A wind-storage joint scheduling method for active distribution network

Abstract

The invention discloses a wind-storage-combined scheduling method of an active distribution network. The method comprises the following steps: utilizing a maximum-minimum wind power value tracking method to carry out battery capacity determination of a wind-storage-combined system, and determining the final battery capacity; utilizing an Elman neural network to carry out ultra-short-term prediction of loads and wind power according to historical wind power data of a wind turbine, wherein the prediction is carried out once every 10 minutes; and carrying out wind-storage-combined optimization scheduling of the active distribution network under various conditions according to prediction results and limitation of the final battery capacity in the wind storage system to enable the wind-storage-combined system to participate in active distribution network scheduling with a certain penetration rate, and determining an extra-added generated power amount in a battery discharging phase according to the short-term prediction results. A capacity determination method of the wind-storage-combined system in the invention is simple and convenient, the obtained results can meet requirements of safe and economical operation of the active distribution network, the Elman neural network has functions of dynamic learning and state memory for the past, and thus the obtained ultra-short-term prediction results of the wind power are not much different from actual values.

Description

Technical field [0001] The invention relates to the technical field of power grid dispatching, in particular to a joint dispatching method of active power distribution network wind storage. Background technique [0002] The large number of distributed power sources connected to the grid and the continuous increase in their penetration rate have brought a series of problems to the power system operation planning. The operation and management of the traditional distribution network will not be able to meet the requirements of a large number of distributed power sources. In order to effectively control the impact of DG output characteristics on the distribution network, active distribution network technology has emerged. Among them, wind power, as the clean energy with the most commercial value at present, has received widespread attention, but its intermittent and random characteristics make it impossible to accurately predict the output of wind power plants, which in turn affects ...

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Problems solved by technology

However, this article also only considers the influence of active power, and does not consider the problems caused when part of the wind storage is out of operation

[0007] It can be seen that there are few existing methods for the joint scheduling of wind storage systems in active distribution networks that consider the economic benefits of active power and reactive power at the same time, and there is a lack of systematic research on the configuration and scheduling of wind storage systems in active distribution networks.

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