A new MPPT scheme based on a novel fuzzy approach

Nabipour, Mahdi; Razaz, Morteza; Seifossadat, Seyed Ghodratollah; Mortazavi, S. S.

doi:10.1016/j.rser.2017.02.054

Cited by 95 publications

(39 citation statements)

References 81 publications

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“…Figure 14a shows the results obtained for the power delivered to the battery with a simulation time of 0.03 s. It can be seen that the two controllers extract the maximum power of 65 W with a good stabilization time of 0.005 s, which is consistent with the results obtained in [15,16]. In Figure 14b, it is observed that the duty cycle of the P&O control presents small oscillations between 0.6926 and 0.7, in contrast to the fuzzy control that is stabilized at a value of D = 0.694.…”

Section: Case 1: Standard Test Conditionssupporting

confidence: 83%

“…Also, algorithms based on artificial intelligence techniques such as fuzzy logic [13][14][15][16][17][18][19] and neural networks [20][21][22] have been used, as well as the implementation of optimization algorithms such as glowworm swarm [23], ant colony [24,25] and bee colony [26][27][28]. These algorithms are part of soft computing techniques and have the advantage of being easily implemented using embedded systems.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Logic Based MPPT Controller for a PV System

Robles-Algarín¹,

Giraldo²,

Álvarez³

2017

Energies

129

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Abstract:The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement maximum power point tracking controllers (MPPT) to obtain the maximum power of a PV system regardless of variations in climatic conditions. The traditional solution for MPPT controllers is the perturbation and observation (P&O) algorithm, which presents oscillation problems around the operating point; the reason why improving the results obtained with this algorithm has become an important goal to reach for researchers. This paper presents the design and modeling of a fuzzy controller for tracking the maximum power point of a PV System. Matlab/Simulink (MathWorks, Natick, MA, USA) was used for the modeling of the components of a 65 W PV system: PV module, buck converter and fuzzy controller; highlighting as main novelty the use of a mathematical model for the PV module, which, unlike diode based models, only needs to calculate the curve fitting parameter. A P&O controller to compare the results obtained with the fuzzy control was designed. The simulation results demonstrated the superiority of the fuzzy controller in terms of settling time, power loss and oscillations at the operating point.

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Section: Case 1: Standard Test Conditionssupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based MPPT Controller for a PV System

Robles-Algarín¹,

Giraldo²,

Álvarez³

2017

Energies

129

View full text Add to dashboard Cite

show abstract

“…Considering the abovementioned, various looks into have been completed utilizing conventional calculations for the displaying and usage of MPPT controllers [5], of which coming up next are featured: bother plus watch (P&O) [6], [7], adjusted P&O [8], [9], fragmentary short out current [10], partial open circuit voltage [11], sliding mode control [12], [13] and gradual conductance [14]. The P&O calculation has been utilized generally, yet it has been demonstrated that this strategy has issues for following the MPP when there are unexpected change within sun powered irradiance [15].…”

Section: Literature Surveymentioning

confidence: 99%

A PV Module Integrated Converter for Enhanced Perfomance in Standalone and DC Microgrid Applications

2019

IJITEE

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The aim of these design toward plot and execute greatest power point following (MPPT) that makes utilize of a fluffy rationale control algorithm. Fluffy rationale, via using dealing with nonlinearities, gives a regular controller used for this form of utilization. The technique likewise income by the heuristic way to deal with the problem that beats the intricacy in demonstrating nonlinear frameworks. Therefore as to perform this objective, MPPT model comprising of a PV module, a DC-DC converter, and a fluffy rationale controller become created. Examination of buck, converter as well as buck-support converter attributes changed into done within an effort on the way to distinguish the most appropriate topology. An incorporated copy of the PV module along with the distinguished converter became reproduced also the effects worn to determine the grasp studying predicted near devise also music the fluffy rationale regulator. The regulator changed into veiled the same as an ongoing control application and the MPPT finished via a dc-dc converter constrained by means of a microcontroller. These results in progressed productiveness in favor of the hobby of a photovoltaic strength framework considering battery may be accurately charged and applied in the course of times of low sunlight based radiation. The better productiveness is relied upon to set off essential value funding funds over the long haul. The well known price is saved low through choosing segments that take into account executing the capacities requiring little to no effort. Reenactment outcomes demonstrate the high estimation of the element coordinated converter for DC unbiased and microgrid packages. A 400 W model changed into completed by 0.14 Euro/W. Testing established efficiencies over 95% thinking about every misfortunes from have an effect on trade, fuzzy logic MPPT, and estimation and manage hardware. Rundown phrases-Boost converter, fuzzy logic most extreme power point following (DMPPT), microgrid, and module coordinated converter (MIC), photovoltaics (PV), control analyzer, control quality, sun based irradiance, exchanging recurrence tweak (SFM).

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“…So, in this case, the voltage is less influenced by the step variation than the duty cycle and they are more rapid and accurate than the classical methods. This can be solved by using the artificial intelligence such as fuzzy logic [8] and artificial neural network [9,10]. These methods are efficient, accurate and capable of tracking the maximal power.…”

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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A new MPPT scheme based on a novel fuzzy approach

Cited by 95 publications

References 81 publications

Fuzzy Logic Based MPPT Controller for a PV System

Fuzzy Logic Based MPPT Controller for a PV System

A PV Module Integrated Converter for Enhanced Perfomance in Standalone and DC Microgrid Applications

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

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