Multistage Stochastic Unit Commitment Using Stochastic Dual Dynamic Integer Programming
Multistage Stochastic Unit Commitment Using Stochastic Dual Dynamic Integer Programming
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DOI：
10.1109/tpwrs.2018.2880996
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发表时间：
2019-05
影响因子：
6.6
通讯作者：
Jikai Zou;Shabbir Ahmed;X. Sun
中科院分区：
文献类型：
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作者：
Jikai Zou;Shabbir Ahmed;X. Sun
机组承诺是电力系统日发电承诺最优调度的关键运行问题。在这个已经很困难的混合整数优化问题中加入不确定性会带来重大的计算挑战。大多数现有的随机UC模型要么采用两阶段决策结构，即在不确定性实现之前确定整个规划范围的承诺进度，要么采用多阶段随机规划模型，并采用相对较小的场景树来确保可追溯性。基于随机对偶动态整数规划（SDDiP）框架，提出了一种求解多阶段随机单元承诺（MSUC）问题的新型分解算法。我们提出了对SDDiP的各种计算增强，并进行了系统和广泛的计算实验，以证明所提出的方法能够处理复杂的随机过程，并且可以解决现有方法无法处理的大量场景的msuc。
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 mixed-integer 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.