Wind power station energy storage capacity control method based on particle swarm optimization

A particle swarm algorithm and energy storage capacity technology, which is applied in the field of wind farm energy storage capacity control, can solve problems such as non-optimal state, reduced wind energy utilization rate, and insufficient consideration of the adaptability between energy storage and grid dispatching decisions.

Inactive Publication Date: 2012-09-12
SHANDONG UNIV
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Problems solved by technology

[0006] The above studies either guarantee a certain value of wind power for a long period of time, or have large fluctuations in a single time window, and have not fully considered the adaptability between energy storage and grid dispatching decisions, which makes wind farms under high wind power When the curtailed

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  • Wind power station energy storage capacity control method based on particle swarm optimization
  • Wind power station energy storage capacity control method based on particle swarm optimization
  • Wind power station energy storage capacity control method based on particle swarm optimization

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Embodiment Construction

[0061] The present invention will be further described below in conjunction with accompanying drawings and examples of implementation.

[0062] figure 1 In the above, the energy storage strategy of the wind storage power generation system is: when the wind power generation power is greater than the reference value of the output power period, the battery is charged. If the battery reaches its maximum capacity C bat.N , the battery will no longer be charged at the next moment. At this time, the excess wind power will be unloaded through the unloader. This energy is called Loss of Wind Energy (LOWE) of the wind farm. When the wind power generation power is less than the reference value of the output power period, the storage battery is discharged. If the battery power reaches its minimum capacity C batmin , the battery will no longer be discharged at the next moment. At this time, part of the reference output power will not be satisfied. This part of the unsatisfied electric e...

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Abstract

The invention relates to a wind power station energy storage capacity control method based on particle swarm optimization. The wind power station energy storage capacity control method includes the steps of taking the interval reference value of the wind power station output power which is adapted to the dispatching cycle of a power grid as a foundation, taking the influence of the wind-abandoning energy of a wind power station and the lost energy of an energy storage system into consideration, taking the lowest costs of the energy storage investment and a wind and power operation system as target functions, establishing a policy model for energy storage capacity optimizing based on a storage battery energy storage system, and then applying the improved particle swarm optimization to solve the functions. By the aid of the wind power station energy storage capacity control method based on the particle swarm optimization, the wind power which is output under effect of the energy storage system can be output smoothly at intervals, so that effective connection between the energy storage system and the existing dispatching operation manner can be realized, and the best economic benefit can be achieved simultaneously.

Description

technical field [0001] The invention relates to a method for controlling the energy storage capacity of a wind farm based on a particle swarm algorithm. Background technique [0002] With the continuous expansion of the scale of wind power, while it transmits a large amount of clean electric energy to the grid, its impact on the dispatching and operation of the power system is also deepening. The reason is that the intermittence and randomness of wind energy cause random fluctuations in wind power, and it is difficult to predict accurately. Therefore, there is an urgent practical need to study the power distribution characteristics of grid-connected wind power, use energy storage methods to stabilize wind power fluctuations, and achieve stable and reliable wind power dispatching. [0003] The distribution characteristics of wind energy have significant time periodicity, and its typical fluctuation cycles are quarterly and annual. Correspondingly, the wind power also has th...

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Application Information

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IPC IPC(8): H02J3/28G06N3/00
CPCY02E10/76Y02E70/30
Inventor 王成福梁军冯江霞
Owner SHANDONG UNIV
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