Sequence to sequence deep learning models for solar irradiation forecasting

04/30/2019
by   Bhaskar Pratim Mukhoty, et al.
0

The energy output a photo voltaic(PV) panel is a function of solar irradiation and weather parameters like temperature and wind speed etc. A general measure for solar irradiation called Global Horizontal Irradiance (GHI), customarily reported in Watt/meter^2, is a generic indicator for this intermittent energy resource. An accurate prediction of GHI is necessary for reliable grid integration of the renewable as well as for power market trading. While some machine learning techniques are well introduced along with the traditional time-series forecasting techniques, deep-learning techniques remains less explored for the task at hand. In this paper we give deep learning models suitable for sequence to sequence prediction of GHI. The deep learning models are reported for short-term forecasting {1-24} hour along with the state-of-the art techniques like Gradient Boosted Regression Trees(GBRT) and Feed Forward Neural Networks(FFNN). We have checked that spatio-temporal features like wind direction, wind speed and GHI of neighboring location improves the prediction accuracy of the deep learning models significantly. Among the various sequence-to-sequence encoder-decoder models LSTM performed superior, handling short-comings of the state-of-the-art techniques.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/07/2022

Deep learning for spatio-temporal forecasting – application to solar energy

This thesis tackles the subject of spatio-temporal forecasting with deep...
research
05/21/2021

Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units

We design multi-horizon forecasting models for limit order book (LOB) da...
research
11/08/2021

Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature

The objective of this paper is to conduct a performance comparison of fi...
research
08/12/2020

Comprehensive forecasting based analysis using stacked stateless and stateful Gated Recurrent Unit models

Photovoltaic power is a renewable source of energy which is highly used ...
research
05/22/2023

Sequence-to-Sequence Forecasting-aided State Estimation for Power Systems

Power system state forecasting has gained more attention in real-time op...
research
06/03/2023

A Novel Deep Knowledge-based Learning Method for Wind Speed Forecast

The increasing installation rate of wind power poses great challenges to...

Please sign up or login with your details

Forgot password? Click here to reset