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Flexibility-Enhanced Continuous-Time Scheduling of Power System Under Wind Uncertainties
IEEE Transactions on Sustainable Energy ( IF 8.8 ) Pub Date : 2021-06-16 , DOI: 10.1109/tste.2021.3089696
Bo Zhou , Jiakun Fang , Xiaomeng Ai , Wei Yao , Jinyu Wen

Flexibility helps accommodate uncertainties from the increasing renewables, such as wind power generation (WPG), but limited to scheduling methods, flexibility potentials of the power system have not been fully realized. This paper proposes the mathematical formulation and novel transformation for flexibility-enhanced continuous-time stochastic scheduling (FE-CTSS) of the power system under wind uncertainties. The Bernstein polynomial (BP) spline-based solution space transformation (SST) for solving continuous-time (CT) scheduling is revisited and the potential capacity and ramping flexibility, which are lost during the SST from function space to algebraic space, are then exposed for the first time. Developed from De Casteljau's algorithm (DCA), the enhancement matrix is derived to tighten the convex hull property and the enhanced SST is proposed to alleviate the feasible region narrowing to activate the potential flexibility in FE-CTSS. Case studies in the modified 6-bus system and the IEEE 118-bus system demonstrate the effectiveness and the promising role of FE-CTSS in the future high-renewable-penetrated and high-flexibility-required power system.

中文翻译:

风不确定性下电力系统灵活性增强的连续时间调度

灵活性有助于适应风力发电 (WPG) 等日益增长的可再生能源带来的不确定性,但仅限于调度方法,电力系统的灵活性潜力尚未完全实现。本文提出了风力不确定性下电力系统灵活性增强连续时间随机调度(FE-CTSS)的数学公式和新变换。重新审视了用于解决连续时间 (CT) 调度的伯恩斯坦多项式 (BP) 基于样条的解空间变换 (SST),然后揭示了在 SST 从函数空间到代数空间的过程中丢失的潜在容量和斜坡灵活性首次。从 De Casteljau 算法 (DCA) 发展而来,推导出增强矩阵以收紧凸包特性,并提出增强 SST 以减轻可行区域变窄以激活 FE-CTSS 中的潜在灵活性。改进后的 6 总线系统和 IEEE 118 总线系统的案例研究证明了 FE-CTSS 在未来高可再生渗透和高灵活性要求的电力系统中的有效性和前景。
更新日期:2021-06-16
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