Optimization Technique Based Fuzzy Logic Controller for MPPT of Solar PV System

Saha, Swarup Kumar; Jaipal,

doi:10.1109/icetietr.2018.8529078

Cited by 16 publications

(6 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a stand-alone PV system, Metaheuristic techniques are used to optimize FLC [22]. The PV efficiency is further improved by the research work on Firefly Optimization Algorithm [23][24][25][26], Gray Wolf Algorithm [27][28][29], Grasshopper Algorithm [30], Ant Colony Optimization algorithm [30], Genetic Optimization Algorithm [32,33] and many other algorithms, optimization techniques are also used in the optimal selection of FLC parameters [34]. Ultra-innovative algorithms for determining the output step size and tracking the MPP, have been used in many popular articles such as in [35], the authors have used the cuckoo search algorithm for MPPT.…”

Section: Introductionmentioning

confidence: 99%

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

et al. 2022

View full text Add to dashboard Cite

The performance of a photovoltaic (PV) array depends on temperature, radiation, shading and load size. Conventional maximum power point tracking (MPPT) methods have acceptable efficiencies under uniform conditions (irradiance = 1000 W/m 2 and temprature = 25 °C), but in dynamic weather conditions, load changes, and also in partial shading conditions due to the presence of several local maximum power points (MPP) in the P-V characteristic, the conventional tracking method does not work well in finding the main MPP. To extract maximum power in all conditions, many algorithms have been proposed, all of which have limitations in terms of convergence speed, output power ripple and efficiency. This research proposes an optimized Fuzzy Logic Controller (FLC) based on the Cuckoo Optimization Algorithm (COA) for MPPT under uniform conditions, dynamic weather conditions, partial shading and under load changes. Finally, the research compared the simulation results with four other popular methods. According to the simulation observations and the result, COA-FLC overcomes the mentioned limitations such as low convergence speed, output power ripple and low tracking efficiency in all conditions. Simulations are performed with MATLAB / Simulink software.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

et al. 2022

View full text Add to dashboard Cite

show abstract

“…One of the great applications of the fuzzy controller in photovoltaic systems is based on maximum power point tracking (MPPT), and in this way maximize the energy harvesting of the system. The goal of this fuzzy controller in such studies is to reach maximum power point (MPP) in a short period of time and quickly adapt to changing environmental conditions [12], [13], [14]. The MPC or modelbased predictive control is a controller that bases its control technique on the process model to predict the value of the output variables in a period.…”

Section: Introductionmentioning

confidence: 99%

Position Control Algorithms of Photovoltaic Panels with Respect to the Incidence of Sunlight

Parra Rosero,

Peñaranda,

Cárdenas

2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

View full text Add to dashboard Cite

This paper shows the design and operation of a oneaxis sun position tracker prototype for use in energy harvesting systems with photovoltaic panels. The prototype design is characterized by using low-cost control elements that allow applying the control algorithms in a simple way using Matlab/Simulink for the development and execution of the PID, FUZZY and PREDICTIVE control algorithms, to evaluate their operation independently in the sun position follower prototype. The control parameters to be considered for the evaluation are the percentage over level, the time and the error in steady state. An external light is used to simulate sunlight, making it possible to show that the predictive controller obtains the best results compared to the other two controllers used.

show abstract

“…There have been numerous tracking algorithms like incremental conductance, perturb-observe method, fractional open circuit voltage and fractional short circuit current which are very cost effective to implement and also simple in structure. The incremental conductance (S. K. Saha et al, 2018) is dependent up on the fact that slope of PV system power curve will be zero at MPP, positive on the left of MPP and negative on the right of MPP.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of PI/RBFN ANN Controllers for Sensor Less BLDC Motor Control Based Fuel Cell/PV Hybrid Electric Vehicle

RAVIPATI¹,

Mani²,

Yarlagadda³

2021

JNMES

View full text Add to dashboard Cite

The present society suffers with the problem of the greenhouse effect due to the emission of huge amount of carbon dioxide. And almost 70% of emission of carbon dioxide will be due to the usage of automotive vehicles. It is required to reduce the utilization of automotive vehicles to protect the life of earth for the coming years. This manuscript presents the design of electric vehicle with the utilization of renewable energy source like solar energy with the combination of fuel cell energy. It involves the design of maximum power point tracking system with intelligent fuzzy controller to track the maximum power for various weather conditions. The proposed electric vehicle drives the brush less DC motor whose speed has been monitored with the sensor less speed control technique. The speed control technique has been realized with two types of controller’s namely proportional intelligent controller and radial basis function neural network. Also the speed control technique has been analysed with the performance comparison of the two controllers in terms of speed, torque generated and also errors of speed and current to improve the performance of speed by 5% with the help of MATLAB/Simulink.

show abstract

Optimization Technique Based Fuzzy Logic Controller for MPPT of Solar PV System

Cited by 16 publications

References 1 publication

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

Optimized Fuzzy Controller Based on Cuckoo Optimization Algorithm for Maximum Power-Point Tracking of Photovoltaic Systems

Position Control Algorithms of Photovoltaic Panels with Respect to the Incidence of Sunlight

Performance Evaluation of PI/RBFN ANN Controllers for Sensor Less BLDC Motor Control Based Fuel Cell/PV Hybrid Electric Vehicle

Contact Info

Product

Resources

About