This research aims to develop decision support tools for better maintenance and planning of renewable energy generation and storage assets using atmospheric, local weather, and on-ground environmental…

This research aims to develop decision support tools for better maintenance and planning of renewable energy generation and storage assets using atmospheric, local weather, and on-ground environmental data blended with site-, regional- and national-generation data. The study will use a combination of these data to understand the relationship between non-cloud cover based atmospheric conditions and the impact on renewable energy generation and storage which will then be used to develop models for planning and decision support for operations. Research will be conducted across multiple renewable generation and storage sites with diverse environmental conditions to validate and verify the existing model developed during phase I of this research. The expected results of this research include a better understanding of the relationship between atmospheric conditions and the impact on renewable energy generation and storage, the development of a decision support tool for proactive and reaction