Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

By Cherif Larbes, S. M. A. cheikh, T. Obeidi, A. Zerguerras. 2009

344 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ddea4c9843cb8b6473663beff83b8eee7b531b18

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Saeed Ahmadi
2. Mohammad Sarvi
3. Sh. Abdi

In Renewable Energy, Sustainability and the Environment

1. Saeed Ahmadi
2. Mohammad Sarvi
3. Sh. Abdi

Citations in the corpus

• A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions (2015, methodology): “To achieve this goal, various MPPT algorithms were proposed such as, perturb and observe (P&O) or hill climbing [3–6], incremental conductance [6,7], voltage-based (VMPPT) and current-based (CMPPT) [8,9] methods, and as well, intelligent computing method [10–13].”