AMPS: Deep Stochastic Models for Space-Time Weather-Driven Grid Simulations

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The power system is changing rapidly with the introduction of large amounts of distributed energy resources such as distributed photovoltaics and loads with demand response potential. The addition of uncertain and variable distributed energy resources requires better understanding of potential impacts on grid operations. Direct testing on the grid is not possible, and the reliance on computer simulations for varying degrees of the distributed energy resource penetration is necessary. The companion mathematical challenge is in generating realistic scenarios of supplies and loads at the customer level, often at high spatial and temporal resolutions involving joint generation of tens of thousands of correlated space-time variables. Moreover, such processes are plagued by discontinuities due to electrical device switching in loads and microscale weather variations in distributed photovoltaics supply. This project represents an end-to-end effort developing new mathematical tools that will be applied to realistic electricity network testbeds.This research will develop a framework for space-time jump-diffusion processes that capture realistic non-Gaussian behavior of distributed energy resources and loads at high time frequencies. Such models will yield unprecedented insights into distributed energy resource implications on current and future grids. The testbed for the new framework and methodology is a state-of-the-art distribution simulation network dataset, Smart-DS. Results of this research will have potential impacts in infrastructure and energy planning by studying grid responses to varying levels of the distributed energy resource adoption. The statistical models will be applicable to a variety of fields including financial mathematics, environmetrics, geography and ecology. Moreover, this research will support student training at the intersection of statistics and energy science, who will gain interdisciplinary and collaborative experience with domain scientists during summer internships at the National Renewable Energy Laboratory.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.