Solar Research Methods

What techniques and technologies are used in solar forecasting research?

This article provides an updated review of the techniques and technologies related to solar forecasting research. More specifically, this article focuses on the very short-range forecasting method that utilizes sky imagery captured by all-sky cameras from the Earth’s surface.

What are the different types of solar forecasting techniques?

The review shows that solar forecasting techniques can be categorised into three main category: (i) NWPs, (ii) image-based methods and (iii) data-driven methods. NWPs are mostly appropriate for 6–48 h ahead forecasting.

What is solar power research?

Studies published in peer-reviewed journals and conferences from 2000 to 2024. Research focusing on solar power forecasting using imagery-based methods, including ground-based sensors, satellite data, and all-sky cameras. Research that provides quantitative performance evaluations using standard error metrics.

Which machine learning techniques are used in solar power forecasting?

These are the most widely used machine learning techniques in solar power forecasting. The most common are MLPs, multi-layer perceptron structures, but due to the large number of topologies, it seems appropriate to propose only publications that review the solar forecasting techniques by the ANN, for example, [118, 119, 120].

What is a minutely solar irradiance forecasting method?

A minutely solar irradiance forecasting method based on real-time sky image-irradiance mapping model. Energy Convers. Manag. 2020, 220, 113075.

Is solar radiation forecasting methodology based on a systematic literature review?

The authors aimed to use a meta-review of previous systematic literature reviews to assess the state of the art of solar radiation forecasting methodology. Meta-review (MR) evaluates and synthesises evidence from existing systematic literature reviews (SLR) [19, 20] and, in this way, facilitates broad comparisons .