Scenario reduction based on correlation sensitivity and its application in microgrid optimization,International Transactions on Electrical Energy Systems

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Scenario reduction based on correlation sensitivity and its application in microgrid optimization
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-01-18 , DOI: 10.1002/2050-7038.12747
Jinxing Hu ₁ , Hongru Li ₁ , Zhenyu Liu ₂

Affiliation

In the stochastic programming involving multiple renewable energy sources such as solar and wind, uncertainties and correlations exist simultaneously in various random variables. To accurately describe them, a large number of scenarios are necessary to be generated, which may render the original programming problem intractable and require critical scenario reduction operations. This paper addresses two crucial issues in scenario reduction: (a) how to preserve the correlation properties of the generated scenarios after reduction and (b) how to guarantee the quality of decision results after reduction. For the first issue, the concepts of correlation sensitivity and partial correlation loss are proposed to specifically retain some key correlations that have an important impact on the solution stability. For the second issue, this paper proposes a novel scenario reduction method that aims to minimize the partial correlation loss and maximize the probabilistic similarity degree before and after reduction. Comparative studies are performed to evaluate the validity and universality of the proposed method. Numerical results of the microgrid economic operation optimization problem show that the reduced scenario set obtained by eliminating 97.8% scenarios can provide approximate target value to the problem with less than 5% accuracy errors and CPU time reduction of around 93.4%.

中文翻译：

基于相关敏感性的场景约简及其在微电网优化中的应用

在涉及多个可再生能源（例如太阳能和风能）的随机规划中，不确定性和相关性同时存在于各种随机变量中。为了准确地描述它们，必须生成大量场景，这可能使原始编程问题变得棘手，并需要进行关键场景缩减操作。本文讨论了场景缩减中的两个关键问题：（a）缩减后如何保留生成的场景的相关属性，以及（b）缩减后如何保证决策结果的质量。对于第一个问题，提出了相关敏感性和部分相关损失的概念，以专门保留一些对解决方案稳定性有重要影响的关键相关性。对于第二期本文提出了一种新的场景约简方法，旨在最小化部分相关损失，并最大程度地减少约简前后的概率相似度。进行了比较研究，以评估所提出方法的有效性和普遍性。微电网经济运行优化问题的数值结果表明，通过消除97.8％的情景获得的减少的情景集可以为该问题提供近似的目标值，且准确度误差小于5％，CPU时间减少了约93.4％。

更新日期：2021-03-02

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