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Stochastic Network-Constrained Unit Commitment to Determine Flexible Ramp Reserve for Handling Wind Power and Demand Uncertainties

机译:随机网络约束单位承诺,以确定柔性坡道储备,用于处理风力和需求不确定性

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The flexible ramp reserve of dispatchable generators is a key effective means to compensate the fast fluctuation of wind power generators and the forecast error of demand. This article proposes a stochastic network-constrained unit commitment (NCUC) model to determine, on daily horizon, the optimal schedule of generation units along with the required flexible ramp and spinning reserves under uncertainties of wind power and demand. Point estimate method (PEM) is utilized to reduce the number of scenarios that model wind power and demand uncertainties. In addition to PEM scenarios, some worst-case scenarios based on regional wind and demand variations are defined and incorporated in the proposed model. The NCUC model includes for these scenarios various technical constraints of generation units and operation constraints of the network. To ensure computational tractability of NCUC model, the ac network operation constraints are linearized. The proposed mixed integer linear programming NCUC model is tested using the IEEE 118-bus system. The obtained results show better units scheduling than the conventional (deterministic) NCUC model.
机译:可调度发电机的柔性斜坡储备是补偿风力发电机的快速波动和需求误差的关键有效手段。本文提出了一个随机网络受限的单位承诺(NCUC)模型,以确定日常地平线,发电单位的最佳时间表以及所需的柔性斜坡和纺纱储备在风力力量和需求的不确定下。点估计方法(PEM)用于减少模型风电和需求不确定性的场景的数量。除了PEM情景外,基于区域风和需求变化的一些最坏情况的情况是定义和纳入所提出的模型。 NCUC模型包括用于这些场景的各种技术约束和网络的操作约束。为确保NCUC模型的计算易易性,AC网络操作约束是线性化的。使用IEEE 118总线系统测试所提出的混合整数线性编程NCUC模型。所获得的结果显示比传统(确定性)Ncuc模型更好的单位调度。

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