A risk-considered stochastic home load management under real-time electricity prices

Electricity prices based on real-time pricing (RTP) strategy provides consumers the opportunity to respond to the price changes and hence, reduce their electricity bills. Automatic home load control systems also help consumers to simply manage their usage profile more efficiently. This paper proposes a stochastic formulation for automatic home load controllers to schedule the operation period of various home appliances such that the expected electricity payment is minimized. The level of risk imposed by price volatility during the following hours is also taken into consideration in the developed formulation. Difference between the expected payment and the payment in the worst scenario is used as the risk measure. The price uncertainty is modeled via normal probability density functions with increasing standard deviations. Finally, effectiveness of the developed formulation is demonstrated by applying to a typical home.