Scheduling method considering incoming water correlation cascade hydropower stations

A cascade hydropower station group and scheduling method technology, applied in the direction of instruments, character and pattern recognition, data processing applications, etc., can solve the problems of ignoring the spatial correlation of natural water, etc.

Active Publication Date: 2016-07-27
SHANGHAI UNIVERSITY OF ELECTRIC POWER +1
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However, most of the current existing studies only consider the former relation

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  • Scheduling method considering incoming water correlation cascade hydropower stations
  • Scheduling method considering incoming water correlation cascade hydropower stations
  • Scheduling method considering incoming water correlation cascade hydropower stations

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[0079] The present invention proposes a scheduling method for cascade hydropower station groups considering the correlation of incoming water. The present invention first establishes a mathematical model for annual random scheduling of cascade hydropower stations. The model aims at maximizing the total power generation in the scheduling period while satisfying multiple requirements. The constraints of reservoirs and hydropower units, among which the hydro-hydropower conversion relationship of cascade hydropower units is as follows figure 1 As shown, in this model, except for the probability model of natural inflow, the others belong to the mixed formal linear programming model.

[0080] Secondly, sampling is carried out for correlated random natural inflow variables, such as figure 2 Shown.

[0081] In the established optimal scheduling model of the annual cascade hydropower station group, the natural inflow of each power station in each period is random and relevant. In order to ...

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Abstract

The invention relates to a scheduling method considering incoming water correlation cascade hydropower stations, the method is characterized in that, the method comprises the following steps: 1) a cascade hydropower stations random scheduled mathematical model is established; 2) random natural incoming water variables related to the cascade hydropower stations are sampled, and a sample matrix Rs is obtained; 3) a vector quantization algorithm is adopted to arrange all sample scenes in sample matrix Rs, various sample scenes are distributed to different scene kinds, and core scene sets of various scene kinds are acquired; 4) according to the cascade hydropower stations random scheduled mathematical model and core scene sets, a sensitivity analysis method is adopted to randomly schedule, schedule target objective function YRs of all sample scenes in the sample matrix Rs are acquired; 5) the schedule target objective function YRs are calculated to acquire probability statistics information of scheduling benefits. Compared with the technology in the prior art, the method provided by the invention has advantages of fast, reliability, high selectivity, considered incoming water correlation, wide application range and the like.

Description

Technical field [0001] The invention relates to a dispatching method for a cascade hydropower station group, in particular to a dispatching method for a cascade hydropower station group considering the correlation of incoming water. Background technique [0002] The main task of long-term optimal dispatching of hydropower stations is to optimize the annual hydropower generation and reservoir water storage conditions with the goal of maximizing system benefits while satisfying various operating constraints. However, affected by a variety of uncertain factors (randomness of incoming water), it is difficult to model and solve this problem. In order to simplify the influence of uncertain factors, some literatures only use the predicted average value of natural inflow as input, so as to establish a deterministic model for the long-term optimal scheduling of hydropower stations. This type of deterministic model is too simple to consider the impact of the randomness of natural incoming...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/06312G06Q10/0635G06Q50/06G06F18/22
Inventor 葛晓琳夏澍钟俊玲
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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