Open AccessA bi‐level approach to load restoration strategy considering variant length of time steps
Author(s) -
Sun Lei,
Yang Zhichao,
Li Mingming,
Ding Ming,
Liang Bomiao
Publication year - 2022
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12307
Subject(s) - correctness , mathematical optimization , computer science , linear programming , integer programming , upper and lower bounds , control theory (sociology) , electric power system , transmission line , pickup , transmission (telecommunications) , power (physics) , scheme (mathematics) , energy storage , energy (signal processing) , algorithm , mathematics , mathematical analysis , telecommunications , physics , statistics , control (management) , quantum mechanics , artificial intelligence , image (mathematics)
A bi‐level load restoration optimisation strategy is proposed for the transmission system with wind farm‐energy storage combined systems (WESs), taking the variant length of time steps into account. The upper level model is proposed to maximise weighted restored loads, and formulated as a mixed‐integer linear programming model. After solving the upper model, the optimal load pickup and transmission line restoration scheme can be obtained and delivered to the lower level model. The lower level model adopts a non‐linear model to minimise the length of the current time step, which is delivered to the upper lever model. By iteratively solving the upper and lower level models, the optimal load pickup and transmission line restoration scheme as well as the optimal length of current time step can be obtained. To minimise the gap between the scheduled generation of the WES and its actual power generation, a real‐time energy storage (ES) dispatch strategy is proposed taking maximum charging‐discharging cycles of the ES into account. The entire load restoration strategy can be obtained by iteratively solving the proposed model with updated operational conditions of power systems. Finally, two test systems are employed to verify the validity and correctness of the proposed model.