Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Varghese, Needhu; Reji, P.

doi:10.1002/2050-7038.12124

Cited by 14 publications

(9 citation statements)

References 31 publications

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“…where, I 0 is reverse saturation current, q is the electron charge, A is a dimensionless material quantity, T is the temperature in Kelvin, I obypass is the reverse saturation current of bypass diode [34]- [35]. The specifications of PV module considered for simulation studies are shown in Table 1.…”

Section: Modeling Of Solar Pv Panel With Bypass Diodementioning

confidence: 99%

An Algorithm for Enhanced Performance of Photovoltaic Array Under Partial Shading Condition

2020

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The partial shading on photovoltaic (PV) modules causes a reduction in generated power and multiple peak points in their electrical characteristics. If the number of shaded modules of two or more rows are different then electrical characteristics exhibit multiple peaks. Also, as the number of shaded modules in a row increases the generated power decreases. These two observations are the main idea of this paper. The algorithm proposed in this paper redistributes shaded modules to various rows such that each row gets the lowest possible number of shaded modules and thereby increases the generated power. This work discusses a condition to achieve an equal number of shaded modules in all rows for which there is only one peak in the electrical characteristics. For the case where this condition is not satisfied, there can only be two-row groups with a different number of shaded modules. However, each group is having the same number of shaded modules and so only two peaks in the electrical characteristics. The proposed algorithm is applicable to any mxn structure of PV arrays. Extensive simulations are carried out and the performance of the proposed algorithm is compared with existing methods for various shading patterns. The results show that the proposed method gives minimum power loss, better performance ratio, and a lesser number of peak points. INDEX TERMS Maximum power generated, partial shading loss, performance ratio, reconfiguration, total cross tied configuration.

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Section: Modeling Of Solar Pv Panel With Bypass Diodementioning

confidence: 99%

An Algorithm for Enhanced Performance of Photovoltaic Array Under Partial Shading Condition

2020

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“…In hybrid renewable energy, the system is plagued with multiple stages of power conversion 24,25 . The wind energy power generation operation, producing AC, normally consists of a wind generator; the output of generator is fed to a three‐phase rectifier and followed by a battery tank 26 and inverter and then finally given to a load as shown in Figure 5. While in solar energy, the voltage is first raised using a DC‐DC converter 27,28 and then changed into AC by using an inverter, 29 and finally, the power is delivered to a load.…”

Section: Introductionmentioning

confidence: 99%

Design of novel universal converter for integration of solar and wind energy for AC and DC load

Kumar

Tatabhatla

Agarwal

2021

Circuit Theory & Apps

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Power generation through renewable sources using a multistage power conversion process was plagued with efficiency and reliability issues. It led to the evolvement of a novel universal converter for the simultaneous interfacing of solar and wind energy. Solar energy is extracted using a multiphase boost converter, while a 2n converter with a switch reluctance generator has been used for wind energy extraction. In this paper, a novel universal converter is used to integrate both solar and wind energies, which will reduce multiple stages of the power conversion process. This converter generates an output voltage of the sino‐square waveform, which is a combination of a sinusoidal and square waveform. Enhanced efficiency and competency of this sino‐square waveform in domestic and industrial applications have been validated with a systematic comparison with conventional square waveform. These two waveforms have been compared based on various harmonics generation, total harmonic distortion (THD), and switching losses. The proposed topology has been validated with an experimental setup using a PV emulator for solar energy. Wind energy has been implemented using an induction motor with switch reluctance generator.

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“…However, a pitch angle controller requires a fast compatible response for unexpected changes in wind speed. As a universal estimator, the Adaptive Neuro-Fuzzy Inference System (ANFIS), which incorporates both an artificial neural network (ANN) and a fuzzy logic controller, is superior to controllers that adopt a single control technique (Varghese and Reji, 2019;Zamen et al, 2019). ANFIS can automatically generate fuzzy if-then rules and optimize turbine parameters via the learning capability of an ANN, and has been primarily used to predict the power coefficient of a wind turbine and to estimate the wind speed (Fan and Mu, 2020;Marugan et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Smoothing the output power of a wind energy conversion system using a hybrid nonlinear pitch angle controller

Fan

2021

Energy Exploration & Exploitation

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Wind energy has been developed and is widely used as a clean and renewable form of energy. Among the existing variety of wind turbines, variable-speed variable-pitch wind turbines have become popular owing to their variable output power capability. In this study, a hybrid control strategy is proposed to implement pitch angle control. A new nonlinear hybrid control approach based on the Adaptive Neuro-Fuzzy Inference System and fuzzy logic control is proposed to regulate the pitch angle and maintain the captured mechanical energy at the rated value. In the controller, the reference value of the pitch angle is predicted by the Adaptive Neuro-Fuzzy Inference System according to the wind speed and the blade tip speed ratio. A proposed fuzzy logic controller provides feedback based on the captured power to modify the pitch angle in real time. The effectiveness of the proposed hybrid pitch angle control method was verified on a 5 MW offshore wind turbine under two different wind conditions using MATLAB/Simulink. The simulation results showed that fluctuations in rotor speed were dramatically mitigated, and the captured mechanical power was always near the rated value as compared with the performance when using the Adaptive Neuro-Fuzzy Inference System alone. The variation rate of power was 0.18% when the proposed controller was employed, whereas it was 2.93% when only an Adaptive Neuro-Fuzzy Inference System was used.

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Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Cited by 14 publications

References 31 publications

An Algorithm for Enhanced Performance of Photovoltaic Array Under Partial Shading Condition

An Algorithm for Enhanced Performance of Photovoltaic Array Under Partial Shading Condition

Design of novel universal converter for integration of solar and wind energy for AC and DC load

Smoothing the output power of a wind energy conversion system using a hybrid nonlinear pitch angle controller

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