A k-Nearest Neighbor Space-Time Simulator with applications to large-scale wind and solar power modelling

• DOI: 10.5281/zenodo.5912033
• Publication Date: 2022-01-27
• Authors: Yash Amonkar; David Farnham; Upmanu Lall
• Keywords: 13. Climate action; 0207 environmental engineering; 02 engineering and technology; 7. Clean energy; 01 natural sciences; Article; 0105 earth and related environmental sciences

We develop and present a k-Nearest Neighbor Space-Time Simulator that accounts for the spatiotemporal dependence in high dimensional hydroclimatic fields (e.g., wind and solar) and can simulate synthetic realizations of arbitrary length. We illustrate how this statistical simulation tool can be used in the context of regional power system planning under a scenario of high reliance on wind and solar generation and when long historical records of wind and solar power generation potential are not available. We show how our simulation model can be used to assess the probability distribution of the severity and duration of energy ���droughts��� at the network scale that need to be managed by long duration storage or alternate energy sources. We present this estimation of supply side shortages for the Texas Interconnection.<br/>This is a version of the GitHub repository with data and simulations. Added separately due to the size constraints in GitHub. GitHub Repo Link - https://github.com/yashamonkar/LDS-Inferences<br/>