@misc{b205911ac9674d568ac04f651e40c642,
title = "Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System",
abstract = "This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal photovoltaic (PV) power plants reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60\% renewable penetration Western Electricity Coordinating Council (WECC) system. On a realistic 1-day operation profile of the WECC system, the ML model demonstrates a savings of more than 40\% PV headroom compared to a conservative approach.",
keywords = "frequency control, machine learning, photovoltaics, PV, WECC, Western Electricity Coordinating Council",
author = "Haoyu Yuan and Jin Tan and Yingchen Zhang and Shutang You and Hongyu Li and Yu Su and Yilu Liu and Samanvitha Murthy",
year = "2020",
language = "American English",
series = "Presented at the Innovative Smart Grid Technologies (ISGT 2020) North America, 17-20 February 2020, Washington, D.C.",
publisher = "National Laboratory of the Rockies (NLR)",
address = "United States",
type = "Other",
}