A robust unit commitment model under correlated temperatures and demands

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

Abstract

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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温度和需求相关条件下的鲁棒机组承诺模型
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。
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