Particle swarm algorithm-based variable weight combination power load short-term prediction method

Abstract

The invention discloses a particle swarm algorithm-based variable weight combination power load short-term prediction method. For the shortcoming of low prediction accuracy of a conventional single load prediction model and a fixed weight combination prediction model, the time correlation of power loads and the influence of other related factors on the power loads are comprehensively considered; multiple power load prediction models are combined; and a variable weight combination prediction model of power load short-term prediction is built. Meanwhile, for the shortcoming that a particle swarmoptimization variable weight parameter combination prediction method easily falls into a local optimal solution, a parameter dynamic adjustment particle swarm algorithm is established, optimization solving of weight parameters of the variable weight combination prediction model is realized, and finally short-term prediction of the power loads is realized. The combination prediction model is superior to a conventional load prediction method, a fixed weight combination prediction method and the particle swarm optimization variable weight parameter combination prediction method; and relatively high prediction accuracy is achieved.

Description

technical field [0001] The invention belongs to the field of power system load forecasting, and in particular relates to a short-term forecasting method for variable weight combined power load based on particle swarm algorithm. Background technique [0002] Power system scheduling is the key to ensure the reliability and safety of the power system, and short-term power load forecasting is the basis of power system scheduling. Effective and accurate forecasting of short-term power load can effectively improve the security and economy of the power grid. [0003] Short-term and ultra-short-term load forecasting are generally aimed at forecasting hours and below, and are mainly used for power system dispatching. Due to its short forecast period, the forecast method is required to have a faster forecast time. In addition, short-term forecasting and ultra-short-term forecasting also require high accuracy. [0004] With the rapid development of my country's economy, the power de...

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