Towards the Development of a Low-Cost Irradiance Nowcasting Sky Imager

Luis Valentín,Carlos Pineda-Arellano,Cesar Peña-Martínez,Manuel Peña-Cruz,Daniela Moctezuma,Arturo Díaz-Ponce

doi:10.3390/app9061131

Abstract

Solar resource assessment is fundamental to reduce the risk in selecting the solar power-plants’ location; also for designing the appropriate solar-energy conversion technology and operating new sources of solar-power generation. Having a reliable methodology for solar irradiance forecasting allows accurately identifying variations in the plant energy production and, as a consequence, determining improvements in energy supply strategies. A new trend for solar resource assessment is based on the analysis of the sky dynamics by processing a set of images of the sky dome. In this paper, a methodology for processing the sky dome images to obtain the position of the Sun is presented; this parameter is relevant to compute the solar irradiance implemented in solar resource assessment. This methodology is based on the implementation of several techniques in order to achieve a combined, fast, and robust detection system for the Sun position regardless of the conditions of the sky, which is a complex task due to the variability of the sky dynamics. Identifying the correct position of the Sun is a critical parameter to project whether, in the presence of clouds, the occlusion of the Sun is occurring, which is essential in short-term solar resource assessment, the so-called irradiance nowcasting. The experimental results confirm that the proposed methodology performs well in the detection of the position of the Sun not only in a clear-sky day, but also in a cloudy one. The proposed methodology is also a reliable tool to cover the dynamics of the sky.

Highlights

The assessment of solar irradiance has become one of the most important topics in the field of solar energy, such as the photovoltaic industry (PV), concentrating solar power (CSP), and the solar chemistry process [1,2,3,4]
The prototype was designed with the intention of capturing sky dome images for detecting the position of the Sun and analyzing sky dynamics, avoiding the use of high-cost fish eye lenses, as well as expanding CMOS sensor life by avoiding overexposure to the sunlight
A novel methodology based on the implementation of several image processing techniques to achieve a robust and automatic detection of the position of the Sun from a set of images, acquired with a low-cost artificial vision system, was proposed

Summary

Introduction

The assessment of solar irradiance has become one of the most important topics in the field of solar energy, such as the photovoltaic industry (PV), concentrating solar power (CSP), and the solar chemistry process [1,2,3,4]. In the solar power industry, constant assessment of the solar resource is essential to establish the viability of exploiting a specific location and predicting the factors that may affect its energy production. Having an accurate assessment of the solar resource is an important advantage that can help in establishing solar energy as a more competitive alternative. The proposal in [1] argued that the assessment and forecasting of the solar resource are essential tasks, since they allow better management of the solar field in real time, reducing the maintenance activities, improving the expected benefits. The installation of PV and CSP plants has generated an increase in the production of electricity with renewable energy, and it is to be expected that this trend will continue

Methods

Results

Conclusion