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A data-driven approach to identifying system pattern regions in market operations

机译:一种数据驱动方法来识别市场运营中系统模式区域的方法

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This paper studies the fundamental coupling between individual load levels and locational marginal prices in security constrained economic dispatch. The concepts of system pattern and system pattern region (SPR) are introduced for the analysis. Theoretical investigation suggests that SPRs are disjoint, convex, and separable sets and there exists separating hyperplanes among SPRs. Furthermore, the total number of SPRs is finite and the SPRs are one-to-one mapped with vectors of LMPs. Monte-Carlo simulation results provide solid support of the theoretical analysis and reveal more characteristics of system patterns and SPRs. Based on the theoretical analysis, a data-driven approach to identifying the separating hyperplanes among SPRs is proposed. This approach suggests the potential use of historical load/price data for understanding and predicting system status and prices. One promising feature of the proposed approach is that the vector of LMPs at all the buses can be successfully pinpointed given a load vector without the information of system topology. Case studies in IEEE 24 bus system illustrate the potential value of this approach in operational planning and energy trading.
机译:本文研究了个人负荷水平与安全受限经济派遣中的基本耦合。引入了系统模式和系统图案区域(SPR)的概念进行分析。理论研究表明,SPR是不相交的,凸和可分离的组,并且在SPR中存在分离超平面。此外,SPR的总数是有限的,并且SPR是用LMP的载体映射的一对一。 Monte-Carlo仿真结果提供了理论分析的坚实支持,并揭示了系统模式和SPR的更多特征。基于理论分析,提出了一种识别SPR之间识别分离超平面的数据驱动方法。这种方法表明潜在使用历史负荷/价格数据,以了解和预测系统状态和价格。所提出的方法的一个有希望的特征是,在没有系统拓扑信息的情况下,可以成功定位所有总线的LMP的向量。 IEEE 24总线系统的案例研究说明了这种方法在运营规划和能源交易中的潜在价值。

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