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Farhadkhani, Mehdi, Rafiee, Majid, Nikpayam, Hossein. (1401). Scenario-Based Hybrid Robust-Stochastic Programming for Coordinated Scheduling of Electricity & Natural Gas Supply Systems. , (), -. doi: 10.22059/aie.2023.349439.1849
Mehdi Farhadkhani; Majid Rafiee; Hossein Nikpayam. "Scenario-Based Hybrid Robust-Stochastic Programming for Coordinated Scheduling of Electricity & Natural Gas Supply Systems". , , , 1401, -. doi: 10.22059/aie.2023.349439.1849
Farhadkhani, Mehdi, Rafiee, Majid, Nikpayam, Hossein. (1401). 'Scenario-Based Hybrid Robust-Stochastic Programming for Coordinated Scheduling of Electricity & Natural Gas Supply Systems', , (), pp. -. doi: 10.22059/aie.2023.349439.1849
Farhadkhani, Mehdi, Rafiee, Majid, Nikpayam, Hossein. Scenario-Based Hybrid Robust-Stochastic Programming for Coordinated Scheduling of Electricity & Natural Gas Supply Systems. , 1401; (): -. doi: 10.22059/aie.2023.349439.1849

Scenario-Based Hybrid Robust-Stochastic Programming for Coordinated Scheduling of Electricity & Natural Gas Supply Systems

Advances in Industrial Engineering
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 24 اسفند 1401
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/aie.2023.349439.1849
نویسندگان
Mehdi Farhadkhani1؛ Majid Rafiee* 2؛ Hossein Nikpayam2
1Niroo Research Institute (NRI)
2Sharif University of Technology
چکیده
Stochastic and robust optimizations have been considered as two different views to stochastic problems. While robust optimization takes optimization in the worst case, stochastic optimization regards no conservative view and merely focuses on expected value. However, unilateral view to stochastic problems is not applicable in most real problems. In this article a hybrid robust and stochastic approach is proposed for optimization problems under uncertainty. Our major contribution is to present different conservative levels in solving an optimization problem by Hybrid Robust and Stochastic Optimization approach. To this end, we cluster uncertain parameters into different clusters using Latin Hypercube Sampling and K-Means clustering tools; having established various numbers of clusters of uncertain parameters, different clustering criteria and a Multi-Criteria Decision Making (MCDM) tool is employed to determine the optimal number of clusters of uncertain parameters. Then, a hybrid energy optimization model under uncertainty is applied to coordinate scheduling of natural gas-fired electricity generation units and gas supply units (gas refinery) under natural gas and electricity demand uncertainty, with known probability distribution and uncertain parameters having different levels of conservatism. The results indicate that while no special trend is evident in the execution time as the number of clusters increases, the optimal value is decreased.
کلیدواژه‌ها
Coordinated Scheduling of Electricity & Natural Gas Supply Systems؛ Hybrid Robust and Stochastic Optimization؛ K-means Clustering؛ Latin Hypercube Sampling؛ Scenario Generation
آمار
تعداد مشاهده مقاله: 215


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