Hybrid Laplace distribution-based wind power fluctuation quantity probability distribution model building method

Abstract

The invention discloses a hybrid Laplace distribution-based wind power fluctuation quantity probability distribution model building method. The method comprises the steps of firstly, calculating a wind power fluctuation quantity sequence according to actually measured wind power data of a wind farm and a default time scale; building a hybrid Laplace distribution model; and determining a parameter of the hybrid Laplace distribution model according to the wind power fluctuation quantity sequence, thereby obtaining a wind power probability distribution model. By the wind power probability distribution model obtained by the method, the wind power fluctuation characteristics can be accurately described; especially, the accuracy of heavy-tailed characteristic description of wind power fluctuation distribution is improved; and aiming at the description problem of wind power fluctuation of different temporal and spatial scale levels, the model can also reach the satisfactory accuracy.

Description

technical field [0001] The invention belongs to the technical field of wind power fluctuation characteristic analysis, and more specifically relates to a method for establishing a probability distribution model of wind power fluctuation based on mixed Laplace distribution. Background technique [0002] With the rapid development of new energy power generation technology, the demand for large-scale wind power grid connection has further increased, and the volatility and intermittency of wind power not only affect the power quality, but also increase the difficulty of grid planning and scheduling, and also affect the security and stability of the grid. operation poses a potential risk. Minute-scale fluctuations affect the control performance of the AGC of the power system; hour-scale fluctuations affect the real-time scheduling of the power system within a day; daily fluctuations affect the arrangement of peak-shaving methods of the power system; year-to-month fluctuations aff...

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Problems solved by technology

[0004] Due to the strong randomness of wind power changes, the fluctuation laws of wind power vary greatly on different temporal and spatial scales, and it is difficult to accurately describe the fluctuation characteristics of wind power with a time series analysis method on a single temporal and spatial scale.

The use of non-parametric estimation methods to describe the fluctuation characteristics of wind power often requires a large amount of sample data, and the existing data have confirmed that the probability distribution of wind power fluctuations presents a clear regularity, so the non-parametric estimation method is not the optimal solution

The probability distribution of wind power fluctuations presents a strong heavy-tailed characteristic. For parametric estimation methods, traditional distribution models are difficult to accurately reflect the peak probability of wind power fluctuations near the mean value

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