Artificial bee swarm optimization algorithm for parameters identification of solar cell models

By Alireza Askarzadeh, Alireza Rezazadeh. 2013

415 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/b910f8c28d092d04cf1730e43bf22537b28ab4c9

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. Zhihua Cai
2. Wenyin Gong

In Genetics

1. Zhihua Cai
2. Wenyin Gong

In Renewable Energy, Sustainability and the Environment

1. Zhihua Cai
2. Wenyin Gong

Citations in the corpus

• Parameter extraction of solar cell models using repaired adaptive differential evolution (2013, methodology): “Because of several promising features like renewability, l ess pollution, ease of installation, and noise-free, the photovoltaic (PV) system such as solar cell has been obtaine d increasing interest recently [1].”
• A parameter extraction technique exploiting intrinsic properties of solar cells (2016, neutral): “…from the dataset as follows: V OC ¼ 0 : 5727 V, I SC ¼ 0 : 7605 A, V M ¼ 0 : 45 V and I M ¼ 0 : 69 A. Table 3 shows the extracted parameters, calculated by the proposed method and by eight reference techniques: LMSA [25], CPSO [21], SA [23], PS [18], BMO [20], ABSO [22], GA [17], and Newton [12].”