skip to main content

Title: Systematic Evaluation of Stochastic Methods in Power System Scheduling and Dispatch with Renewable Energy

As more wind power and other renewable resources are being integrated into the electric power grid, the forecast uncertainty brings operational challenges for the power system operators. In this report, different operational strategies for uncertainty management are presented and evaluated. A comprehensive and consistent simulation framework is developed to analyze the performance of different reserve policies and scheduling techniques under uncertainty in wind power. Numerical simulations are conducted on a modified version of the IEEE 118-bus system with a 20% wind penetration level, comparing deterministic, interval, and stochastic unit commitment strategies. The results show that stochastic unit commitment provides a reliable schedule without large increases in operational costs. Moreover, decomposition techniques, such as load shift factor and Benders decomposition, can help in overcoming the computational obstacles to stochastic unit commitment and enable the use of a larger scenario set to represent forecast uncertainty. In contrast, deterministic and interval unit commitment tend to give higher system costs as more reserves are being scheduled to address forecast uncertainty. However, these approaches require a much lower computational effort Choosing a proper lower bound for the forecast uncertainty is important for balancing reliability and system operational cost in deterministic and interval unit commitment. Finally,more » we find that the introduction of zonal reserve requirements improves reliability, but at the expense of higher operational costs.« less
 [1] ;  [2] ;  [3] ;  [2]
  1. Univ. of Washington, Seattle, WA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
  3. Argonne National Lab. (ANL), Argonne, IL (United States); Electric Reliability Council of Texas (ERCOT), Austin, TX (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Technical Report
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Country of Publication:
United States