Measurement-based Locational Marginal Pricing in Active Distribution Systems

Roohallah Khatami, Severin Nowak, Y. Chen
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引用次数: 2

Abstract

This paper proposes a measurement-based method for calculating real-time distribution locational marginal prices (DLMPs) without the use of an offline network model. Instead, the proposed method relies only on online measurements collected at a subset of distribution system buses to estimate a linear sensitivity model mapping bus voltages to injections, which in turn is embedded in an optimal power flow (OPF) problem as an equality constraint. The proposed method completely obviates the need for an accurate distribution network model that may not be available, especially for active distribution networks with faster variations in operating point. Also, the proposed method renders the original OPF problem with nonlinear constraints a computationally efficient quadratic programming problem (with linear constraints) and provides sufficiently accurate DLMPs at buses where measurements are collected. Via numerical simulations involving a 33-bus test system, we demonstrate that the proposed method yields similar DLMPs as solving the OPF problem with an up-to-date model and greatly outperforms it when the model is out of date.
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主动配电系统中基于计量的区位边际定价
本文提出了一种不使用离线网络模型的实时分配区位边际价格(DLMPs)计算方法。相反,该方法仅依赖于在配电系统总线子集上收集的在线测量数据来估计将总线电压映射到注入的线性灵敏度模型,该模型反过来作为等式约束嵌入到最优潮流(OPF)问题中。该方法完全避免了对准确的配电网模型的需要,特别是对于运行点变化较快的主动配电网。此外,所提出的方法使具有非线性约束的原始OPF问题成为计算效率高的二次规划问题(具有线性约束),并在收集测量的总线上提供足够精确的dlmp。通过涉及33总线测试系统的数值模拟,我们证明了所提出的方法产生的dlmp与使用最新模型解决OPF问题相似,并且在模型过时时大大优于它。
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