Abstract: With the development of smart grid, the scale and types of data obtained from dispatch control systems increase exponentially, and dealing with these data is relatively complex. In order to better perform power dispatching to provide corresponding decision support for power system and better serve customers to meet the users power needs at different times, this paper proposes a G-DSM algorithm based on genetic algorithm, which can control server appliances. In the algorithm, the load scheduling problem is defined as cost minimization problem and solved by genetic algorithm. The algorithm combines with the large amount of power big data obtained from the user side to plan the users power demand, reduces the users cost and peak power load, thereby avoiding the waste of power resources and improving the work efficiency of the power grid. Experimental results show that the algorithm has good feasibility and is easy to implement in actual operation.

Key words: big data, smart grid, electricity demands, genetic algorithm