A data-driven approach to energy storage capacity planning for wind farms

Abstract

The invention provides a data-driven wind farm energy storage capacity planning method, which relates to the technical field of new energy power generation planning. First, collect relevant data such as wind power, energy storage devices, wind curtailment upper limit, transmission line capacity, etc., and then establish a wind farm operation optimization model with energy storage and a wind farm energy storage capacity optimization model based on distribution robust optimization. The energy storage capacity optimization model is converted into the form of mixed integer linear programming, and finally solved by a mathematical programming solver. The wind farm energy storage capacity planning method based on distribution robust optimization provided by the invention can make full use of the historical data of wind power, consider the error of the approximate probability distribution of the historical data, take into account the economy and conservatism, and is easy to program to find the optimal solution.

Description

technical field [0001] The invention relates to a wind farm energy storage capacity planning method, in particular to a data-driven wind farm energy storage capacity planning method, and belongs to the technical field of new energy power generation planning. Background technique [0002] Wind power is a clean and renewable power generation method that has developed rapidly in recent years. However, due to the intermittent and randomness of the output power of wind power generation, there is often a mismatch between wind power, load demand and power system status, which makes wind power unable to be fully absorbed by the power system, resulting in wind curtailment. Installing a suitable energy storage device in a wind farm can transfer the wind energy that cannot be absorbed in time, which is beneficial to reduce the intermittency and randomness of wind power generation, reduce the wind curtailment rate, and reduce the reserve capacity required by the power system. The large...

AI Technical Summary

Problems solved by technology

However, the value range of wind power is large, usually including the case of no power generation, which makes the results of robust optimization very conservative

[0004] Distribution robust optimization is an emerging mathematical tool. This method assumes that some information about the probability distribution of random quantities is known, that is, the probability distribution is in a known set, but the exact probability distribution is unknown.

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