Abstract

Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast models must be supported by updated information of the local irradiance field, and solar sensor networks are positioning as the more direct way to obtain these data. The development of solar sensor networks adapted to small-scale systems as microgrids is subject to specific requirements: high updating frequency, high density of measurement points and low investment. This paper proposes a wireless sensor network able to provide snapshots of the irradiance field with an updating frequency of 2 Hz. The network comprised 16 motes regularly distributed over an area of 15 m × 15 m (4 motes × 4 motes, minimum intersensor distance of 5 m). The irradiance values were estimated from illuminance measurements acquired by lux-meters in the network motes. The estimated irradiances were validated with measurements of a secondary standard pyranometer obtaining a mean absolute error of 24.4 W/m and a standard deviation of 36.1 W/m. The network was able to capture the cloud motion and the main features of the irradiance field even with the reduced dimensions of the monitoring area. These results and the low-cost of the measurement devices indicate that this concept of solar sensor networks would be appropriate not only for photovoltaic plants in the range of MW, but also for smaller systems such as the ones installed in microgrids.

Highlights

  • Sensor networks are consolidating as promising data sources for future solar energy forecasting applications, for local and very-short term applications

  • All-sky cameras and satellite imagery have been used for this purpose, but, due to the complexity and inaccuracies associated with the image-to-irradiance conversion process, solar sensor networks are gaining attention as a direct solution to capture the local irradiance field and its evolution [1]

  • The present study described and tested an irradiance monitoring system adapted to the restrictive necessities of MGs or small-scale PV systems

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Summary

Introduction

Sensor networks are consolidating as promising data sources for future solar energy forecasting applications, for local and very-short term applications At these scales, solar instrumentation is focused on capturing the cloud motion, which is the main cause of irradiance variations. Solar sensor networks have been used in different studies, generally involving scales larger than the ones associated with MGs. Data are acquired by a set of sensors randomly distributed over the concerned area, and later processed to estimate the solar variability of the area or forecast the irradiance at a certain point. The network should be able to capture the over irradiance events produced by the clouds’ edges to prevent damages in PV-inverters It should demand an easy-to-implement infrastructure and a low investment appropriated to the scale of the concerned systems.

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