Electric power big data-based main transformer peak load prediction method and data warehouse system

Abstract

The invention relates to the technical field of electric power systems, and in particular to an electric power big data-based main transformer peak load prediction method and a data warehouse system.The method comprises the following steps of: S1, carrying out statistics and analysis on history data of a power grid system, so as to establish the data warehouse system; S2, analyzing an extracted knowledge according to a decision purpose of a final user by adoption of a sequence mode analysis and clustering analysis data mining method, distinguishing most valuable information and submitting theinformation to the user; and S3, preprocessing main transformer peak load data through the arranged history data, and establishing a support vector machine-based load prediction model to predict thefuture main transformer load condition. According to the electric power big data-based main transformer peak load prediction method, the data warehouse system is established, the data mining method isestablished, and the support vector machine-based method is adopted to predict the main transformer load change condition, so that correct and reliable main transformer peak load prediction is realized, and systems are reasonably scheduled to ensure safe and economic operation.

Description

technical field [0001] The invention relates to the technical field of electric power systems, and more specifically, to a method for forecasting peak loads of main transformers based on electric power big data. Background technique [0002] With the commercialization and marketization of the power system, the accuracy of power load forecasting is of great significance to the safe and economical operation of the power system and the development of the national economy. The level of power load forecasting has become one of the notable signs of whether the management of a power enterprise is moving toward modernization. As an important basis in power trading, the power system load forecast value provides the necessary guidance for power companies to customize power quotations, operation plans, and grid planning. Its prediction accuracy will closely affect the economic benefits of power companies, especially in my country's power industry. Today, with the development of electri...

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Problems solved by technology

However, it is very difficult to achieve this point, because the influencing factors of power changes are very complex. This type of power load forecasting cannot be completed solely by relying on the data and information of the power system itself. In addition, environmental factors and power The relationship between them cannot be simply described by functions. In other words, they are a kind of fuzzy relationship. With the advancement and development of the power industry, the scale of the power system is getting larger and larger, which makes many political, Factors such as economy, society and even meteorology are also added to the background of forecasting, which greatly increases the difficulty of predicting the environment

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