Spot price prediction method for electricity market and related equipment thereof
A power market and price forecasting technology, applied in forecasting, neural learning methods, electrical digital data processing, etc., can solve problems such as late start, influence, and abnormal real-time prices, and achieve the effect of avoiding limitations and improving accuracy
Pending Publication Date: 2022-08-09
华润电力(广东)销售有限公司
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[0003] Due to the relatively late start of domestic spot market transactions, relevant research and historical data are relatively scarce, and the existing methods mainly use a single model, such as using the least squares method to perform polynomial fitting on the price prediction model, and obtain the market price with a polynomial degree of 4. Forecasting model and real-time price forecasting model, however, this method is easily affected by abnormal real-time prices, which makes the forecasting model inaccurate and has certain limitations
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[0095] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.
[0096] With the continuous expansion of power spot pilots, the level of spot price has become a key factor for power generators and electricity sales companies to formulate optimal trading strategies. Therefore, how to accurately predict the spot price is very important.
[0097]In the national electricity market, the embodiments of this application mainly illustrate the Guangdong electricity market. Therefore, it is not difficult to understand that t...
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The embodiment of the invention provides a spot price prediction method for an electricity market. The method is used for solving the problem of accuracy of electricity market prediction. The method provided by the embodiment of the invention comprises the following steps: acquiring sample data influencing the B-type bidding electric quantity of the electricity market; inputting the sample data into an initial BP neural network model to train the initial BP neural network model; the trained initial BP neural network model is disturbed, and the disturbed initial BP neural network model is trained, so that an intermediate BP neural network model can be obtained; if the intermediate BP neural network model satisfies a preset condition, determining the intermediate BP neural network model as a target BP neural network model; and when the target BP neural network model is the optimal BP neural network model, selecting the target BP neural network model for prediction so as to output a prediction result.
Description
technical field [0001] The embodiments of the present application relate to problems in the technical field of spot price prediction in the electricity spot market, and in particular, to a method for spot price prediction in the electricity market. Background technique [0002] With the continuous expansion of power spot pilots, the level of spot prices has become a key factor for power generators and electricity sales companies to formulate optimal trading strategies. Therefore, how to accurately predict spot prices is very important. Under the model of "medium and long-term, supplemented by spot" in the Guangdong power market, the accuracy of future spot price forecasts affects the management strategies of contract positions of power generators and electricity sales companies, and ultimately affects their respective profits. [0003] Due to the late start of domestic spot market transactions, related research and historical data are relatively scarce, and the existing meth...
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IPC IPC(8): G06Q10/04G06Q30/02G06Q50/06G06F16/242G06N3/02G06N3/08G06F17/10
CPCG06Q10/04G06Q30/0283G06Q50/06G06F16/242G06N3/02G06N3/08G06F17/10Y04S50/14
Inventor 贺小平滕志毅许志荣常作攀李良谭凌云王欣玮陈雄汝张皓
Owner 华润电力(广东)销售有限公司