Extremal Nelder–Mead colony predation algorithm for parameter estimation of solar photovoltaic models-Reference-Cited by-同舟云学术

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Extremal Nelder–Mead colony predation algorithm for parameter estimation of solar photovoltaic models

Published:2022-08-18 Issue:10 Volume:10 Page:4176-4219
ISSN:2050-0505
Container-title:Energy Science & Engineering
language:en
Short-container-title:Energy Science & Engineering

Author:

Xu Boyang¹,Heidari Ali Asghar²^ORCID,Zhang Siyang³,Chen Huiling¹^ORCID,Shao Qike¹

Affiliation:

1. Department of Computer Science and Artificial Intelligence Wenzhou University Wenzhou China

2. School of Surveying and Geospatial Engineering, College of Engineering University of Tehran Tehran Iran

3. School of Information Engineering Wenzhou Business College Wenzhou China

Publisher

Wiley

Subject

General Energy,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.1273

Reference145 articles.

1. A Novel Chaotic Flower Pollination Algorithm for Global Maximum Power Point Tracking for Photovoltaic System Under Partial Shading Conditions

2. Modified JAYA algorithm for optimal power flow incorporating renewable energy sources considering the cost, emission, power loss and voltage profile improvement

3. Parameter Identification for PV Modules Based on an Environment-Dependent Double-Diode Model

4. Parameters identification of PV solar cells and modules using flexible particle swarm optimization algorithm

5. Flower Pollination Algorithm based solar PV parameter estimation

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1. Parameters identification of photovoltaic models using Lambert W-function and Newton-Raphson method collaborated with AI-based optimization techniques: A comparative study;Expert Systems with Applications;2024-12

2. Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model;Computers in Biology and Medicine;2024-06

3. Dimensional decision covariance colony predation algorithm: global optimization and high−dimensional feature selection;Artificial Intelligence Review;2023-03-13

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