Daily Prediction of PV Power Output Using Particulate Matter Parameter with Artificial Neural Networks-Reference-Cited by-同舟云学术

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Daily Prediction of PV Power Output Using Particulate Matter Parameter with Artificial Neural Networks

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:2023 11th International Conference on Smart Grid (icSmartGrid)
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Author:

Irmak Erdal¹,Yesilbudak Mehmet²,Tasdemir Oguz³

Affiliation:

1. Gazi University,Faculty of Technology,Department of Electrical and Electronics Engineering,Ankara,Turkey

2. Nevsehir Haci Bektas Veli University,Faculty of Engineering and Architecture,Department of Electrical and Electronics Engineering,Nevsehir,Turkey

3. Kırşehir Ahi Evran University, Vocational College of Kaman,Department of Electricity and Electronics,Kırsehir,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10169137/10169142/10171103.pdf?arnumber=10171103

Reference24 articles.

1. Forecasting and uncertainty analysis of day-ahead photovoltaic power using a novel forecasting method

2. Very Short-Term Estimation of Global Horizontal Irradiance Using Data Mining Methods

3. Recurrent Neural Network-Based Hourly Prediction of Photovoltaic Power Output Using Meteorological Information

4. Parameter Extraction of Photovoltaic Cells and Modules Using Grey Wolf Optimizer with Dimension Learning-Based Hunting Search Strategy

5. Daily Photovoltaic Power Prediction Enhanced by Hybrid GWO-MLP, ALO-MLP and WOA-MLP Models Using Meteorological Information

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced PV Power Prediction Considering PM10 Parameter by Hybrid JAYA-ANN Model;Electric Power Components and Systems;2024-03-04

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