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Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant

Nonthawat Khortsriwong,
Promphak Boonraksa,
Terapong Boonraksa,
Thipwan Fangsuwannarak,
Asada Boonsrirat,
Watcharakorn Pinthurat and
Boonruang Marungsri

Energies2023, 16(5), 2119;https://doi.org/10.3390/en16052119

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22 February 2023

Recently, deep learning techniques have become popular and are widely employed in several research areas, such as optimization, pattern recognition, object identification, and forecasting, due to the advanced development of computer programming techn...

327 Results Found

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Outlier Events of Solar Forecasts for Regional Power Grid in Japan Using JMA Mesoscale Model

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Day-Ahead PV Generation Scheduling in Incentive Program for Accurate Renewable Forecasting

Deep RNN-Based Photovoltaic Power Short-Term Forecast Using Power IoT Sensors

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Multi-Site Photovoltaic Forecasting Exploiting Space-Time Convolutional Neural Network

Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities

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Benchmark Comparison of Analytical, Data-Based and Hybrid Models for Multi-Step Short-Term Photovoltaic Power Generation Forecasting

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Short-Term Photovoltaic Power Forecasting Based on a Feature Rise-Dimensional Two-Layer Ensemble Learning Model

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Revolutionizing Solar Power Production with Artificial Intelligence: A Sustainable Predictive Model

Reduction of Power Imbalances Using Battery Energy Storage System in a Bulk Power System with Extremely Large Photovoltaics Interactions

SP-Transformer: A Medium- and Long-Term Photovoltaic Power Forecasting Model Integrating Multi-Source Spatiotemporal Features

Sensorless PV Power Forecasting in Grid-Connected Buildings through Deep Learning

Short-Term Photovoltaic Power Forecasting Based on an Improved Zebra Optimization Algorithm—Stochastic Configuration Network

Evidential Extreme Learning Machine Algorithm-Based Day-Ahead Photovoltaic Power Forecasting

SSA-LSTM: Short-Term Photovoltaic Power Prediction Based on Feature Matching

Adaptive Graph Neural Network-Based Hybrid Approach for Long-Term Photovoltaic Power Forecasting

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