Power load forecasting method based on big data technology, and research and application system based on method

Abstract

The present invention is a power load forecasting method based on big data technology and a research application system based on the method. With the support of big data technology, a variety of mature open source products are integrated to form a data source, data integration, data storage, Data calculation, data analysis, implementation of electrical load characteristic analysis and electrical load forecast analysis. The invention effectively improves the efficiency of mass data processing, and solves the limitations of traditional statistical analysis assumptions and judgments. It can scientifically and accurately predict the electricity demand of the future power, which is conducive to the peak-shaving and valley-filling and stable operation of the power grid, and provides decision-making support for the company's power grid planning, equipment maintenance, and power deployment.

Description

Technical field [0001] The invention belongs to the field of power information big data information mining and analysis, in particular to a power load forecasting method based on big data technology and a research application system based on the method. Background technique [0002] The existing power load forecasting methods are all based on traditional statistical analysis for data specification and data presentation. Traditional statistical analysis refers to the use of statistical methods and knowledge related to the analysis object, and the research from the combination of quantitative and qualitative activity. Statistical analysis can be divided into 5 steps: describe the nature of the data to be analyzed; study the data relationship of the basic group; create a model to summarize the connection between the data and the basic group; prove (or deny) the validity of the model; adopt the model To predict future trends. [0003] When using traditional statistical analysis metho...

AI Technical Summary

Problems solved by technology

[0004] The purpose of this patent is to solve the problem that traditional statistical analysis methods need to make assumptions about the relationship between data distribution and variables before analysis and application. Data mining technology based on big data does not need to make any assumptions about data distribution. Algorithms automatically find hidden relationships or regularities between variables

Aiming at the low efficiency of traditional statistical analysis methods in processing real-time and massive data, big data-based distributed message queues, stream computing, memory computing and distributed parallel computing technologies can realize data collection and processing in a highly efficient, concise and real-time manner

Images