Hybrid ANN based Incremental Conductance MPPT-Current Control Algorithm for Constant Power Generation of PV fed DC Microgrid

Bhatia, Pratishtha; Mittal, Shivangi; Raizada, Shirish; Verma, Vishal

doi:10.1109/stpec49749.2020.9297751

Cited by 2 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…NNC is essentially a nonlinear control approach and extensively increases system effectivity with greater effectiveness [64][65][66][67][68]. This approach can successfully cope with the nonlinear behavior of the system besides any data about the mathematical model [69][70][71][72][73]. In addition, the dynamic features of the DC-DC converter with the neural network can be realized excellent dynamic characteristics, compared with the conventional methods [74].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

View full text Add to dashboard Cite

In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm 𝑃𝑂 and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control. This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

show abstract

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

View full text Add to dashboard Cite

show abstract

“…However, this technique is difficult to implement due to complexity arising from increased system dynamics. ANN based MPPT approach for PV electric vehicle is studied in (Bhatia et al, 2020) where open circuit voltage and temperature of solar cell were used as input variables while MPP voltage was the output variable. In addition to ANN and GA, fuzzy logic controller is also used for PV systems which is relatively easy to design since knowledge of an accurate MPPT model is not required (Dehghani et al, 2021).…”

mentioning

confidence: 99%

Backstepping based real twisting sliding mode control for photovoltaic system

Malik¹,

Sun²,

Numan³

et al. 2023

Front. Energy Res.

View full text Add to dashboard Cite

Renewable energy sources tied to a utility grid require non-linear control algorithms to provide an efficient and stable output under different operating conditions. The maximum power point tracking (MPPT) approach is necessary for power generation due to non-linear behavior of photovoltaic (PV) power plants. In changing environmental and partial shading conditions, the standard MPPT methods may lead to abnormal results. In this paper, a backstepping based real twisting sliding mode MPPT control is proposed for the PV-battery system where maximum available power is extracted by tracking PV voltage. Moreover, a direct sliding mode control is proposed for battery-integrated buck boost converter for voltage regulation. Reference sliding surface is generated through linear interpolation based on the predicted maximum power point PV voltage. The proposed MPPT strategy is tested against variations of irradiance, temperature, and load. Simulation results highlight superior tracking performance, reduced chattering, and oscillations of this technique over existing models.

show abstract

Hybrid ANN based Incremental Conductance MPPT-Current Control Algorithm for Constant Power Generation of PV fed DC Microgrid

Cited by 2 publications

References 16 publications

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Backstepping based real twisting sliding mode control for photovoltaic system

Contact Info

Product

Resources

About