基于隐马尔可夫模型的居民用电量预测

Power load forecasting is the basis of power system planning and it is also an important part of the electricity market, while electricity consumption of the residents is a most potential growth point of the electricity market in the coming period. Based on Hidden Markov model and combining K-Means clustering algorithm, a new electricity load forecasting method is proposed. The data of Beijing residential electricity consumption from 1978 to 2012 is chosen to make an empirical analysis on the basis. The status quo and characteristics of the Beijing residential electricity consumption is discussed and a prediction of electricity consumption is made in the next few years. Comparing with the general linear regression model, the new prediction method based on hidden Markov model is more effective and feasible.