4.5 Article

Resilience-directional robust power dispatching of microgrids under meteorological disasters

期刊

IET RENEWABLE POWER GENERATION
卷 13, 期 12, 页码 2084-2093

出版社

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-rpg.2018.6223

关键词

scheduling; distributed power generation; disasters; integer programming; stochastic programming; linear programming; minimisation; meteorological disasters; novel resilience-directional robust dispatch model; islanded AC; DC hybrid microgrid; HMG; inherent uncertainties; source-load power; meteorological disaster strikes; wind turbine; PV; bidirectional converter; double uncertainties; output constraints; RRD model manifests; min-max-min tri-layer problem; mixed-integer recourse variables; nested column; -constraint generation algorithm; mixed-integer linear programming model; MILP problem; minimal operating cost; establishing robust scheduling plans; worst disaster scenario

资金

  1. National Natural Science Foundation of China [U1866208]
  2. Scientific Research Foundation of Graduate School of Southeast University [YBPY1879]

向作者/读者索取更多资源

This study proposes a novel resilience-directional robust dispatch (RRD) model for an islanded AC/DC hybrid microgrid (HMG). The inherent uncertainties on the source-load power and the occurrence of meteorological disasters are considered in this model. When a meteorological disaster strikes, the wind turbine (WT), photovoltaic (PV), and bidirectional converter of the HMG should be offline to ensure the stability of the HMG and the safety of these sensitive units. When affected by such double uncertainties, the output constraints of the WT, PV and load are bilinear but are linearised via big-M approach. The proposed RRD model manifests as a min-max-min tri-layer problem with mixed-integer recourse variables, which is difficult to solve directly. Therefore, a nested column-and-constraint generation algorithm is adopted to convert the tri-layer problem to a two-stage mixed-integer linear programming (MILP) model. The MILP problem is addressed by the commercial solver, thereby obtaining the minimal operating cost and establishing robust scheduling plans with the worst disaster scenario. The effectiveness and rationality of the proposed RRD model and its solution methodology are verified in numerical tests.

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