Skip to content

“Uncertainty Modeling & Risk Mitigation of Power Markets Operations”

Dr. Zhi Zhou
Computational Scientist
Argonne National Laboratory
January 20, 2017    2:30-3:30
John D. Tickle Building 410



Renewable energy is being rapidly introduced into existing energy supply portfolios because it is a renewable and clean source of energy as opposed to fossil fuels, whose price is prone to escalation and negative effect to environment gets more attention. However, several critical issues must be solved before we can achieve large-scale penetration. This talk focuses on the issues coming with supply uncertainty in wind power generation, which is inherently intermittent and variable, giving rise to new challenges for a reliable and cost-efficient operation of power systems.

This talk presents two major parts. The first part discusses the modeling and representation of uncertainty, which includes a wind power probabilistic forecasting method using probabilistic kernel density forecasting with a quantile-copula estimator. This model can yield accurate wind power distribution estimation in forms of scenario and quantile sets. The second part discusses several applications on power system and market operations with significant supply/demand uncertainties from both a system operator and market participants’ perspectives. On the system operator’s perspective, we present a series of novel unit commitment (UC) models based on different uncertainty process models, including stochastic programming based UC, chance-constraint goal programming based UC, interval optimization based UC. In addition, an extension of current deterministic UC model is presented, which uses dynamic generation reserve strategies derived from probabilistic information to account for uncertainties. From market participants’ perspective, we present applications on wind power producers’ bidding strategy, under the risk of uncertainties from market prices and wind power production.


Dr. Zhi Zhou is a Computational Scientist with the Center for Energy, Environmental, Economic Systems Analysis at Argonne National Laboratory. He received his Ph.D. degree in Decision Sciences and Engineering Systems from the Rensselaer Polytechnic Institute in 2010. He also received his M.E. and B.E. degrees in Computer Sciences from Wuhan University in 2001 and 2004, respectively. Dr. Zhou’s research mainly focuses on the areas of operations research, modeling and analysis of complex systems with uncertainties, and the applications on power systems/markets, renewable energy integrations, smart grid, and the interdependency with other infrastructure, including transportation, water, climate, etc.


The flagship campus of the University of Tennessee System and partner in the Tennessee Transfer Pathway.