Optimal parameter design of fractional order control based INC-MPPT for PV system

Al‐Dhaifallah, Mujahed; Nassef, Ahmed M.; Rezk, Hegazy; Nisar, Kottakkaran Sooppy

doi:10.1016/j.solener.2017.11.040

Cited by 137 publications

(53 citation statements)

References 45 publications

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“…The dithering effect increases the signal-noise ratio in the linear state space region of the state flow MPPT technique which can be overcome using the Kalman filter MPPT technique [35]. To track the rapid changes of irradiances and to obtain maximum PV voltage that is nearly equal to the open-circuit voltage (V oc ) of PV, an adaptive IC MPPT technique is applied [36]. The major advantage of this technique is its high intrinsic robustness and negligible uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

2020

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Solar photovoltaic (PV) systems are attracting a huge focus in the current energy scenario. Various maximum power point tracking (MPPT) methods are used in solar PV systems in order to achieve maximum power. In this article, a clear analysis of conventional MPPT techniques such as variable step size perturb and observe (VSS-P&O), modified incremental conductance (MIC), fractional open circuit voltage (FOCV) has been carried out. In addition, the soft computing MPPT techniques such as fixed step size radial basis functional algorithm (FSS-RBFA), variable step size radial basis functional algorithm (VSS-RBFA), adaptive fuzzy logic controller (AFLC), particle swarm optimization (PSO), and cuckoo search (CS) MPPT techniques are presented along with their comparative analysis. The comparative analysis is done under static and dynamic irradiation conditions by considering algorithm complexity, tracking speed, oscillations at MPP, and sensing parameters. The single-diode model PV panel and double-diode model PV panel are also compared in terms of fill factor (FF) and maximum power extraction. Clear insight is presented supporting the suitability of MPPT techniques for different types of converter configurations.

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Section: Introductionmentioning

confidence: 99%

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

2020

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“…The selection of the optimal controller parameters is a very important issue for every command and control problems in order to reduce learning errors and improve the quality of the controller [30,31]. Engineers face daily with increasingly complex problems which arise in very different sectors, such as image processing, design of control and diagnostic systems [32,33]. The problem to be solved can often be considered as an optimization problem in which one or more objective functions, are defined that one seeks to minimize or maximize by contributing to all the parameters concerned.…”

Section: Introductionmentioning

confidence: 99%

Optimization of ANFIS controllers using improved ant colony to control an UAV trajectory tracking task

2020

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Development of unmanned aerial vehicles (UAVs) has become the most important research areas in the field of autonomous aeronautical control. This paper proposes a robust and intelligent controller based on adaptive-network-based fuzzy inference system (ANFIS) and improved ant colony optimization (IACO) to govern the behavior of a three degree of freedom quadrotor UAV. The quadrotor was chosen due to its simple mechanical structure; nevertheless, these types of aircraft are highly nonlinear. Intelligent control such as fuzzy logic is a suitable choice for controlling nonlinear systems. The ANFIS controller is used to reproduce the desired trajectory of the quadrotor in 2D Vertical plane and the IACO algorithm aims is to facilitate convergence to the ANFIS's optimal parameters in order to reduce learning errors and improve the quality of the controller. To evaluate the performance of the proposed IACO tuned ANFIS controller, a comparison between the proposed ANFIS-IACO controller and other controller's performance such us ANFIS only and proportional-integral-derivative controllers is illustrated using the same system. As expected, the hybrid ANFIS-IACO controller gives very satisfactory results than the others methods already developed in the same study.

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“…Each controller designed is characterized by its specific yield, efficiency and implementation cost and complexity. Among these methods, there are the classical ones such as perturb and observe (P&O) [2], incremental conductance (INC) [3] and hill climbing [4], these methods are simple and easiest to implement, but their great drawback is their fluctuations around the maximum power point which influences the accuracy and rapidity of the system [5].…”

Section: Introductionmentioning

confidence: 99%

PSO-SMC Controller Based GMPPT Technique for Photovoltaic Panel Under Partial Shading Effect

Ahmed¹,

Cherkaoui²,

Mokhlis³

2020

IJIES

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The effect of partial shading has a strong influence on the production of photovoltaic solar systems. In fact, when this phenomenon occurs, several power peaks appear on the power-voltage curve (P, V). These peaks are divided between the local maxima and a global maximum. This latter presents the superior maximum compared to the local maxima. Therefore, in this case, the conventional MPPT methods such as Incremental Conductance (INC) and Perturb and Observe (P&O) do not have the ability to detect and track the highest peak. Thus, this causes the important loss of power. To overcome this issue, this study focusses on the design of a new method able to distinguish the global maximum power point (GMPP). This method is composed of two loops of control, the particle swarm optimization (PSO) and the sliding mode controller (SMC). The first loop, which consists of PSO, sweeps the power-voltage curve by looking for the GMPP, after that generates the reference of corresponding optimal voltage. While the second loop is designed to track the voltage reference by acting on the duty cycle of the SEPIC converter. This method is characterized by its robustness against the parameters' changes and the modeling error thanks to the SMC controller designed. In addition, the PSO used improves efficiency of the PV modules subjected to the non-uniform meteorological conditions. The simulation results show the rapidity and accuracy of the proposed method for localizing and tracking the global power maximum. In fact, according to the results, the proposed controller has a convergence time about 63ms depending on the shading pattern. Moreover, it is able to detect the meteorological conditions change. To prove the advantages of the proposed technique, this one is compared with the hybrid controllers those composed of P&O and INC combined with BSC and SMC controllers.

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Optimal parameter design of fractional order control based INC-MPPT for PV system

Cited by 137 publications

References 45 publications

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis

Optimization of ANFIS controllers using improved ant colony to control an UAV trajectory tracking task

PSO-SMC Controller Based GMPPT Technique for Photovoltaic Panel Under Partial Shading Effect

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