A Power Load Forecasting Method Based on Typical Daily Load Characteristics

Abstract

The invention discloses a typical daily load characteristic-based power load forecasting method, including: collecting power load data of users in a set industry in a set area, and performing preprocessing on the data; obtaining typical daily load curves of the users and an industry overall load curve; obtaining a correlation coefficient of the typical daily load curves of the users; classifying the users according to a power utilization laws of the users; and selecting a user whose power load change trend has the highest consistency with an industry overall load change, and forecasting power load data of an overall industry through the power utilization behavior laws of the user. The typical daily load characteristic-based power load forecasting method provided by the invention has the beneficial effects of being capable of deriving a forecast of an abnormality of a specific industry and even a whole society power load abnormality from an abnormality of a certain user power load, improving accuracy of a power load forecasting result, and providing a power guarantee for reasonable economic dispatching of an electric power system, reduction of production cost, and prevention of a large-area power failure of a power grid or a power grid breakdown.

Description

technical field [0001] The invention relates to the technical field of power load analysis, in particular to a power load prediction method based on typical daily load characteristics. Background technique [0002] With the development of the economy, the power consumption is increasing year by year, and the diversification and complexity of the power load have put forward higher requirements for the decision-making theory, management methods and technical support of the power load. However, there are still many unreasonable problems in the current work. , unsatisfactory problems: [0003] 1. The analysis of power load focuses on the macro perspective [0004] At present, domestic analysis of power load can only do post-event analysis of power load data, and can only roughly grasp the overall load law changes from a macro level, and cannot do specific analysis on the load characteristics of a certain industry or a certain customer. [0005] 2. The degree of intelligence of...

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Problems solved by technology

[0004] At present, the domestic analysis of power load can only be done after the fact. It can only grasp the overall load law changes from a macro level, and cannot do specific analysis on the load characteristics of a certain industry or a certain customer.

[0005] 2. The degree of intelligence of power load forecasting is not enough

[0006] At present, the forecasting of power load usually uses the display of data and reports as the main means, and the staff often need to use their own work experience to perform secondary processing on the data in order to obtain effective judgments; such a forecasting method, on the one hand, the power load The prediction results have a great relationship with the actual experience and theoretical level of the analysts; on the other hand, when the amount of data is large, it will greatly increase the workload of the forecasters, and the prediction results cannot be effectively comprehensive coverage market status of

[0007] 3. The early warning mechanism for power load changes is not perfect

[0008] At present, the early warning of power load changes at home and abroad often focuses on macro and mesoscopic perspectives, and forecasts from the perspectives of economic changes and industry changes. Due to untimely data acquisition, the best early warning opportunities are often missed, and even only post-event analysis can not be performed. To the reminder function of early warning

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