Prediction of daily photovoltaic plant energy output using machine learning

IF 2.3 4区工程技术 Q3 ENERGY & FUELS

Energy Sources Part A-recovery Utilization and Environmental Effects Pub Date : 2024-04-19 DOI:10.1080/15567036.2024.2341975

Bharat Girdhani, Meena Agrawal

引用次数: 0

Abstract

The energy crisis and global warming are the two significant factors that have led to the accelerated development of PV power plants. Accurate prediction of PV plant power output is crucial to enha...

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利用机器学习预测光伏电站的日发电量

能源危机和全球变暖是导致光伏电站加速发展的两个重要因素。准确预测光伏电站的发电量对确保能源安全至关重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Energy Sources Part A-recovery Utilization and Environmental Effects 工程技术-工程：化工

CiteScore

4.40

自引率

6.90%

发文量

488

审稿时长

1.7 months

期刊介绍： Energy Sources Part A: Recovery, Utilization, and Environmental Effects aims to investigate resolutions for the continuing increase in worldwide demand for energy, the diminishing accessibility of natural energy resources, and the growing impact of energy use on the environment. You are invited to submit manuscripts that explore the technological, scientific and environmental aspects of: Coal energy sources Geothermal energy sources Natural gas Nuclear energy sources Oil shale energy sources Organic waste from energy use Petroleum Solar energy sources Tar utilization Sand utilization Wind energy.