TY - JOUR
T1 - Impact of Data Quality on Real-Time Locational Marginal Price
JF - IEEE Transactions on Power Systems
Y1 - 2014/03//
SP - 627
EP - 636
A1 - Liyan Jia
A1 - Kim, Jinsub
A1 - Robert J. Thomas
A1 - Lang Tong
KW - electricity markets
KW - locational marginal pricing
KW - reliability and markets
KW - RM11-003
AB - The problem of characterizing impacts of data quality on real-time locational marginal price (LMP) is considered. Because the real-time LMP is computed from the estimated network topology and system state, bad data that cause errors in topology processing and state estimation affect real-time LMP. It is shown that the power system state space is partitioned into price regions of convex polytopes. Under different bad data models, the worst case impacts of bad data on real-time LMP are analyzed. Numerical simulations are used to illustrate worst case performance for IEEE-14 and IEEE-118 networks.
VL - 29
IS - 2
JO - IEEE Trans. Power Syst.
DO - 10.1109/TPWRS.2013.2286992
ER -
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 -
TY - JOUR
T1 - On Topology Attack of a Smart Grid: Undetectable Attacks and Countermeasures
JF - IEEE Journal on Selected Areas in Communications
Y1 - 2013/07//
SP - 1294
EP - 1305
A1 - Kim, Jinsub
A1 - Lang Tong
KW - power system economics
KW - power system security
KW - pricing
KW - reliability and markets
KW - RM11-003
KW - smart grid
AB - Covert data attacks on the network topology of a smart grid is considered. In a so-called man-in-the-middle attack, an adversary alters data from certain meters and network switches to mislead the control center with an incorrect network topology while avoiding detections by the control center. A necessary and sufficient condition for the existence of an undetectable attack is obtained for strong adversaries who can observe all meter and network data. For weak adversaries with only local information, a heuristic method of undetectable attack is proposed. Countermeasures to prevent undetectable attacks are also considered. It is shown that undetectable attacks do not exist if a set of meters satisfying a certain branch covering property are protected. The proposed attacks are tested with IEEE 14-bus and IEEE 118-bus system, and their effect on real-time locational marginal pricing is examined.
VL - 31
IS - 7
JO - IEEE J. Select. Areas Commun.
DO - 10.1109/JSAC.2013.130712
ER -