ESP Journal of Engineering & Technology Advancements |
© 2023 by ESP JETA |
Volume 3 Issue 1 |
Year of Publication : 2023 |
Authors : Geetha S, Menaga S, Sivakumar G |
:10.56472/25832646/JETA-V3I3P104 |
Geetha S, Menaga S, Sivakumar G, 2023. "Solar Power Forecasting Using Artificial Neural Networks" ESP Journal of Engineering & Technology Advancements 3(3): 119-124.
As concerns about climate change continue to grow, sustainable development and renewable energy are becoming increasingly important worldwide. Predicting the energy output of sustainable sources at a specific location throughout the year can greatly aid in making informed investments in sustainable energy. Energy forecasting can also help mitigate uncertainties surrounding resource availability. Specifically, solar power forecasting has gained significant attention from researchers. In this project, an artificial neural network (ANN) model was developed to generate power prediction. The study also included sensitivity analysis and compared the performance model to multiple linear regression and persistence models.
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Solar Power Prediction, Machine Learning, ANN, Performance Analysis, Accuracy.