Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning
Approximate Latent Factor Algorithm for Scenario Selection and Weighting in Transmission Expansion Planning
复制标题
输电扩容规划场景选择和加权的近似潜因子算法
DOI：
10.1109/tpwrs.2019.2942925
复制
发表时间：
2020
影响因子：
6.6
通讯作者：
Webster, Mort D.
中科院分区：
文献类型：
--
作者：
Bukenberger, Jesse P.;Webster, Mort D.
输电扩展规划的一个主要难点是选择具有代表性的场景来评估候选输电网络。需求和可再生发电的可变性使得在计算可靠性和成本时包含几个场景至关重要，但在优化中包含太多场景在计算上是难以处理的。为了减少获得系统精确近似值所需的代表性操作条件的数量，我们提出了一种基于多元统计的方法，该方法利用了不同场景和网络配置之间的潜在相关结构。所提出的算法包括一种客观而严格的方法来选择提供尽可能多的系统信息的场景子集，以及一种从该场景子集精确地近似系统成本的方法。其结果是一组场景和权重，可以很容易地纳入传统的输电扩展规划公式。我们将此应用于具有8,736个不同操作条件的312总线WECC模型。与其他场景约简技术相比，该方法得到的传输方案更可靠，总成本更低，并且优化目标的预期系统性能与实际系统性能之间的误差更小。
One major difficulty in transmission expansion planning is selecting the representative scenarios to use to evaluate candidate transmission networks. The variability in demand and renewable generation makes the inclusion of several scenarios critical when calculating reliability and cost, but including too many scenarios in an optimization is computationally intractable. To reduce the number of representative operating conditions needed to obtain an accurate approximation of the system, we propose a method rooted in multivariate statistics that exploits the latent correlative structure between different scenarios and network configurations. The proposed algorithm includes an objective and rigorous way to select a subset of scenarios that provide as much information about the system as possible, and a method to accurately approximate the system cost from that scenario subset. The result is a set of scenarios and weights that are easily incorporated into traditional transmission expansion planning formulations. We apply this to a 312-bus WECC model with 8,736 distinct operating conditions. The transmission plans found with the proposed method are more reliable and have a lower total cost than those from other scenario reduction techniques, as well as a smaller error between the expected system performance from the optimization objective and the actual system performance.
DOI：
10.1109/pesgm.2015.7285747
发表时间：
2015-07
期刊：
2015 IEEE Power & Energy Society General Meeting
影响因子：
--
作者：
Alexandre Moreira;A. Street;J. Arroyo
通讯作者：
Alexandre Moreira;A. Street;J. Arroyo
用于工程和经济分析的电力系统网络缩减
DOI：
--
发表时间：
2012
期刊：
影响因子：
--
作者：
D. Shi
通讯作者：
D. Shi
影响因子：
--
作者：
ANDERSON, TW
通讯作者：
ANDERSON, TW