Title: The Applications of Stochastic Optimization in Power System Operations

Speaker: Huang Yuping (Dr. University of Central Florida)

Time: Thursday, Oct 26, 2017, 15:00

Venue: Meeting room 625, Hongsheng Technology Building, Wushan Campus

[Report Summary]

With the high penetration of renewable energy and increasing deregulation of the electricity industry, a lot of uncertainties on electricity supply and transmission add great stresses to power system operation. Optimization approaches have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources. Because of the significant variability and intermittent of renewable energy, traditional deterministic optimization approaches become less attractive and thus have been transited to stochastic optimization to improve the schedule of generating units for better accommodating the large fluctuations in renewable generation outputs and maintaining the power system reliability.

This talk will introduce the applications of stochastic optimization in unit commitment, which is often used by U.S. independent system operators and generation companies (GENCOs). In the energy market, risk-constrained stochastic unit commitment models were designed with the implementations of demand response projects and energy storage, to model risks associated with the decisions in a stochastic environment. The advance of such models can avoid over-conservative solutions but still ensure system reliability by limiting loss of loads. As for ancillary service market, a stochastic reliability unit commitment model with Conditional Value-at-Risk (CVaR) constraints can replace current rigid operating reserve requirements but ensure the desired reliability level with lowest cost options and fewer generation resources. Last, a small power system that usually is owned by a GENCO could be used to support running an electric transportation system. This talk will introduce the study about the co-optimization of power generation planning and electric vehicle service scheduling, aiming to explore the mobile energy storage function of electric vehicles in micro grids.