Electricity price risk prediction method and device based on Monte Carlo

Abstract

The invention provides an electricity price risk prediction method and device based on Monte Carlo. The method comprises the steps of obtaining historical data of an electricity market; calculating and generating a system residual capacity ratio historical data set and a blocking degree historical data set, and combining every two data sets to generate a historical data two-dimensional point set; calculating and generating a system residual capacity ratio random data set and a blocking degree random data set, and combining the data sets in pairs to generate a random data two-dimensional point set; calculating an electricity price mapping relation, and calculating and forming an electricity price level data set according to the electricity price mapping relation; and calculating the electricity price risk level of the unprocessed node according to the electricity price level data set and a preset confidence level. According to the method and device, the random data set similar to the historical data set is generated through the Monte Carlo method, the problem that the prediction precision is insufficient due to the fact that the number of medium-and-long-term electricity price prediction samples is too small is solved, and therefore electricity price risk prediction can be accurately and comprehensively carried out.

Description

technical field [0001] The invention relates to the technical field of risk prediction, in particular to a Monte Carlo-based electricity price risk prediction method and device. Background technique [0002] With the gradual advancement of the historical reform of electricity, the price level of electricity is constantly changing due to the influence of various factors such as the relationship between market supply and demand, the market power of market players, and the cost of electricity production. In the market environment, accurate electricity price risk prediction is of great significance for market operators to implement market supervision and market entities to formulate trading strategies. [0003] At present, the commonly used electricity price risk quantification method is Value at Risk (VaR). This method accurately quantifies the electricity price risk by calculating the maximum possible loss of a product in a specific future period under a certain probability l...

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Problems solved by technology

[0004] In the early stage of electricity market construction, historical supply and demand data and clearing price data are often less than those in mature electricity markets. Traditional electricity price risk prediction based on Monte Carlo methods will cause large prediction deviations due to the small number of historical data samples.

How to reasonably expand the data sample based on the existing data set is a problem to be solved in the electricity price risk prediction through the Monte Carlo method. In addition, the traditional electricity price risk prediction method matching the influencing factors of the electricity price cannot fully reflect the changes in the key boundary conditions in the electricity market. , how to obtain a definite electricity price prediction result through reasonable mapping is also a key issue in electricity price risk prediction

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