Long Period Continuous Operation Data Sample Generation Method for Power Grid

In recent years, artificial intelligence technology has provided new ideas for solving the problems related to power system operation and control, and the new power system has also provided new scenarios for the application of artificial intelligence technology. Artificial intelligence training needs massive data samples of power grid dispatching and operation, and the quality of training samples is an important factor to determine the training effect. At present, the standard examples often do not contain operation data information, and the actual power grid operation data contains less extreme scenarios, which is difficult to be directly used for artificial intelligence training. This paper proposes a method to generate long-term continuous operation data samples for power grid, and constructs data samples that meet the actual power grid operation characteristics to support artificial intelligence training in multiple scenarios.