Short-term power generation output prediction method for distributed small hydropower station

Abstract

The invention relates to a short-term power generation output prediction method for a distributed small hydropower station, and the method comprises the steps: carrying out the basin hydrological law analysis according to the historical electric quantity information and rainfall information of the small hydropower station, employing a distributed frame structure, and employing a large-scale data mining calculation method, and building a rainfall and power station electric quantity incidence relation calibration parameter; predicting the electric quantity of the power station in the future three days by adopting a chaos time sequence method through a future drainage basin rainfall prediction sequence, performing day-by-day process decomposition on the daily electric quantity by utilizing a similarity machine learning discrimination method, and finally obtaining an output process prediction sequence of the small hydropower station in the future three days. Therefore, the internal relation between the rainfall and the electric quantity of the small hydropower station without water regimen forecasting is accurately described, the daily electric quantity process is decomposed by using a recurrent neural network and similar data mining, and the daily output process forecasting of the small hydropower station without water regimen forecasting is realized. And the planned output compilation method of the water-regimen-free forecasting power station is provided for refined small hydropower dispatching.

Description

technical field [0001] The invention relates to the technical field of power generation capacity prediction, in particular to a method for predicting short-term power generation output of distributed small hydropower stations. Background technique [0002] With the continuous development of the social economy, the electricity load of residents and enterprises has increased rapidly, and the imbalance of power generation and consumption between regions has become more prominent. For the peak period of electricity load, it is necessary to make full use of all available resources to meet the peak load demand. With the refined development of power dispatching, small hydropower has the characteristics of small installed capacity and large total capacity, and the demand for arranging its peak has gradually become prominent. However, due to the low construction standards of small hydropower, most of them do not have water regime monitoring stations. Conventional power stations The p...

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Problems solved by technology

With the refined development of power dispatching, small hydropower has the characteristics of small installed capacity and large total capacity, and the demand for arranging its peak has gradually become prominent. However, due to the low construction standards of small hydropower, most of them do not have water regime monitoring stations. Conventional power stations The power forecasting method fails in this case, so it is necessary to carry out anhydrous forecasting and forecasting of the power generation output of small hydropower stations to meet the needs of small hydropower station output planning and refined power generation

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