Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 34, Issue 3, Pages 1814-1823Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2018.2880996
Keywords
Unit commitment; multistage stochastic integer programming; stochastic dual dynamic integer programming
Categories
Funding
- National Science Foundation [1633196, 1751747]
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [1633196] Funding Source: National Science Foundation
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1751747] Funding Source: National Science Foundation
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Unit commitment (UC) is a key operational problem in power systems for the optimal schedule of daily generation commitment. Incorporating uncertainty in this already difficult mixedinteger optimization problem introduces significant computational challenges. Most existing stochastic UC models consider either a two-stage decision structure, where the commitment schedule for the entire planning horizon is decided before the uncertainty is realized, or a multistage stochastic programming model with relatively small scenario trees to ensure tractability. We propose a new type of decomposition algorithm, based on the recently proposed framework of stochastic dual dynamic integer programming (SDDiP), to solve the multistage stochastic unit commitment (MSUC) problem. We propose a variety of computational enhancements to SDDiP, and conduct systematic and extensive computational experiments to demonstrate that the proposed method is able to handle elaborate stochastic processes and can solve MSUCs with a huge number of scenarios that are impossible to handle by existing methods.
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