The lack of reliable data for ground solar irradiance (direct normal and global irradiance) is a major obstacle for the development of adequate policies to promote and take advantage of existing solar technologies. Although the radiation that reaches the outer layers of the atmosphere is well defined and can be easily calculated, the solar irradiance that reaches the ground level where solar collectors (thermal and photovoltaic) operate depends strongly on localized and complex atmospheric conditions. Distributed, embedded environmental sensor systems are enabling scientists and engineers to observe environmental systems with previously unattainable spatiotemporal resolution. The vision of sensor systems coupled with "smart" networking, and integrated with visualization tools by an overarching cyberinfrastructure is shared by disciplines actively engaged in solar irradiance monitoring all over the world, and will only be realized if such systems are developed ahead of the observatory efforts.
The goal of the project is to build and test an Affordable System for Solar Irradiance Sensing and Tracking (ASSIST). This system will be developed and tested in the heart of California's Central Valley together with a couple of well-characterized, infrastructure-rich solar observatories already deployed at UC Merced and UC Davis. ASSIST will serve as model sensor and information technology system for directly and quantitatively observing the effects of cloud cover, aerosol content, and the presence of participating gases in the lower atmosphere (water vapor, carbon dioxide) and in the stratosphere (ozone), all of which can reduce the availability of direct insolation at the ground level to a small fraction of the solar irradiance that reaches the upper atmosphere. These effects are particularly strong on the Direct Normal Irradiance (DNI). Because cloud cover corresponds to the strongest effect on ground insolation, no statistical method that ignores micro-scale (<2km) or meso-gamma scale (2-20 km) weather systems can succeed in estimating real-time and/or forecasting solar power availability. From the operational standpoint, the balancing of supply and demand peaks in the electrical grid requires detailed consideration of the availability of solar power as the US embraces a more renewable profile of energy utilization. Forecasting the available insolation is therefore an enabling information technology for the success of any policy to include solar power to US power grid.
We propose a tiered-architecture where a small number of expensive and highly calibrated solar observatories get complemented by a larger number of inexpensive but uncalibrated ASSIST nodes. ASSIST will include the following static sensor nodes/arrays which themselves consist of several sensors: (1) wireless irradiance instrument (WII), (2) solar dome instrument (SDI), and (3) long range communication node (CN). ASSIST nodes should adapt to the vagaries of the wireless communication channel, as well as possible failures of many of the nodes in the ensemble. A major innovative aspect of ASSIST will be the integration of economic stand alone wireless global irradiance sensor with a new dome sensor that avoids having costly moving parts and automatic solar trackers (ASTs).