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Short-term electrical load on-line predicting method based on self-adaptation enhancing algorithm

A short-term power load, adaptive enhancement technology, applied in image enhancement, computing, genetic model and other directions, can solve the problems of difficult online prediction and the inability to accurately predict the mutation point model.

Inactive Publication Date: 2014-05-14
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

However, it is still impossible to accurately predict some regular mutation point models, and it is not easy to make online predictions

Method used

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  • Short-term electrical load on-line predicting method based on self-adaptation enhancing algorithm
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  • Short-term electrical load on-line predicting method based on self-adaptation enhancing algorithm

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Embodiment Construction

[0062] The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

[0063] figure 1 It is a flow chart of short-term power load online forecasting method based on adaptive enhancement algorithm. Such as figure 1 As shown, the short-term power load online forecasting method based on the adaptive enhancement algorithm provided by the present invention includes:

[0064] Step 1: Select M factors that affect meteorological data, and extract the measured value of each factor that affects meteorological data in the past L days to form a meteorological data matrix S L×M ; Among them, M and L are set values.

[0065] According to the impact of meteorological factors on the power load, select the local factors that affect the meteorological information. For example, M factors such as the h...

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Abstract

The invention discloses a short-term electrical load on-line predicting method based on the self-adaptation enhancing algorithm in the technical field of electrical load predicting. The short-term electrical load on-line predicting method comprises the step of selecting M factors affecting meteorological data and extracting actual measurement values of factors affecting the meteorological data in past L days to form a meteorological data matrix SL*M, the step of extracting electrical load data of n time points of each day in the past L days to form an electrical load data matrix DL*n, the step of selecting m factors with maximum association with the electrical load data from the factors affecting the meteorological data, serving the m factors as valid constituents and forming a valid meteorological data matrix TL*m according to the actual measurement values of the valid constituents of the past L days, the step of solving a short-term electrical load predicting model according to the valid meteorological data matrix TL*m and the electrical load data matrix DL*n, and the step of carrying out electrical load prediction according to the short-term electrical load predicting model. According to the short-term electrical load on-line predicting method, the effect on the model predicting precision of data noise can be effectively eliminated, and a more accurate and stable predicting result can be obtained.

Description

technical field [0001] The invention belongs to the technical field of power load forecasting, and in particular relates to a short-term power load online forecasting method based on an adaptive enhancement algorithm. Background technique [0002] Short-term power load online forecasting is one of the important components of power load forecasting and the basis for intelligent control of power grids. The improvement of online load forecasting ability is not only conducive to improving the safety of the power grid and guiding the maintenance of the power grid, but also can effectively reduce the cost of power generation, improve the economic benefits of the power system, and raise the production and living standards of the people to a new level. [0003] As the main basis for formulating power generation plan, power transmission scheme and grid construction, power load forecasting can estimate the power load in the time range of minutes to years in the future. Short-term loa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/12
Inventor 许刚谈元鹏马爽
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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