Multi-stage wind power accepted range calculating method based on unit combination and economic dispatching

Abstract

The invention discloses a multi-stage wind power accepted range calculating method based on unit combination and economic dispatching, comprising an annual planning stage, a monthly planning stage, and a current planning stage. A, in the annual planning stage, a mathematical model for solving the maximum wind power installed capacity which can be accepted by a region and the minimum wind power installed capacity which must be accessed to the region is established by using regional typical load curve data and based on an economic dispatching optimization method; B, in the monthly planning stage, a mathematical model for solving the maximum wind power which can be accepted by the region and the minimum wind power which must be accessed to the region is established by using monthly load prediction data and based on the economic dispatching optimization method; and C, in the current planning stage, a mathematical model for solving the maximum wind power which can be accepted by the region next day and the minimum wind power which must be accessed to the region next day is established by using recent load prediction data, recent wind power prediction data and a monthly thermal power unit start-stop optimization result and based on the economic dispatching optimization method.

Description

technical field [0001] The invention relates to a multi-stage wind power acceptance range calculation method based on unit combination and economic dispatch. Background technique [0002] With the increasingly severe energy and environmental problems, environmentally friendly renewable resources have gradually attracted attention. With its natural advantages such as low operating cost, less pollution, abundant reserves, and huge development potential, wind energy has been vigorously developed in recent years. Due to the inherent randomness and volatility of wind in nature, grid-connected wind power has the following disadvantages: [0003] 1) Strong uncertainty: that is, wind power output is difficult to predict accurately due to wind speed; [0004] 2) Anti-peaking characteristics: that is, the wind turbine output has a negative correlation with the system load, especially when the load level is low and the wind power output is high, it will cause great problems; [0005]...

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Problems solved by technology

[0005] 3) The output power of wind turbines depends on the wind speed. At present, the wind speed prediction level of wind farms is very limited, and its prediction error is generally about 25% to 40%. challenge

[0006] The adjustment ability of the existing energy structure is insufficient. In order to balance the fluctuation of the power grid, the economy of the system becomes worse. The wind problem is becoming more and more serious, therefore, it is very important to study the wind power acceptance capacity of the grid to improve the security and economy of the grid

[0007] In addition, there is no clear definition and standard calculation method for the capacity of the grid to accommodate wind power. For different fields, the factors considered in evaluating the capacity of wind power are different, which determines the different evaluation methods.

The traditional evaluation of grid capacity is usually from the perspective of wind power planning, considering factors such as operation mode and disturbance mode, and is used to determine the maximum installed capacity of wind power. This type of evaluation method is not suitable for short-term dispatching and operation; The analysis of the wind power capacity of the power grid is analyzed by establishing an algebraic model, but it is difficult to guarantee the validity and practicability of the evaluation results

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