温度和需求相关条件下的鲁棒机组承诺模型

Anna Danandeh, Wen Wang, Bo Zeng, B. Buckley
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引用次数: 2

摘要

鲁棒单位承诺(UC)模型已经深入研究了对冲随机性和风险的有效方法。所有现有的稳健的UC配方都考虑到需求和/或成本的不确定性。然而,我们注意到,电力系统可能会受到周围温度的严重影响,并且燃气发电机的效率、需求和温度之间存在很强的关系。在此基础上,我们建立了一个鲁棒优化模型,考虑了温度和需求预测的相关不确定性,以及前者对发电效率的影响。在一个典型的IEEE测试系统上进行了数值实验,分析了我们的公式和不确定温度的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust unit commitment model under correlated temperatures and demands
Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and temperature. With that observation, we develop a robust optimization model considering correlated uncertainties in temperature and demand forecasting, and the impact of the former one on generating efficiency. Numerical experiments are conducted on a typical IEEE test system to analyse our formulation and the impact of uncertain temperature.
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