TY - CONF
T1 - Forecasting real-time locational marginal price: A state space approach
T2 - 2013 Asilomar Conference on Signals, Systems and Computers
Y1 - 2013/11//
SP - 379
EP - 383
A1 - Yuting Ji
A1 - Kim, Jinsub
A1 - Robert J. Thomas
A1 - Lang Tong
KW - CERTS
KW - locational marginal pricing
KW - reliability and markets
KW - RM13-002
AB - The problem of forecasting the real-time locational marginal price (LMP) by a system operator is considered. A new probabilistic forecasting framework is developed based on a time in-homogeneous Markov chain representation of the realtime LMP calculation. By incorporating real-time measurements and forecasts, the proposed forecasting algorithm generates the posterior probability distribution of future locational marginal prices with forecast horizons of 6-8 hours. Such a short-term forecast provides actionable information for market participants and system operators. A Monte Carlo technique is used to estimate the posterior transition probabilities of the Markov chain, and the real-time LMP forecast is computed by the product of the estimated transition matrices. The proposed forecasting algorithm is tested on the PJM 5-bus system. Simulations show marked improvements over benchmark techniques.
JF - 2013 Asilomar Conference on Signals, Systems and Computers
PB - IEEE
CY - Pacific Grove, CA, USA
DO - 10.1109/ACSSC.2013.6810300
ER -