Design and analysis of genetic algorithm and BP neural network based PID control for boost converter applied in renewable power generations-Reference-Cited by-同舟云学术

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Design and analysis of genetic algorithm and BP neural network based PID control for boost converter applied in renewable power generations

Published:2021-11 Issue: Volume: Page:
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Generation

Author:

Wang Qingsong¹²^ORCID,Xi Haoyu³^ORCID,Deng Fujin¹^ORCID,Cheng Ming¹^ORCID,Buja Giuseppe⁴^ORCID

Affiliation:

1. School of Electrical Engineering Southeast University Nanjing China

2. Jiangsu Key Laboratory of Smart Grid Technology and Equipment Southeast University Nanjing China

3. School of Software Engineering Southeast University Suzhou China

4. Department of Industrial Engineering University of Padova Padova Italy

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rpg2.12320

Reference24 articles.

1. Cascade control with adaptive voltage controller applied to photovoltaic Boost converters;Bellinaso L.V.;IEEE Trans. Ind. App.,2019

2. Robust predictive current controller based on a disturbance estimator in a three‐phase grid‐connected inverter;Lee K.;IEEE Trans. Power Electron.,2012

3. Variable coefficient fractional‐order PID controller and its application to a SEPIC device;Chen L.;IET Control Theory App.,2020

4. Reinforcement learning and its applications in modern power and energy systems: a review;Cao D.;J. Mod. Power Syst. Clean Energy,2020

5. A multi‐agent deep reinforcement learning based voltage regulation using coordinated PV inverters;Cao D.;IEEE Trans. Power Syst.,2020

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