New intelligent control strategy by robust neural network algorithm for real time detection of an optimized maximum power tracking control in photovoltaic systems
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DOI: 10.1016/j.energy.2019.115881
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Cited by:
- Abdelmalek, Samir & Dali, Ali & Bakdi, Azzeddine & Bettayeb, Maamar, 2020. "Design and experimental implementation of a new robust observer-based nonlinear controller for DC-DC buck converters," Energy, Elsevier, vol. 213(C).
- Zhou, Xiaoyan & Zhang, Ying & Ma, Xun & Li, Guoliang & Wang, Yunfeng & Hu, Chengzhi & Liang, Junyu & Li, Ming, 2022. "Performance characteristics of photovoltaic cold storage under composite control of maximum power tracking and constant voltage per frequency," Applied Energy, Elsevier, vol. 305(C).
- Liu, Xiangjie & Zhu, Zheng & Kong, Xiaobing & Ma, Lele & Lee, Kwang Y., 2023. "An economic model predictive control-based flexible power point tracking strategy for photovoltaic power generation," Energy, Elsevier, vol. 283(C).
- Aatabe, Mohamed & El Guezar, Fatima & Vargas, Alessandro N. & Bouzahir, Hassane, 2021. "A novel stochastic maximum power point tracking control for off-grid standalone photovoltaic systems with unpredictable load demand," Energy, Elsevier, vol. 235(C).
- Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2021. "A Simple Method for Detecting Partial Shading in PV Systems," Energies, MDPI, vol. 14(16), pages 1-12, August.
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Keywords
Neural networks; New technique; Algorithm of Levenberg-Marquart; Optimization; Speed; Precision; Smooth signal; Noise of measurements; Sampling frequency; Supervision; Identification; Controllers; Practical alternative; MPPT controllers; Power; Yield; Disturbed commands; Classical methods; Incrementing conductance (IC); Pipeline mode; Filtering by slipping average algorithm;All these keywords.
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