@misc{58f62c87350f44f998efe10dcb679533,
title = "Pro2R: Procurement of Ramping Product and Regulation in CAISO Using Probabilistic Solar Power Forecasts",
abstract = "This presentation summarizes the objectives and findings from the project titled, {"}Pro2R: Coordinated Procurement of Ramping Product & Regulation in CAISO Using Probabilistic Solar Power Forecasts,{"} funded by DOE SETO. The goal is to develop cutting edge probabilistic solar power forecasting methods, and integrate them into ISO market operations. The team has integrated in two ways: 1) to procure ramping product and regulation requirements (ancillary services) in the California ISO market, and 2) to develop an open source visitation and ramp alert related situational awareness using probabilistic forecasts. This deck also summarizes the results from the use of machine learning methods to relate probabilistic solar forecasts to the the needs for flexible ramp product in the California ISO system.",
keywords = "dynamic regulation, flexible ramping product, machine learning, market benefits, open source visualization, probabilistic solar power forecasts, reliability, situational awareness",
author = "Benjamin Hobbs and Venkat Krishnan and Paul Edwards and Haiku Sky and Ibrahim Krad and Carlo Siebenschuh and Hendrik Hamann and Rui Zhang and Jie Zhang and Binghui Li and Li He and Yijiao Wang and Shu Zhang",
year = "2021",
language = "American English",
series = "Presented at the Solar Energy Technologies Office (SETO) Workshop on Solar Forecasting, 5-6 May 2021",
type = "Other",
}