Small hydropower station power generation capacity predicating method combining coupling partial mutual information and CFS ensemble forecast

Abstract

The invention relates to the field of hydropower station optimization and dispatching, in particular to a small hydropower station power generation capacity predicating method combining coupling partial mutual information and CFS ensemble forecast. The method includes the steps that firstly, a partial mutual information method is adopted for analyzing daily electric quantity data and meteorological data of existing small local hydropower stations, factors remarkably affecting the small hydropower station power generation capacity are screened out, the selected factors serve as model input data, an improved three-layer BP neural network prediction model is established, the optimal hidden layer node number of a network is determined according to a trail method, finally, long time sequence meteorological data of a corresponding region are acquired through CFS ensemble forecast, and the meteorological data are combined with the factors to serve as neutral network model input, so that the long-term small hydropower station power generation capacity is predicated. The method has the advantages that the small hydropower station power generation capacity can be effectively predicated and the good reference and basis are provided for the region enriched with the small hydropower stations.

Description

technical field [0001] The invention relates to the field of optimal scheduling and operation of hydropower, in particular to a small hydropower generation capacity prediction method coupled with partial mutual information and CFS ensemble prediction. technical background [0002] my country is rich in hydropower energy. Among them, the exploitable amount of small hydropower resources, which is a clean and renewable energy that is prioritized in the dispatch of national energy-saving power generation, ranks first in the world. With the development of energy-saving power generation dispatching work, the construction and development of small hydropower has been rapidly promoted. However, due to the lack of effective coordination measures, it is impossible to accurately predict the power generation capacity of small hydropower in different periods, resulting in the occupation of limited transmission channel resources by small hydropower and other power sources, leading to a mor...

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Problems solved by technology

However, due to the lack of effective coordination measures, it is impossible to accurately predict the power generation capacity of small hydropower in different periods, resulting in the occupation of limited transmission channel resources by small hydropower and other power sources, leading to a more serious phenomenon of large-scale power generation and water abandonment, which not only causes clean Energy waste seriously restricts the performance of small hydropower energy saving and emission reduction benefits, and seriously threatens the safe and stable operation of regional power grids, especially in the southwest region where small hydropower is abundant. In order for the power dispatching department to coordinate and optimize the dispatch of various power sources in the region, so as to improve the utilization rate of clean energy such as small hydropower

However, due to the fact that small hydropower stations are mostly located in small watersheds in remote mountainous areas, the communication conditions and hardware facilities are poor, and there is a lack of corresponding hydrological data and meteorological observation data such as precipitation and temperature. Power generation and other data are very limited, resulting in the lack of hydrological, meteorological, power generation and other data of small hydropower in many areas, which brings difficulties to small hydropower generation prediction, and it is difficult to use traditional methods to predict power generation capacity

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