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A Determination Method for the Optimal Operation of Controllable Generators in Micro Grids That Copes with Unstable Outputs of Renewable Energy Generation
Author(s) -
Takano Hirotaka,
Zhang Peng,
Murata Junichi,
Hashiguchi Takuhei,
Goda Tadahiro,
Iizaka Tatsuya,
Nakanishi Yosuke
Publication year - 2015
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.22687
Subject(s) - renewable energy , grid , mathematical optimization , distributed generation , photovoltaic system , computer science , tabu search , engineering , reliability engineering , electrical engineering , mathematics , geometry
SUMMARY Micro grids are expected to be one of the most realistic energy systems for efficient use of renewable energy sources with few adverse effects on the main electric power grids. However, it is difficult to maintain the supply‐and‐demand balance because distributed renewable energy generation units (DREGs), such as photovoltaic generation systems and wind turbine generation systems, generate a significant portion of electrical energy in the micro grids. Therefore, an operation planning method is needed considering the uncertainty in weather prediction in order to ensure stable micro grid operations. This paper presents an optimization method for operation plans of controllable generators in micro grids that copes with the uncertainty of DREG outputs. In the proposed method, the optimal operation plans are determined by, depending on the problem conditions, either an enumeration method or Tabu Search with preprocessing. Numerical simulations were carried out for a micro grid model in order to verify the usefulness of the proposed method. In the simulations, the daily operation plan and the modified half‐hourly one were determined by the proposed method. As a result, we could obtain the optimal plans which had enough reserve margins for coping with the fluctuations caused by DREGs and demand.