Real-Time Price Based Home Appliances Intelligent Control

Real-time price drives residential customers to involve in peak load shifting. It requires home appliances intelligent controller. Firstly, according to the historical prices, the controller can provide real-time price forecasting based on neural network. Secondly, factors including predicted value of real-time price, type, running time, expecting running status and ambient temperature of home appliances will be taken into account in calculating the predicted electricity expenses in different times of the day. The period with the lowest electricity expenses will be considered as the operation time of home appliances. Thirdly, the predicted value of real-time price, electricity consumption subsidy, operating cost and the amount of generating electricity are used to calculate the operation profit/loss of distribution generation which determines the period of DG. Finally, a large number of experiments are carried out to verify home appliances intelligent controller. The results showed that the controller can minimize residential electricity expenses and accomplishes peak load shifting.