A method of load volatility auto-identification and its application in demand side management

Knowing the characteristics of customers´ electrical load volatility can help to understand their usage behavior preferences, which is very useful to the utilities´ business such as demand side management. This paper presents a new self-adaptive method to auto-identify the volatility characters of customer´s time series electricity load pattern. The method can successfully recognize the main fluctuations of a load pattern and effectively filter out the random small turbulences which cannot represent the load volatility. The simulation results show that this method is effective and can dramatically improve the performance of customer electricity consumption behavior analysis. Finally the application of this method in demand side management is proposed.