A Meta-Analysis of Solar Forecasting Based on Skill Score

08/22/2022
by   Thi Ngoc Nguyen, et al.
3

We conduct the first comprehensive meta-analysis of deterministic solar forecasting based on skill score, screening 1,447 papers from Google Scholar and reviewing the full texts of 320 papers for data extraction. A database of 4,758 points was built and analyzed with multivariate adaptive regression spline modelling, partial dependence plots, and linear regression. Notably, the analysis accounts for the most important non-linear relationships and interaction terms in the data. We quantify the impacts on forecast accuracy of important variables such as forecast horizon, resolution, climate conditions, regions' annual solar irradiance level, power system size and capacity, forecast models, train and test sets, and the use of different techniques and inputs. By controlling for the key differences between forecasts, including location variables, the findings from the analysis can be applied globally. An overview of scientific progress in the field is also provided.

READ FULL TEXT

page 16

page 21

page 27

page 29

research
04/15/2019

Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation

The increased usage of solar energy places additional importance on fore...
research
06/22/2022

Multi-Resolution, Multi-Horizon Distributed Solar PV Power Forecasting with Forecast Combinations

Distributed, small-scale solar photovoltaic (PV) systems are being insta...
research
10/13/2018

Very Short Term Time-Series Forecasting of Solar Irradiance Without Exogenous Inputs

This paper compares different forecast methods and models to predict ave...
research
11/03/2021

What drives the accuracy of PV output forecasts?

Due to the stochastic nature of photovoltaic (PV) power generation, ther...
research
02/01/2021

Benchmarking of Deep Learning Irradiance Forecasting Models from Sky Images – an in-depth Analysis

A number of industrial applications, such as smart grids, power plant op...
research
10/27/2020

Improving seasonal forecast using probabilistic deep learning

The path toward realizing the potential of seasonal forecasting and its ...
research
03/18/2022

Benchmarks for Solar Radiation Time Series Forecasting

With an ever-increasing share of intermittent renewable energy in the wo...

Please sign up or login with your details

Forgot password? Click here to reset