Medium-and-long-term power generation optimization method and system for hydroelectric generating set

Abstract

The invention discloses a medium-and-long-term power generation optimization method and system for a hydroelectric generating set. The method comprises the following steps: obtaining historical data of a hydropower station; according to the historical data, fitting the on-dam water level-flow coefficient, the under-dam water level-flow coefficient and the comprehensive efficiency coefficient, and obtaining a hydroelectric generating set output model without the reservoir water volume; predicting the warehousing flow of the next year according to the historical warehousing flow data by adopting a clustering segmentation ARIMA method; superposing the difference value between the historical storage flow and the historical power generation flow into the storage flow of the next year to obtain a predicted power generation flow; and substituting the comprehensive efficiency, the water purification head and the predicted power generation flow into a hydroelectric generating set output model which does not contain the reservoir water volume, calculating to obtain medium-and-long-term predicted output of the hydroelectric generating set, and optimizing medium-and-long-term power generation of the hydroelectric generating set according to the medium-and-long-term predicted output of the hydroelectric generating set. According to the method, the reliability of the multi-energy complementary scene in which the hydroelectric generating set participates can be planned by combining the obtained predicted output value with a related updating strategy.

Description

technical field [0001] The invention belongs to the technical field of power plant planning, and in particular relates to a medium- and long-term power generation optimization method and system for a hydroelectric unit. Background technique [0002] The hydropower station uses the potential energy generated by the height difference between the forebay water level (the water level above the dam) and the tail water level (the water level below the dam) to drive the turbine to rotate, and the turbine drives the generator to generate electricity to complete the conversion from mechanical energy to electrical energy. Hydropower has good regulation performance, and as an adjustable energy source, it is increasingly involved in the application field of multi-energy complementary power generation. Modeling of hydropower units is an important link in the multi-energy complementary joint operation system. Existing documents and patents have established detailed models of short-term d...

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Problems solved by technology

Existing documents and patents have established detailed models of short-term dispatching hydroelectric units. Few documents have modeled the mid- and long-term output of hydroelectric units. A few documents have established a constant-efficiency simplified hydroelectric unit model that ignores the influence of unit water head in long-term dispatching problems. The simplified model is not accurate enough, and it is difficult to consider the time-series characteristics of the natural inflow of the reservoir

[0003] In addition, most of the existing hydropower unit models have introduced the variable of reservoir water volume. In actual engineering, the reservoir water volume is difficult to measure. In actual engineering, the water level data and water head data of the reservoir can be obtained and easily measured.

[0004] The existing short-term scheduling model of hydropower units does not conform to the actual production. From the survey of hydropower stations, it is difficult to measure the data of reservoir water volume in hydropower stations, and the fitting coefficient is difficult to obtain in actual production.

Because the shape of the reservoir is generally irregular, sometimes stretching tens of square kilometers, the water storage capacity of such a large reservoir cannot be measured

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