A Low-cost System for High-frequency Solar Imagery and Power Data Acquisition

Abstract

With advances in solar energy research and increasingly accurate forecast techniques, intermittency no longer stands as a barrier to the adoption of solar energy. Coupling reliable data and knowledge on the inherent variability of the solar resource with advanced learning and forecast models, renewable energy can take an even bigger role in today’s energy paradigm. The objective of this work is to develop and test a low-cost data acquisition system able to provide relevant data for solar energy forecast models. The results yielded from the performed tests indicate high correlation between image derived attributes and power measurements 20 s ahead.

Intelligent collection method of measurement and detection data based on power Internet of Things

“…The experimental test shows that the scheme is superior to the traditional method in the efficiency and quality of data anomaly detection, and has certain research significance in the field of power grid security. Reference [6] puts forward a low-cost system for highfrequency solar imaging and power data acquisition. With the progress of solar energy research and more and more accurate prediction technology, intermittence is no longer an obstacle to the adoption of solar energy.…”