Probalistic Forecast of Real-Time LMPs

Project Status: 
Completed

As more renewable resources are integrated into the transmission system, and the power system operates closer to its capacity, congestion conditions become less predictable and locational marginal prices  more volatile. The increased congestion and price uncertainties pose significant challenges to system operators and market participants. This research aims to develop new computationally tractable techniques for short-term probabilistic forecasting of  real-time locational marginal price in a power grid.  In particular, the developed methods provide the probability distribution of the locational marginal prices and congestion patterns up to several hours ahead of the operation time.   For system operators and market participants, such techniques can be used for congestion management, system planning, risk management, and demand response.

Related Publications

Guo, Ye, Yuting Ji, and Lang Tong. "Incorporating interface bids in the economic dispatch for multi-area power systems." 2017 IEEE Power & Energy Society General Meeting (PESGM). Chicago, IL, USA: IEEE, 2017.
Guo, Ye, and Lang Tong. "Robust tie-line scheduling for multi-area power systems with finite-step convergence." 2017 IEEE Power & Energy Society General Meeting (PESGM). Chicago, IL, USA: IEEE, 2017.
Ji, Yuting, and Lang Tong. "Multi-proxy interchange scheduling under uncertainty." 2016 IEEE Power and Energy Society General Meeting (PESGM). Boston, MA, USA: IEEE, 2016. 1 - 5.
Ji, Yuting, Robert J Thomas, and Lang Tong. "Probabilistic Forecast of Real-Time LMP via Multiparametric Programming." 48th Hawaii International Conference on System Sciences (HICSS). Kauai, HI: IEEE, 2015.
Jia, Liyan, and Lang Tong. "Renewable in distribution networks: Centralized vs. decentralized integration." 2015 IEEE Power & Energy Society General Meeting. Denver, CO, USA: IEEE, 2015. 1 - 5.
Ji, Yuting, and Lang Tong. "Stochastic coordinated transaction scheduling via probabilistic forecast." 2015 IEEE Power & Energy Society General Meeting. Denver, CO, USA: IEEE, 2015. 1 - 5.
Ji, Yuting, Jinsub Kim, Robert J Thomas, and Lang Tong. "Forecasting real-time locational marginal price: A state space approach." 2013 Asilomar Conference on Signals, Systems and Computers. Pacific Grove, CA, USA: IEEE, 2013. 379 - 383.