A Hybrid ANFIS-ABC Based MPPT Controller for PV System With Anti-Islanding Grid Protection: Experimental Realization

Padmanaban, Sanjeevikumar; Priyadarshi, Neeraj; Bhaskar, Mahajan Sagar; Holm‐Nielsen, Jens Bo; Ramachandaramurthy, Vigna K.; Hossain, Eklas

doi:10.1109/access.2019.2931547

Cited by 116 publications

(54 citation statements)

References 32 publications

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“…This ANFIS support provides relief to the HC method from the difficulty of seasonal weather changes. As the ANFIS technique approximates the offline MPP duty ratio, it helps to minimize the amplitude of associated power oscillations by smaller duty ratio perturbation steps [107], [108]. Thus, a trade-off between the rapidity of reaching steady-state power and the amplitude of power oscillations is made by ANFIS, as depicted in Figure 25.…”

Section: Hill Climbing With Adaptive Neuro-fuzzy Inference System mentioning

confidence: 99%

Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition–A Retrospection

et al. 2020

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A significant growth in solar photovoltaic (PV) installation has observed during the last decade in standalone and grid-connected power generation systems. The solar PV system has a non-linear output characteristic because of weather intermittency, which tends to have a substantial effect on overall PV system output. Hence, to optimize the output of a PV system, different maximum power point tracking (MPPT) techniques have been used. But, the confusion lies while selecting an appropriate MPPT, as every method has its own merits and demerits. Therefore, a proper review of these techniques is essential. A "Google Scholar" survey of the last five years (2015-2020) was conducted. It has found that overall seventy-one review articles are published on different MPPT techniques; out of those seventy-one, only four are on uniform solar irradiance, seven on non-uniform and none on hybrid optimization MPPT techniques. Most of them have discussed the limited number of MPPT techniques, and none of them has discussed the online and offline under uniform and hybrid MPPT techniques under non-uniform solar irradiance conditions all together in one. Unfortunately, very few attempts have made in this regard. Therefore, a comprehensive review paper on this topic is need of time, in which almost all the well-known MPPT techniques should be encapsulated in one paper. This article focuses on classifications of online, offline, and hybrid optimization MPPT algorithms, under the uniform and non-uniform irradiance conditions. It summarizes various MPPT methods along with their mathematical expression, operating principle, and block diagram/flow charts. This research will provide a valuable pathway to researchers, energy engineers, and strategists for future research and implementation in the field of maximum power point tracking optimization.

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Section: Hill Climbing With Adaptive Neuro-fuzzy Inference System mentioning

confidence: 99%

Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition–A Retrospection

et al. 2020

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“…In addition to standalone PGS, MPPT techniques can also be applied to grid-integrated PV systems [19][20][21][22], hybrid renewable energy systems [23][24][25][26], PV water pumping system [27,28] and Internet of Things [15]. In [19][20][21][22], fuzzy particle swarm optimization MPPT method [19], modified sine-cosine optimized algorithm [20], hybrid adaptive neuro-fuzzy inference system and artificial bee colony algorithm [21], and adaptive neuro-fuzzy inference system-particle swarm optimization-based hybrid MPPT technique [22] have been successfully applied to gridintegrated PV systems to achieve fast convergence and high accuracy. In [23][24][25][26], a firefly asymmetrical fuzzy logic controller based unified MPPT hybrid controller, hybrid fuzzy particle swarm optimization-based MPPT approach, Jaya-based MPPT method, and Lyapunov controller are utilized in PV-Wind-Fuel Cell hybrid system [23], hybrid PV-wind system [24] and PV-Fuel Cell systems [25,26] to achieve high efficiency and stable operation.…”

Section: Introductionmentioning

confidence: 99%

A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation With Adaptive Perturb and Observe

et al. 2020

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This paper proposes a fast and efficient maximum power tracking approach, which synthesizes simplified model-based state estimation (SMSE) with adaptive alpha perturb-and-observe (α-P&O) method, to further raise the capability and efficacy of maximum power point (MPP) tracking (MPPT). Only any two sampling points, in the first stage, on the operating characterization curve are needed to estimate the irradiance and temperature based on SMSE. In the second phase, the operation point is moved directly to the operating voltage command (OVC) derived from the fitting relationship between the voltages at MPP under various insolation intensities, and then the α-P&O method takes over the next tracking to pinpoint the exact MPP. Performances are demonstrated through simulations and experiments. Experimental results reveal that tracking accuracies exceed 99.2 % in all test scenarios. Comparing with conventional and variable step-size P&O methods, the tracking time is shortened by 84.6 % and 76.0 %, improvement of 1.26 % and 0.03 % in tracking accuracy can also be achieved, and the tracking energy loss is reduced by 68.0 % and 52.7 %, respectively. INDEX TERMS Maximum power point tracking, photovoltaic generation system, perturb and observe, state estimation.

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“…The ANFIS has several advantages such as robust performance, ability to capture the nonlinear structure of a process, adaptation capability, and fast learning capacity. The ANFIS has been successfully implemented for fault detection, function approximation, time series forecasting, control, and nonlinear processes modelling [23]- [27].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Method Based on Optimized Neuro-Fuzzy System and Effective Features for Fault Location in VSC-HVDC Systems

Rohani

Koochaki

2020

IEEE Access

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One of the most important issues with HVDC systems are the occurrence of various faults that can lead to considerable electrical power losses, serious damage to expensive equipment and huge financial losses. Hence, it is highly required to design an accurate and automatic fault location method in HVDC systems for maintaining uninterrupted supply of energy and protecting sensitive equipment such as rectifiers and inverters. Accordingly, this paper proposes a new hybrid system based on adaptive neuro-fuzzy inference system (ANFIS) with optimal parameters and Hilbert-Huang (HH) transform for fault location in voltage sourced converter-HVDC (VSC-HVDC) systems. The proposed fault location method consists of three major sections. In the first section, HH transform is applied to extract new features from current signal. In the second part, ANFIS uses the extracted features to estimate the fault location in transmission lines. Learning algorithm determines the accuracy and efficiency of each machine-learning algorithm. In the third section of the developed system, enhanced version of particle swarm optimization (PSO) algorithm named chaotic dynamic weight PSO (CDWPSO) algorithm is implemented as learning algorithm to train the ANFIS. The developed fault detection and location system was tested on a VSC-HVDC system with 250 km length and the obtained results using MATLAB simulations have shown that combination of new features, and CDWPSO-based ANFIS has high accuracy in fault detection and location in VSC-HVDC systems. High fault location accuracy, robust performance of neuro-fuzzy system, optimal training of ANFIS, extraction of novel effective features from current signal and fault location only with six features are the main contribution of the developed system.

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A Hybrid ANFIS-ABC Based MPPT Controller for PV System With Anti-Islanding Grid Protection: Experimental Realization

Cited by 116 publications

References 32 publications

Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition–A Retrospection

Investigation of MPPT Techniques Under Uniform and Non-Uniform Solar Irradiation Condition–A Retrospection

A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation With Adaptive Perturb and Observe

A Hybrid Method Based on Optimized Neuro-Fuzzy System and Effective Features for Fault Location in VSC-HVDC Systems

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