Wind Power Prediction and Dispatch Strategy Considering Wind-Load Similarity in Strong Wind Scenarios

In strong wind scenarios, thermal power units often work in deep peak shaving state when a large amount of wind power is integrated into the grid, and their output fluctuation cannot be too large to meet the requirements of unit stability. This paper proposes a wind power prediction and optimal dispatch model considering wind-load similarity. Firstly, the meteorological data is divided into multiple subsets to identify the strong wind meteorological scenarios, then a wind power prediction model that adapts to different scenarios of wind power characteristics is constructed, which improves the prediction accuracy; following this, the influence of wind power-load similarity on unit dispatch is analyzed, and the goal of maximizing the wind-load similarity is set as the objective, and the wind power is trimmed by genetic algorithm, and then a penalty term for suppressing the fluctuation of thermal power units is introduced in the objective function of MPC optimization dispatch. Finally, this paper uses the wind farm and load data of Xuzhou, China to verify the proposed model. The simulation results show that the average output adjustment, which reflects the fluctuation of thermal power units, is reduced by 47.52% in natural gas units and by 35.66% on coal-fired units.