Ultra-short-term node load prediction method and system based on real-time electricity price

Abstract

The invention provides an ultra-short-term node load prediction method based on the real-time electricity price. The ultra-short-term node load prediction method includes the steps of: obtaining historical data of the node day-ahead clearing electricity price, a node day-ahead transaction load, the node real-time electricity price and the node actual load of the N days before a prediction day; calculating an electricity price difference delta P between the node day-ahead clearing electricity price and the node real-time electricity price, and calculating a load difference delta L between the node day-ahead transaction load and the node actual load; obtaining training samples and a training set according to the delta P and the delta L; obtaining a function relation between the electricity price deviation and the load fluctuation according to a data training set of the N days before the prediction day and the machine learning algorithm; and obtaining an ultra-short-term node load prediction model according to the function relation between the electricity price deviation and the load fluctuation. The method carries out power system load prediction on the basis of considering the influence of the real-time electricity price, effectively improves the accuracy of load prediction, and provides high-quality, high-precision basic data for power trading, power grid dispatching operationand the like.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a method and system for ultra-short-term node load forecasting based on real-time electricity prices. Background technique [0002] Accurate power system load forecasting is an important prerequisite for the power system to rationally arrange power generation, transmission, distribution, and use. Load forecasting technology is directly used to arrange power dispatching plans and conduct power grid safety checks, and its accuracy directly affects the safety of the power system. sex and economy. Therefore, mastering the law that affects load changes and improving its prediction accuracy is the basis for realizing the refined management of power system economic dispatch. [0003] At present, short-term load forecasting methods are mainly divided into traditional forecasting methods and intelligent forecasting methods. Traditional forecasting methods mainly include time series...

AI Technical Summary

Problems solved by technology

[0007] The present invention provides an ultra-short-term node load forecasting method based on real-time electricity prices to solve the technical problem that the load forecast of the existing power system does not consider the influence of real-time electricity prices, resulting in low accuracy of load forecasting, so that when real-time electricity prices are considered Power system load forecasting based on the influence of the power system can effectively improve the accuracy of load forecasting and provide high-quality, high-precision basic data for power trading, power grid dispatching and operation, and power grid security checks.

Images