Development and benchmarking of solar nowcasting systems

The cloud induced variability of the solar resource is an operational challenge for both photovoltaic and concentrating solar plants. This and their growing contributions to overall power generation challenge the stability of electricity grids. Storage and grid development can be used to address this issue, whose deployments are optimized by forecasts. For several days ahead, solar forecasts are provided by Numerical Weather Prediction models with typical resolutions of 16-50 km and hours to days. Weather satellites provide solar irradiance predictions with kilometric spatial resolutions and typical temporal resolutions between 5 min and 15 min. This leaves a gap for local, short-term and high resolution solar forecasting systems. High resolution forecasts for the next minutes ahead are notably provided by all-sky imager (ASI) based nowcasting systems. Such systems consist of at least one camera taking hemispherical images of the sky. A large amount of hardware and software configurations to derive such short-term forecasts is proposed in literature. However, different validation periods, locations and approaches as well as the lack of comprehensive benchmarks make direct comparisons difficult. Therefore, the optimal configuration of ASI based nowcasting systems is unclear. To address this question, a modular framework to achieve high resolution spatially resolved solar forecasts for irradiance maps is developed. Within this framework, different hardware and software configurations are tested, highlighting the need for comprehensive benchmarks for each main step involved in the processing: cloud segmentation, cloud motion vector assessment, cloud height estimation. Four cloud segmentation approaches are benchmarked. Furthermore, a novel tool to validate cloud motion vector measurements is developed and applied, ruling out certain setups. Comparing five different cloud height measurement approaches found a setup based on two ASIs to be the most promising. The optimal distance between the cameras of such a two ASI system is investigated both with an in-field study and modeling. Besides benchmarking individual sub-tasks of nowcasting systems, a framework to evaluate nowcasted irradiance maps is applied to example configurations. Special focus is put on temporal and spatial aggregation effects. In order to investigate spatial aggregation effects, spatially resolved reference irradiance maps provided by a developed shadow camera system are compared to nowcasted irradiance maps. Aggregation effects are found to have a strong effect on deviations. With the implemented frameworks and conducted benchmarks, the optimal system among the considered configurations to nowcast irradiance maps is determined to be a two camera setup using a clear sky library based cloud segmentation as well as novel differential approaches for cloud height and motion vector estimations. Further options for improvements are identified to include in-depth studies of cloud dynamics, combinations of ASIs with other sensors such as satellites, optimized cloud segmentation algorithms and the development of systems dedicated to solar ramp forecasts