An Improved Approach to Enhance Training Performance of ANN and the Prediction of PV Power for Any Time-Span without the Presence of Real-Time Weather Data

An Improved Approach to Enhance Training Performance of ANN and the Prediction of PV Power for Any Time-Span without the Presence of Real-Time Weather Data

In this work, an improved approach to enhance the training performance of an Artificial Neural Network (ANN) for prediction of the output of renewable energy systems is proposed. Using the proposed approach, a significant reduction of the Mean Squared Error (MSE) in training performance is achieved,...

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Bibliographic Details
Main Authors: Abdul Rauf Bhatti, Ahmed Bilal Awan, Walied Alharbi, Zainal Salam, Abdullah S. Bin Humayd, Praveen R. P., Kankar Bhattacharya
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
solar energy
power system operation
photovoltaics
PV power prediction
Artificial Neural Network (ANN)
power forecasting
Environmental effects of industries and plants
TD194-195
Renewable energy sources
TJ807-830
Environmental sciences
GE1-350
Online Access:https://doaj.org/article/08e8e42e923d471383cf2f4c513c16b9
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https://doaj.org/article/08e8e42e923d471383cf2f4c513c16b9

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