论文标题
基于改进的多层次不确定性集的不确定性管理的位置边际定价机制
A Locational Marginal Pricing Mechanism for Uncertainty Management Based on Improved Multi-Ellipsoidal Uncertainty Set
论文作者
论文摘要
可再生能源（RES）的大规模整合给电力系统带来了巨大挑战。具有成本效益的储备部署和不确定性定价机制对于处理RES的不确定性和可变性至关重要。为此，本文提出了一种新型的位置边际定价机制，用于管理RES的不确定性。首先，考虑到风力动力预测的时间相关性和条件相关性，可以更好地捕获风能的不确定性，以改进了改进的多素质不确定性集（IMEU）。每个椭圆形子集的尺寸是根据综合评估指数优化的，以减少无效区域，而不会大大损失建模准确性，以降低保守主义。然后，建立了基于IMEUS的强大单位承诺（RUC）模型和强大的经济调度（RED）模型，以用于日期的市场清算。在整体调度过程中，都考虑了储备成本和坡度限制。此外，基于红色模型的Langrangian功能，开发了一种新的位置边缘定价机制。引入了不确定性位置边际价格（ULMP），以指控RES的不确定性，并奖励提供储备以减轻不确定性的发电机。新的定价机制可以提供有效的价格信号，以激励日期管理市场的不确定性管理。最后，通过对PJM 5-BUS系统和IEEE 118-BUS系统的众多模拟来验证所提出方法的有效性。
Large-scale integration of renewable energy sources (RES) brings huge challenges to the power system. A cost-effective reserve deployment and uncertainty pricing mechanism are critical to deal with the uncertainty and variability of RES. To this end, this paper proposes a novel locational marginal pricing mechanism in day-ahead market for managing uncertainties from RES. Firstly, an improved multi-ellipsoidal uncertainty set (IMEUS) considering the temporal correlation and conditional correlation of wind power forecast is formulated to better capture the uncertainty of wind power. The dimension of each ellipsoidal subset is optimized based on a comprehensive evaluation index to reduce the invalid region without large loss of modeling accuracy, so as to reduce the conservatism. Then, an IMEUS-based robust unit commitment (RUC) model and a robust economic dispatch (RED) model are established for the day-ahead market clearing. Both the reserve cost and ramping constraints are considered in the overall dispatch process. Furthermore, based on the Langrangian function of the RED model, a new locational marginal pricing mechanism is developed. The uncertainty locational marginal price (ULMP) is introduced to charge the RES for its uncertainties and reward the generators who provide reserve to mitigate uncertainties. The new pricing mechanism can provide effective price signals to incentivize the uncertainty management in the day-ahead market. Finally, the effectiveness of the proposed methods is verified via numerous simulations on the PJM 5-bus system and IEEE 118-bus system.
