A Support Vector Machine Short-Term Load Forecasting Method

Abstract

The invention relates to a method for forecasting a short-term load of a support vector machine. The method comprises the following steps of: 1, selecting load data and weather data before a forecast date, and constructing a support vector machine model by adopting a particle swarm optimization (PSO) clustering algorithm based on a K mean value; and 2, inputting a new sample for forecasting. By the method, after historical data samples are classified, the sample characteristic is relatively obvious; therefore, for specific mode, the generalization capacity of the support vector machine is improved according to a variation rule from learning of relatively few samples to load; furthermore, the historical samples are clustered by adopting the PSO-K mean value clustering method, so that relatively high global convergence is achieved; and moreover, the support vector machine model is constructed for each classification, so that the calculation efficiency of the support vector machine is improved. By the method, when a large scale of data is analyzed, on the premise of keeping the forecast precision, the forecast efficiency is improved; and the load data can be forecasted precisely, quickly and in real time.

Description

technical field [0001] The invention relates to a load forecasting method, in particular to a support vector machine short-term load forecasting method, which belongs to the field of electric power forecasting. Background technique [0002] Power load forecasting is an important research issue in the field of power systems. It refers to exploring the internal relationship between power loads through the analysis and research of historical data based on the known power system, economy, society, weather, etc. and the law of development and change, and make pre-estimation and speculation on the development and change of load. [0003] Scientific prediction is the basis and guarantee for correct decision-making. Power load forecasting is a very important content in power dispatching, an important part of the power management system, and a prerequisite for safe and economical operation of the power grid. The stable operation of the power system requires that the power generatio...

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Problems solved by technology

[0023] Aiming at the disadvantages of complex calculation and low generalization ability of the existing forecasting methods, the present invention provides a short-term load forecasting method for support vector machines based on the K-means PSO (ParticleSwarmOptimization) clustering algorithm with a simple model and strong generalization ability

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