Work

Effect of meteorological factors on photovoltaic power forecast based on the neural network

Year: 2017

Type: article

Abstract: In this paper, the effects of meteorological factors (including air temperature, wind speed, and relative humidity) on photovoltaic (PV) power forecast using neural network models have been studied.

Source: RSC Advances

DOI: 10.1039/c7ra10591f

Authors: Wenbo Xiao, Jin Dai, Huaming Wu, Gina Nazario, Feng Cheng

Institutions: Nanchang Hangkong University, University of South Florida

Language: English

Topic: Solar Radiation and Photovoltaics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Climate action, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $1,042

Funder: Education Department of Jiangxi Province

Award: G3111017801

OpenAlex ID: W2772170482

FWCI: 0.816

Cites: 19

Cited by: 11

Related to: 10