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European Journal of Operational Research, Volume 234, Issue 3, 1 May 2014, Pages 751-762.
Ruiwei Jianga, Muhong Zhangb, Guang Lic, Yongpei Guana
a-Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611, USA and
b-School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA and
c-Electric Reliability Council of Texas (ERCOT), Austin, TX 78744, USA.
Abstract
For a current deregulated power system, a large amount of operating reserve is often required to maintain the reliability of the power system using traditional approaches. In this paper, we propose a two-stage robust optimization model to address the network constrained unit commitment problem under uncertainty. In our approach, uncertain problem parameters are assumed to be within a given uncertainty set. We study cases with and without transmission capacity and ramp-rate limits (The latter case was described in Zhang and Guan (2009), for which the analysis part is included in Section 3 in this paper). We also analyze solution schemes to solve each problem that include an exact solution approach and an efficient heuristic approach that provides tight lower and upper bounds for the general network constrained robust unit commitment problem. The final computational experiments on an IEEE 118-bus system verify the effectiveness of our approaches, as compared to the nominal model without considering the uncertainty.
Additional information:
Renewable energy has been increasingly penetrating into the power grid system recently. Due to its intermittent nature, a large amount of operating reserve is required to maintain the reliability of the power system using traditional approaches. To address this challenging issue, this paper provides one of the first studies on developing two-stage robust optimization models and solution approaches to solve the reliability unit commitment run problems, so as to reduce reserve amount while ensuring system robustness. It provides an innovative method to decide reserve levels at different stages for power system operations and leads to operating reserve cost savings.
