under Partial Shading Conditions

Research and Application of MPPT Control Strategy Based on Improved Slime Mold Algorithm in Shaded Conditions

MPPT for Photovoltaic System Using Adaptive Fuzzy Backstepping Sliding Mode Control

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