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Auto recommending method of urban power load forecasting module based on associative rules

A prediction model and power load technology, which is applied in the field of automatic recommendation of urban power load prediction models based on association rules, can solve the problems of urban power load calculation, models cannot be considered, etc., and achieve credible prediction results, strong credibility, guidance The effect of urban power grid planning

Inactive Publication Date: 2009-10-14
TIANJIN UNIV
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Problems solved by technology

Considering that there are many types of existing load forecasting models, and they all have their own applicable conditions, for example, some models cannot consider the factors related to urban power load for calculation, and some models are not suitable for calculation when the urban load is saturated.

Method used

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  • Auto recommending method of urban power load forecasting module based on associative rules
  • Auto recommending method of urban power load forecasting module based on associative rules
  • Auto recommending method of urban power load forecasting module based on associative rules

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Embodiment Construction

[0020] The automatic recommendation method of the present invention will be described in detail below.

[0021] 1. Construction of historical case database

[0022] To recommend a suitable model, a historical database must first be established. The original data provided for the present invention come from the planning-related data of a large number of cities in China, mainly including: historical load data of previously predicted regions, data of related factors, such as the proportion of the secondary industry, city type , urban administrative functions, urban population development, urban load development status, forecast time limit, urban GDP development level, etc. In order to obtain accurate and reasonable conclusions, the applicability of the model is also analyzed as a continuous quantity. Here, the applicability of the model is set as a value between 0 and 1, where 0 is the lowest level of applicability, indicating that the model is not applicable ; 1 is the highest ...

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Abstract

The invention belongs to the load forecasting field of a power distribution system, relating to an auto recommending method of urban power load forecasting module based on associative rules. The method comprises the steps of: establishing a historical data base; carrying out data analysis and generalization; mining the associative rules; matching the rules; and obtaining model recommending conclusion by circulating the steps. The method not only can forecast the using condition of a model in an area to be measured, but also can conclude application rules of some models; by utilizing an inference method based on cases, the efficiency of model recommending is improved; and simultaneously the load forecasting efficiency is improved by combining certain expertise.

Description

technical field [0001] The invention belongs to the fields of medium and long-term load forecasting in power distribution system planning and short-term load forecasting in power distribution system operation, and relates to an automatic recommendation method for urban power load forecasting models. Background technique [0002] In urban power grid planning, the analysis and prediction of load and its development trend is a basic work, which determines the future city's demand for electricity and the power supply capacity of the future urban power grid, and plays an important role in the determination of urban power supply points and power generation planning. The guiding significance of , its accuracy directly affects the quality of power grid planning. Load forecasting has strong predictive characteristics and is affected by many factors, such as urban characteristics (such as urban centrality, urban functions, urban climate types, urban economic development levels, and ur...

Claims

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Application Information

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IPC IPC(8): G05B19/04G06N7/00G06Q50/00G06F17/00G06Q50/06
Inventor 肖峻耿芳葛少云罗凤章王笑一
Owner TIANJIN UNIV
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