Short-term load prediction method based on particle swarm optimization least squares support vector machine

Abstract

The present invention relates to a short-term load prediction method based on a particle swarm optimization least squares support vector machine. Aiming at the deficiency of a single kernel function least squares support vector machine model, the Gaussian kernel function and the Polynomial kernel function are combined to obtain a new hybrid kernel function so as to improve the learning ability and the generalization ability of the least squares support vector machine model; the particle swarm optimization algorithm based on double populations is employed to optimize parameters of the least squares support vector machine of the hybrid kernel function, the particle swarm optimization algorithm based on double populations has advantages of good global search and local search performances, and a strategy having dynamic accelerated factors is employed so as to greatly increase the variety of particles and prevent the search from being caught in a local extremum. The short-term load prediction method based on the particle swarm optimization least squares support vector machine maximally utilizes information in computation, and in the process of selecting the optimal parameter value, the average mean square error of load data and actual data is employed as the adaptation value of the particle swarm optimization algorithm so as to improve the short-item load prediction accuracy value.

Description

technical field [0001] This paper relates to the field of electric power engineering, especially a short-term load forecasting method based on particle swarm optimization least squares support vector machine. Background technique [0002] Short-term load forecasting mainly refers to the power load in the next 1 to 7 days. With the deepening of the system reform of my country's electric power industry, electric power related enterprises gradually enter the market, and it will become inevitable for their operation mode to change from monopoly operation to market competition. Load forecasting is an important task in the power industry. It is not only the prerequisite for ensuring the safe and stable operation of the power grid, but also the basis for quotations from power generators and electricity sales companies. At present, due to the uncertainty in the specific implementation process of load forecasting and the complex factors of quantification difficulty, some theoretical...

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Problems solved by technology

To solve the problem of low accuracy of short-term load forecasting results in existing technical measures

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