An intelligent task scheduling algorithm of electricity consumption for reducing the load peak

Smart electricity consumption technology is an important part of smart grid, and task scheduling of household electricity consumption is one of the important applications of smart electricity consumption researches in household. However, the lack of efficient intelligent scheduling optimization algorithms has restricted its application. The task of electricity consumption is defined according to the characteristics of household electricity consumption, which are divided into two types of interruptible and non-interruptible tasks. And then the model of task scheduling problem of household electricity consumption is established. The objective of the model is to reduce the load peak of one day in household. For the model´s optimization objective, an efficient intelligent task scheduling optimization algorithm is designed based on an improved genetic algorithm. Experiments show that the designed algorithm can obtain a better result for the task arrangement of electricity consumption, reduce the load peak effectively, and has certain practical value.