Unit Combination Scheduling Method Considering System Frequency Dynamic Constraints under High Wind Power Share

Qun Li, Qiang Li and Chenggen Wang ()
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Qun Li: State Grid Jiangsu Electric Power Co., Ltd., Research Institute, Nanjing 211103, China
Qiang Li: State Grid Jiangsu Electric Power Co., Ltd., Research Institute, Nanjing 211103, China
Chenggen Wang: State Grid Jiangsu Electric Power Co., Ltd., Research Institute, Nanjing 211103, China

Sustainability, 2023, vol. 15, issue 15, 1-20

Abstract: Power systems with a high wind power share are characterized by low rotational inertia and weak frequency regulation, which can easily lead to frequency safety problems. Providing virtual inertia for large-scale wind turbines to participate in frequency regulation is a solution, but virtual inertia is related to wind power output prediction. Due to wind power prediction errors, the system inertia is reduced and there is even a risk of instability. In this regard, this article proposes a unit commitment model that takes into account the constraints of sharp changes in frequency caused by wind power prediction errors. First, the expressions of the equivalent inertia, adjustment coefficient, and other frequency influence parameters of the frequency aggregation model for a high proportion wind power system are derived, revealing the mechanism of the influence of wind power prediction power and synchronous machine start stop status on the frequency modulation characteristics of the system. Second, the time domain expression of the system frequency after the disturbance is calculated by the segment linearization method, and the linear expressions of “frequency drop speed and frequency nadir” constraints are derived to meet the demand of frequency regulation in each stage of the system. Finally, a two-stage robust optimization model based on a wind power fuzzy set is constructed by combining the effects of wind power errors on power fluctuation and frequency regulation capability. The proposed model is solved through affine decision rules to reduce its complexity. The simulation results show that the proposed model and method can effectively improve the frequency response characteristics and increase the operational reliability of high-share wind power systems.

Keywords: frequency safety; power system inertia; wind power forecasting error; two-stage robust optimization; affine decision rule (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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