Cell-growth-model-based space load prediction method

A spatial load forecasting and cellular technology, applied in forecasting, computational models, biological models, etc., can solve problems such as lack of consideration of the interaction of plots, incomplete plot data, and inaccurate load forecasting.

Active Publication Date: 2015-11-18
RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER +1
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Problems solved by technology

[0005] In order to overcome the deficiencies in the above-mentioned prior art, the present invention provides a space load prediction method based on the cell growth model, which comprehensively considers the development mode of the load from multiple aspects, multiple angles, and multiple factors, and predicts the future space of the planning area. The load distribution value and its development trend can be predicted to a certain extent, which solves the problem of incomplete plot data and lack of consideration of the mutual influence of each plot, which leads to inaccurate load forecasting.

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  • Cell-growth-model-based space load prediction method
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  • Cell-growth-model-based space load prediction method

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[0080] In order to clearly illustrate the technical features of this solution, the present invention will be described in detail below through specific implementation modes and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and / or letters in different instances. This repetition is for the purpose of simplicity and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted herein to avoid unnecessarily limiting the...

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Abstract

Disclosed in the invention is a cell-growth-model-based space load prediction method. The method comprises: establishing a cell growth model; selecting and setting a cell sample zone in a space-time database; defining power load cells; establishing a conversion rule of the power load cells; establishing a power load cell sample sub database; obtaining association attribute data of a center power load cell and neighboring cells; determining an activity value of the center power load cell according to the load attribute data; determining a load value of the center power load cell based on the conversion rule of the power load cell and storing cell data that may be changed within a planning period into an optimized cell data table; and carrying out space load prediction on all power load cells and outputting a space load prediction value. According to the invention, a problem that load prediction is not accurate because phenomena that the plot data are not complete and all plots are influenced mutually are not considered can be solved.

Description

technical field [0001] The invention relates to a power load forecasting method, in particular to a space load forecasting method based on a cell growth model. Background technique [0002] The results of load forecasting have guiding significance for the determination of power network and power supply point, and are an important basis for power grid planning, as well as essential basic data for urban planning and economic development. At present, the methods commonly used in medium and long-term load forecasting mainly include S-curve method, elastic coefficient method, gray system method, fuzzy algorithm, etc., and comprehensive methods based on the above methods. These methods generally can only predict the total load but cannot determine the load. specific distribution. In power distribution system planning, load forecasting not only requires the ability to predict the total amount of load, but also requires location information that can predict future load growth, beca...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/00
CPCY04S10/50
Inventor 冯亮冯旭郑志杰吴奎华杨波梁荣杨慎全
Owner RES INST OF ECONOMICS & TECH STATE GRID SHANDONG ELECTRIC POWER
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