An interval two-stage robust stochastic programming approach for steam power systems design and operation optimization under complex uncertainties. (18th May 2022)

• Record Type: Journal Article
• Authors: Niu, Teng; Yin, Hongchao; Feng, Enmin
• Is Part Of: Chemical engineering science. Volume 253(2022)
• Publication Date: 2022-05-18
• Subjects: Steam power systems -- Optimization -- Uncertainty -- Interval two-stage robust stochastic programming -- System risks; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2022.117533
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: Present uncertainties as both probability distributions and discrete intervals. Permit in-depth analyse of various scenarios for the violated promised policy targets. Directly reflect the system risk into the optimization model. Assess trade-offs between system economy and stability. Abstract: In this study, an interval two-stage robust stochastic programming approach is developed for the design and operation optimization of steam power systems under complex uncertainties by integrating interval-parameter programming and robust optimization into two-stage stochastic programming. The approach has the following advantages: (1) it extends the traditional two-stage stochastic programming method by enabling uncertainties presented as both probability distributions and discrete intervals to be effectively incorporated within the optimization framework, and could permit in-depth analyses of various policy scenarios when the promised policy targets are violated; (2) it could effectively reflect system risks generated by stochastic programming process, overcome the deficiency of uncontrollable risks in system and enhance the robustness of optimization, such that it is suitable for risk-aversion planners under high-variability conditions. One case of a refinery engineering project is provided for demonstrating the applicability and availability of the proposed approach. The numerical results provides ample decision-making space for decision makers to evaluate trade-offs between system economy and stability.