Argonne National Laboratory

Economic Impacts of Wind Covariance Estimation on Power Grid Operations

TitleEconomic Impacts of Wind Covariance Estimation on Power Grid Operations
Publication TypeConference Paper
Year of Publication2014
AuthorsPetra, CG, Zavala, VM, Nino-Ruiz, ED, Anitescu, M
Conference NameFERC Technical Conference on RT and Market Efficiency through Improved Software
Date Published06/2014
Other NumbersANL/MCS-P5148-0614
AbstractWe study the impact of capturing spatiotemporal correlations between multiple wind supply points on economic dispatch procedures. Using a simple dispatch model, we first show analytically that over/underestimation of correlation leads to positive and negative biases of dispatch cost, respectively. A rigorous, large-scale computational study for the State of Illinois transmission grid with real topology and physical constraints reveals similar conclusions. For this study, we use the Rao-Blackwell-Ledoit-Wolf estimator to approximate the wind covariance matrix from a small number of wind samples generated with the numerical weather prediction model WRF and we use the covariance information to generate a large number of wind scenarios. The resulting stochastic dispatch problems are solved by using the interior-point solver PIPS-IPM on the BlueGene/Q (Mira) supercomputer at Argonne National Laboratory. We find that strong and persistent biases result from neglecting correlation information and indicate to the need to design a market that coordinates weather forecasts and uncertainty characterizations.