Power dispatching online trend early warning system based on ultra short term load prediction

A technology for short-term load forecasting and load forecasting, which is applied in the field of power dispatching online trend warning system, power grid short-term trend warning and post-accident post-processing plans, which can solve problems such as low level of intelligence and cognitive impairment due to massive information.

Inactive Publication Date: 2016-07-20
STATE GRID LIAONING ELECTRIC POWER RES INST +1
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Problems solved by technology

However, when the power grid is in an abnormal state, it still needs to rely on human experience for judgment and processing, and dispatchers are prone to cognitive impairment when they need to process massive

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  • Power dispatching online trend early warning system based on ultra short term load prediction
  • Power dispatching online trend early warning system based on ultra short term load prediction
  • Power dispatching online trend early warning system based on ultra short term load prediction

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Embodiment Construction

[0036] The present invention is a power dispatching online trend early warning system based on ultra-short-term load forecasting, which specifically includes the following operation steps:

[0037] 1. Short-term load forecasting based on big data analysis of electricity consumption.

[0038] Use time series methods for short-term load forecasting. Time series method is a quantitative forecasting method, which is widely used as a commonly used forecasting method in data mining. The two tasks of time series modeling are to analyze how the current data is affected by the data of the previous periods, and the other is the regularity of the changes in time. The time series algorithm selected by the present invention is the ARIMA model. The full name of ARIMA model is AutoRegressiveIntegratedMovingAverageModel (ARIMA). It is a well-known time series forecasting method proposed by Box and Jenkins in the early 1970s, so it is also called Box-Jenkins model. , Box-Jenkins method. Among t...

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Abstract

The invention relates to the technical field of applying an online safety analysis result to load prediction, and particularly relates to a power dispatching online trend early warning system based on ultra short term load prediction. Particularly, through statistics, analysis and prediction on load data, a power grid future trend is calculated, and a power grid short term trend early warning and accident post-treatment plan is formed. The system of the invention comprises the following operation steps of short term load prediction based on electricity consumption large data analysis, trend tendency analysis through ultra short term load obtained based on an ARIMA algorithm, power grid risk assessment and warning, equipment maintenance schedule management, data access panoramic surveillance, treatment in the accident and power supply restoration after the accident. Linkage between the online trend early warning and dispatching plan change information can be realized, and a trend analysis early warning and assistant decision-making system with integration of a province and regions can be formed.

Description

Technical field [0001] The invention relates to the application of online safety analysis results in the technical field of load forecasting, and in particular to a power dispatching online trend warning system based on ultra-short-term load forecasting. Specifically, the future of the power grid is calculated by statistics, analysis and forecasting of load data The trend is to form a short-term trend warning and post-accident handling plan for the power grid. Background technique [0002] At present, the safety and stability analysis of power grids in various provinces has gradually developed from offline to online. Based on the D5000 platform, an online safety analysis system including static, transient, dynamic, voltage, frequency, small disturbance stability calculation and short-circuit current calculation has been widely used. However, when the power grid is in an abnormal state, it still needs to rely on manual experience for judgment and processing, and dispatchers are p...

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 曾辉马千金晓明刘淼朱钰唐俊刺孙文涛李铁姜枫冯占稳朱伟峰崔岱陈晓东李家珏王超韩子娇刘罡王爱华高潇姜山王顺江张建方景锋
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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