Comparison between proposed fuzzy logic and ANFIS for MPPT control for photovoltaic system

Farah, Lotfi; Haddouche, Adel; Haddouche, Ali

doi:10.11591/ijpeds.v11.i2.pp1065-1073

Cited by 29 publications

(19 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many advantages can be achieved by using Fuzzy logic such as nonlinearities, not needing a mathematical modeling and working with imprecise inputs [15,16,21]. Thus, it has received increased interest in MPPT applications [22][23][24][25].…”

Section: Fuzzy Logic Mppt Algorithmmentioning

confidence: 99%

Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm

Nasser

Yaqoob

Hassoun

2021

IJEECS

View full text Add to dashboard Cite

The nonlinear characteristics and intense credence dependence of photovoltaic (PV) panel on the solar irradiance and ambient temperature demonstrate important challenges for researchers in the PV panel topic. To overcome these problems, the maximum power point tracking (MPPT) controller is needed which can improve the PV panel efficiency. In other words, for maximum efficiency, the MPPT controller can help to extract the optimal and overall available output power from the PV panel at different output load conditions. Fuzzy logic (FL) is one of the strongest techniques in the extracting of MPP in the PV panel since it has several advantages; robust; no requirement to have an accurate mathematical model, and works with imprecise inputs. Therefore, in this paper, fuzzy logic (FL-MPPT) has been designed and simulated to improve dynamic performance PV panel at different solar irradiance and then increased the efficiency. Therefore, "MATLAB/Simulink software" has been used to build the proposed algorithm and the simulation results have been adequate as well. Besides, a robust FL-MPPT algorithm has been presented with high dynamic performance under different weather conditions. Finally, the proposed algorithm has a quicker response and less oscillatory comparison of the conventional algorithms in the subject of extracting the maximum PV power.

show abstract

Section: Fuzzy Logic Mppt Algorithmmentioning

confidence: 99%

Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm

Nasser

Yaqoob

Hassoun

2021

IJEECS

View full text Add to dashboard Cite

show abstract

“…In this paper, the panel is coupled directly to a boost converter, used to realize the operation with a resistive load. The boost converter topology is used to provide high voltage gain to achieve the maximum power by algorithm [34]. The boost converter can be analyzed according to two possible swich states, diagrams of which are presented in Figure 4(b) and (c), separately.…”

Section: Dc/dc Boost Convertermentioning

confidence: 99%

New improved hybrid MPPT based on neural network-model predictive control-kalman filter for photovoltaic system

Kacimi

Grouni

Idir

et al. 2020

IJEECS

View full text Add to dashboard Cite

In this paper, new hybrid Maximum Power Point Tracking (MPPT) strategy for Photovoltaic Systems has been proposed. The proposed technique for MPPT control based on a novel combination of an Artificial Neural Network (ANN) with an improved Model Predictive Control using Kalman Filter (NN-MPC-KF). In this paper the Kalman Filter is used to estimate the converter state vector for minimizes the cost function then predict the future value to track the Maximum Power Point (MPP) with fast changing weather parameters. The proposed control technique can track the MPP in fast changing irradiance conditions and a small overshoot. Finally, the system is simulated in the MATLAB/Simulink environment. The simulation results verify the appropriate performance of the proposed method. As a result, the proposed algorithm can achieve higher maximum power point tracking efficiency, faster dynamic response, and lower oscillations. In addition, the comparative simulation results of the proposed algorithm with the other maximum power point tracking algorithms show the superiority of the proposed algorithm.

show abstract

“…A different hybrid energy system has been studied in many research papers [6][7][8][9][10][11][12][13][14][15][16][17][18]. The authors in [19] are proposing to realize a technical-economic capacity of a hybrid renewable energy system (HRES) to occupy the energy demand of a university site in the Himalayan state of northeastern Sikkim, and also the other aspect of exploring the electrical voltage of other renewable energy resources such as biogas and syngas and hydrokinetic energy, in addition to a solar-wind hybridization mainly carried out in the resource-rich urban planning territory of the east of the Himalayas.…”

Section: Introductionmentioning

confidence: 99%

A hybrid renewable energy production system using a smart controller based on fuzzy logic

Moussa

Derrouazin

Latroch

et al. 2022

Electrical Engineering & Electromechanics

View full text Add to dashboard Cite

Introduction. This article proposes an improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology with multiple inputs and outputs (I/O). It is used to control hybrid electric energy sources built around photovoltaic solar panels, wind turbine and electric energy storage system assisted by the electric grid. The novelty in this work that solar photovoltaic, wind turbine and storage system energy sources are prioritized over the grid network which is solicited only during adverse weather conditions, in order to supply a typical household using up to 4,000 Wh per day. In addition of that, the surplus of renewable energy produced during favorable climatic condition is used to produce hydrogen suitable for household heating and cooking using eletrolyzer system. Purpose. Development of improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology. This system is embedded on Arduino 2560 mega microcontroller, on which the fundamental program of fuzzy logic and the distribution of events with all possible scenarios have been implemented according to a flowchart allowing the management of the hybrid system. Methods as well as a parametric search and a simulation to characterize the system, are carried out in order to put on the proposed techniques to ensure continuous accommodation at home. Results. The proposed system results confirm their effectiveness by visualizing the output control signals from the electronic switches. Practical value of which transmits power through a single-phase DC/AC converter to power the AC load for the accommodation.

show abstract

Comparison between proposed fuzzy logic and ANFIS for MPPT control for photovoltaic system

Cited by 29 publications

References 11 publications

Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm

Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm

New improved hybrid MPPT based on neural network-model predictive control-kalman filter for photovoltaic system

A hybrid renewable energy production system using a smart controller based on fuzzy logic

Contact Info

Product

Resources

About