The Unit Commitment Problem With AC Optimal Power Flow Constraints
The Unit Commitment Problem With AC Optimal Power Flow Constraints
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DOI：
10.1109/tpwrs.2015.2511010
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发表时间：
2016-01
影响因子：
6.6
通讯作者：
Anya Castillo;C. Laird;Cesar A. Silva-Monroy;J. Watson;R. O'Neill
中科院分区：
文献类型：
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作者：
Anya Castillo;C. Laird;Cesar A. Silva-Monroy;J. Watson;R. O'Neill
提出了一种基于数学规划的带交流最优潮流(ACOPF)网络约束的机组组合优化方法。该问题是一个非凸混合整数非线性规划(MINLP)，我们用基于外逼近法的求解技术来求解。我们的解决方案技术在机组组合约束和ACOPF约束下共同优化实时和无功调度和调度。该方法是一种利用强大的线性和混合整数商业求解器的局部求解方法。与铜板和DCOPF约束建模方法相比，我们展示了更精确的ACOPF约束建模对机组组合问题的相对经济和运行影响；我们使用6节点、IEEE RTS-79和IEEE-118测试系统进行分析。我们的方法可以扩展到求解更大规模的电力系统，也可以通过分解技术来考虑安全约束或不确定性。
We propose a mathematical programming-based approach to optimize the unit commitment problem with alternating current optimal power flow (ACOPF) network constraints. This problem is a nonconvex mixed-integer nonlinear program (MINLP) that we solve through a solution technique based on the outer approximation method. Our solution technique cooptimizes real and reactive power scheduling and dispatch subject to both unit commitment constraints and ACOPF constraints. The proposed approach is a local solution method that leverages powerful linear and mixed-integer commercial solvers. We demonstrate the relative economic and operational impact of more accurate ACOPF constraint modeling on the unit commitment problem, when compared with copperplate and DCOPF constraint modeling approaches; we use a six-bus, the IEEE RTS-79, and the IEEE-118 test systems for this analysis. Our approach can be extended to solve larger scale power systems as well as include security constraints or uncertainty through decomposition techniques.