Maximum Power Point Tracking with Modified Incremental Conductance Technique in Grid-Connected PV Array

Siddique, Muhammad Abu Bakar; Khan, Mahnoor; Asad, A.B.M.A.; Rehman, Ateeq Ur; Asif, Rameez; Rehman, Saif Ur

doi:10.1109/citisia50690.2020.9371803

Cited by 16 publications

(15 citation statements)

References 28 publications

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“…Eng 2023, 4 PWM controller is added to the INC by authors in [20], which quickly tracks the MPP in a standalone PV system even under the change of irradiation, but the oscillations still appear. A Proportional Integral (PI) controller is adopted for the variable step INC algorithm in [24]; it can track the MPP faster and more precisely.…”

Section: The Proposed Mppt Technique Based On the Hysteresis Controlmentioning

confidence: 99%

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

Ouardi

Gadari

Mokhlis

et al. 2023

Eng

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A new Maximum Power Point Tracking (MPPT) method, consisting in combining the Incremental Conductance (INC) algorithm with the Hysteresis control, was developed and applied to a standalone photovoltaic (PV) system to generate the maximum power of the PV array. The INC allows one to search for the Maximum Power Point (MPP). The hysteresis improves the accuracy of tracking the MPP very fast even after severe changes in weather conditions and has no oscillations around the MPP. The five-level S-Packed U Cells (SPUC5) inverter is used to transform the produced DC voltage to AC voltage; it generates five-level output voltage with a small number of switches and only DC source voltage. The capacitors of the SPUC5 are controlled by the Pulse Width Modulation (PWM) in order to balance their voltages. The proposed PV system was established and trained in the MATLAB/Simulink environment under various irradiation conditions. A comparison between different MPPT methods, INC-PWM and INC-PI, was investigated in order to examine the effectiveness of the developed MPPT technique in particular, and of all the PV system components. The results of the simulation validate the effectiveness of the suggested MPPT algorithm as well as the used SPUC5 inverter.

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Section: The Proposed Mppt Technique Based On the Hysteresis Controlmentioning

confidence: 99%

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

Ouardi

Gadari

Mokhlis

et al. 2023

Eng

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“…Many researchers forecasted the price of electricity using the ANN strategy in traditional ways. In this regard, a multi-layer feed-forward Neural Network (MFFNN), Neuro-Fuzzy, Fuzzy Neural Network, and Adaptive Wavelet Neural Network approaches based on the different analyses were used to extract selection features of price and load signals for each hour [18,19]. The electricity price varies due to dynamic variations in load demand throughout the day; therefore, this strategy minimizes the MAPE in load and price at hourly, daily, and weekly intervals [20].…”

Section: Related Workmentioning

confidence: 99%

A Novel Machine Learning-Based Price Forecasting for Energy Management Systems

et al. 2021

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Price forecasting (PF) is the primary concern in distributed power generation. This paper presents a novel and improved technique to forecast electricity prices. The data of various power producers, Capacity Purchase Price (CPP), Power Purchase Price (PPP), Tariff rates, and load demand from National Electric Power Regulatory Authority (NEPRA) are considered for MAPE reduction in PF. Eight time-series and auto-regression algorithms are developed for data fetching and setting the objective function. The feed-forward ANFIS based on the ML approach and space vector regression (SVR) is introduced to PF by taking the input from time series and auto-regression (AR) algorithms. Best-feature selection is conducted by adopting the Binary Genetic Algorithm (BGA)-Principal Component Analysis (PCA) approach that ultimately minimizes the complexity and computational time of the model. The proposed integration strategy computes the mean absolute percentage error (MAPE), and the overall improvement percentage is 9.24%, which is valuable in price forecasting of the energy management system (EMS). In the end, EMS based on the Firefly algorithm (FA) has been presented, and by implementing FA, the cost of electricity has been reduced by 21%, 19%, and 20% for building 1, 2, and 3, respectively.

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“…The papers in Refs. [ [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] ], discuss the most popular methods.…”

Section: Introductionmentioning

confidence: 99%

MPPT efficiency enhancement of a grid connected solar PV system using Finite Control set model predictive controller

Salau,

Alitasb

2024

Heliyon

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Maximum Power Point Tracking with Modified Incremental Conductance Technique in Grid-Connected PV Array

Cited by 16 publications

References 28 publications

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

A Novel Machine Learning-Based Price Forecasting for Energy Management Systems

MPPT efficiency enhancement of a grid connected solar PV system using Finite Control set model predictive controller

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