Short-term PV power forecasting using variational mode decomposition integrated with Ant colony optimization and neural network

Deep Learning Based Forecasting of Photovoltaic Power Generation by Incorporating Domain Knowledge

(2021) Xing Luo et al.   ENERGY

Point and Interval Solar Power Forecasting Using Hybrid Empirical Wavelet Transform and Robust Wavelet Kernel Ridge Regression

(2020) P. K. Dash et al.   Natural Resources Research

Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach

(2020) Abdelkader Dairi et al.   Applied Sciences-Basel

A Hybrid Forecasting Method for Solar Output Power Based on Variational Mode Decomposition, Deep Belief Networks and Auto-Regressive Moving Average

(2018) Tuo Xie et al.   Applied Sciences-Basel

Optimizing Cloud-Service Performance: Efficient Resource Provisioning via Optimal Workload Allocation

(2017) Zhuoyao Wang et al.   IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS

Comparing support vector regression for PV power forecasting to a physical modeling approach using measurement, numerical weather prediction, and cloud motion data

(2016) Björn Wolff et al.   SOLAR ENERGY

Variational Mode Decomposition

(2014) Konstantin Dragomiretskiy et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation

(2014) Yuan-Kang Wu et al.   INTERNATIONAL JOURNAL OF PHOTOENERGY

Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks

(2014) Aminmohammad Saberian et al.   INTERNATIONAL JOURNAL OF PHOTOENERGY

Identification of linear time-varying mdof dynamic systems from forced excitation using Hilbert transform and EMD method

(2008) Z.Y. Shi et al.   JOURNAL OF SOUND AND VIBRATION